2025-09-07T07:45:24.8515662Z Current runner version: '2.328.0' 2025-09-07T07:45:24.8521365Z Runner name: 'i-0b7d0f7dc0527ca9b-1003' 2025-09-07T07:45:24.8522233Z Runner group name: 'default' 2025-09-07T07:45:24.8523040Z Machine name: '5b251226417a' 2025-09-07T07:45:24.8525548Z ##[group]GITHUB_TOKEN Permissions 2025-09-07T07:45:24.8527580Z Contents: read 2025-09-07T07:45:24.8528151Z Metadata: read 2025-09-07T07:45:24.8528662Z ##[endgroup] 2025-09-07T07:45:24.8530789Z Secret source: Actions 2025-09-07T07:45:24.8531523Z Prepare workflow directory 2025-09-07T07:45:24.9019039Z Prepare all required actions 2025-09-07T07:45:24.9053957Z Getting action download info 2025-09-07T07:45:25.2509298Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd) 2025-09-07T07:45:26.7120180Z Download action repository 'pytorch/pytorch@main' (SHA:ada43ed39c80b746b4822c92640a1882619e2795) 2025-09-07T07:45:43.9238723Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-09-07T07:45:44.2796631Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-09-07T07:45:44.5769143Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-09-07T07:45:44.8935917Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T07:45:45.2632125Z Getting action download info 2025-09-07T07:45:45.4038385Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-09-07T07:45:45.7222997Z Getting action download info 2025-09-07T07:45:45.8532349Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-09-07T07:45:46.1791643Z Getting action download info 2025-09-07T07:45:46.3069219Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-09-07T07:45:46.5803758Z Getting action download info 2025-09-07T07:45:46.7262418Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634) 2025-09-07T07:45:46.7266528Z ##[group] Inputs 2025-09-07T07:45:46.7266868Z build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T07:45:46.7272531Z test-matrix: {"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T07:45:46.7278063Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:45:46.7278773Z sync-tag: 2025-09-07T07:45:46.7279558Z timeout-minutes: 1440 2025-09-07T07:45:46.7279770Z use-gha: 2025-09-07T07:45:46.7280802Z 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 2025-09-07T07:45:46.7281707Z s3-bucket: gha-artifacts 2025-09-07T07:45:46.7281909Z aws-role-to-assume: 2025-09-07T07:45:46.7282428Z disable-monitor: false 2025-09-07T07:45:46.7282664Z monitor-log-interval: 15 2025-09-07T07:45:46.7282884Z monitor-data-collect-interval: 4 2025-09-07T07:45:46.7283142Z ##[endgroup] 2025-09-07T07:45:46.7283466Z Complete job name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T07:45:46.7736969Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-09-07T07:45:46.7737713Z with: 2025-09-07T07:45:46.7738412Z github-secret: *** 2025-09-07T07:45:46.7739032Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-09-07T07:45:46.7739755Z activate-with-label: false 2025-09-07T07:45:46.7740054Z label: with-ssh 2025-09-07T07:45:46.7740576Z remove-existing-keys: true 2025-09-07T07:45:46.7740926Z fail-silently: true 2025-09-07T07:45:46.7741518Z env: 2025-09-07T07:45:46.7741744Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:46.7742123Z ##[endgroup] 2025-09-07T07:45:46.8827933Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-09-07T07:45:46.8828679Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-09-07T07:45:46.9014247Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-09-07T07:45:46.9014615Z with: 2025-09-07T07:45:46.9014781Z no-sudo: true 2025-09-07T07:45:46.9014966Z submodules: recursive 2025-09-07T07:45:46.9015163Z fetch-depth: 0 2025-09-07T07:45:46.9015322Z env: 2025-09-07T07:45:46.9015476Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:46.9015687Z ##[endgroup] 2025-09-07T07:45:46.9088948Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:46.9089715Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:45:46.9108663Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:45:46.9108984Z env: 2025-09-07T07:45:46.9109151Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:46.9109357Z ##[endgroup] 2025-09-07T07:45:46.9258062Z ##[group]Run actions/checkout@v4 2025-09-07T07:45:46.9258295Z with: 2025-09-07T07:45:46.9258486Z ref: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:45:46.9258729Z fetch-depth: 0 2025-09-07T07:45:46.9258909Z submodules: recursive 2025-09-07T07:45:46.9259091Z show-progress: false 2025-09-07T07:45:46.9259284Z repository: pytorch/pytorch 2025-09-07T07:45:46.9259834Z token: *** 2025-09-07T07:45:46.9259998Z ssh-strict: true 2025-09-07T07:45:46.9260169Z ssh-user: git 2025-09-07T07:45:46.9260508Z persist-credentials: true 2025-09-07T07:45:46.9260721Z clean: true 2025-09-07T07:45:46.9260904Z sparse-checkout-cone-mode: true 2025-09-07T07:45:46.9261121Z fetch-tags: false 2025-09-07T07:45:46.9261284Z lfs: false 2025-09-07T07:45:46.9261458Z set-safe-directory: true 2025-09-07T07:45:46.9261645Z env: 2025-09-07T07:45:46.9261883Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:45:46.9262072Z ##[endgroup] 2025-09-07T07:45:47.0233102Z Syncing repository: pytorch/pytorch 2025-09-07T07:45:47.0234358Z ##[group]Getting Git version info 2025-09-07T07:45:47.0234715Z Working directory is '/home/charlie/_work/pytorch/pytorch' 2025-09-07T07:45:47.0235196Z [command]/usr/bin/git version 2025-09-07T07:45:47.0238907Z git version 2.50.1 2025-09-07T07:45:47.0262883Z ##[endgroup] 2025-09-07T07:45:47.0274668Z Temporarily overriding HOME='/home/charlie/_work/_temp/87280e47-5157-4068-bc5f-8d1c79c236c6' before making global git config changes 2025-09-07T07:45:47.0275366Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T07:45:47.0279431Z [command]/usr/bin/git config --global --add safe.directory /home/charlie/_work/pytorch/pytorch 2025-09-07T07:45:47.0325258Z Deleting the contents of '/home/charlie/_work/pytorch/pytorch' 2025-09-07T07:45:47.0328346Z ##[group]Initializing the repository 2025-09-07T07:45:47.0331676Z [command]/usr/bin/git init /home/charlie/_work/pytorch/pytorch 2025-09-07T07:45:47.0381884Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-09-07T07:45:47.0382392Z hint: is subject to change. To configure the initial branch name to use in all 2025-09-07T07:45:47.0382931Z hint: of your new repositories, which will suppress this warning, call: 2025-09-07T07:45:47.0383244Z hint: 2025-09-07T07:45:47.0383485Z hint: git config --global init.defaultBranch 2025-09-07T07:45:47.0383749Z hint: 2025-09-07T07:45:47.0384033Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-09-07T07:45:47.0384451Z hint: 'development'. The just-created branch can be renamed via this command: 2025-09-07T07:45:47.0384766Z hint: 2025-09-07T07:45:47.0384947Z hint: git branch -m 2025-09-07T07:45:47.0385154Z hint: 2025-09-07T07:45:47.0385415Z hint: Disable this message with "git config set advice.defaultBranchName false" 2025-09-07T07:45:47.0385872Z Initialized empty Git repository in /home/charlie/_work/pytorch/pytorch/.git/ 2025-09-07T07:45:47.0392705Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-09-07T07:45:47.0435068Z ##[endgroup] 2025-09-07T07:45:47.0435468Z ##[group]Disabling automatic garbage collection 2025-09-07T07:45:47.0437384Z [command]/usr/bin/git config --local gc.auto 0 2025-09-07T07:45:47.0467363Z ##[endgroup] 2025-09-07T07:45:47.0467676Z ##[group]Setting up auth 2025-09-07T07:45:47.0473126Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T07:45:47.0502832Z [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' || :" 2025-09-07T07:45:47.0759451Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T07:45:47.0788672Z [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' || :" 2025-09-07T07:45:47.1026935Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:45:47.1063582Z ##[endgroup] 2025-09-07T07:45:47.1063993Z ##[group]Fetching the repository 2025-09-07T07:45:47.1070374Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:46:51.9041342Z From https://github.com/pytorch/pytorch 2025-09-07T07:46:51.9042020Z * [new branch] 160583 -> origin/160583 2025-09-07T07:46:51.9042782Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-09-07T07:46:51.9045794Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-09-07T07:46:51.9046480Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-09-07T07:46:51.9047210Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-09-07T07:46:51.9047914Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-09-07T07:46:51.9048621Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-09-07T07:46:51.9050366Z * [new branch] NicoshevSVE128 -> origin/NicoshevSVE128 2025-09-07T07:46:51.9052151Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-09-07T07:46:51.9053752Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-09-07T07:46:51.9055162Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-09-07T07:46:51.9056665Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-09-07T07:46:51.9058311Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-09-07T07:46:51.9059946Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-09-07T07:46:51.9061844Z * [new branch] VLA_exp -> origin/VLA_exp 2025-09-07T07:46:51.9064110Z * [new branch] actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor 2025-09-07T07:46:51.9065762Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-09-07T07:46:51.9067463Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-09-07T07:46:51.9069146Z * [new branch] add-vllm-nightly-build -> origin/add-vllm-nightly-build 2025-09-07T07:46:51.9070778Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-09-07T07:46:51.9072467Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-09-07T07:46:51.9074035Z * [new branch] addsimde -> origin/addsimde 2025-09-07T07:46:51.9076173Z * [new branch] addvllmtest -> origin/addvllmtest 2025-09-07T07:46:51.9077909Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-09-07T07:46:51.9079477Z * [new branch] adi/test -> origin/adi/test 2025-09-07T07:46:51.9081312Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-09-07T07:46:51.9082915Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-09-07T07:46:51.9084490Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-09-07T07:46:51.9086435Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-09-07T07:46:51.9087746Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-09-07T07:46:51.9089392Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-09-07T07:46:51.9092430Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-09-07T07:46:51.9093950Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-09-07T07:46:51.9095518Z * [new branch] alt-disable -> origin/alt-disable 2025-09-07T07:46:51.9097802Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-09-07T07:46:51.9099393Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-09-07T07:46:51.9101293Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-09-07T07:46:51.9103147Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-09-07T07:46:51.9104693Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-09-07T07:46:51.9106272Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-09-07T07:46:51.9107916Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-09-07T07:46:51.9109412Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-09-07T07:46:51.9111319Z * [new branch] angelayi/fake_cache_empty -> origin/angelayi/fake_cache_empty 2025-09-07T07:46:51.9112866Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-09-07T07:46:51.9114296Z * [new branch] angelayi/item -> origin/angelayi/item 2025-09-07T07:46:51.9115797Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-09-07T07:46:51.9117280Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-09-07T07:46:51.9118917Z * [new branch] angelayi/pattern -> origin/angelayi/pattern 2025-09-07T07:46:51.9120666Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-09-07T07:46:51.9122679Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-09-07T07:46:51.9124240Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-09-07T07:46:51.9125793Z * [new branch] 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2025-09-07T07:46:52.8619884Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-09-07T07:46:52.8621557Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-09-07T07:46:52.8622970Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-09-07T07:46:52.8624627Z * [new tag] ciflow/binaries/156049 -> ciflow/binaries/156049 2025-09-07T07:46:52.8625259Z * [new tag] ciflow/binaries/156712 -> ciflow/binaries/156712 2025-09-07T07:46:52.8626243Z * [new tag] ciflow/binaries/157432 -> ciflow/binaries/157432 2025-09-07T07:46:52.8627197Z * [new tag] ciflow/binaries/157685 -> ciflow/binaries/157685 2025-09-07T07:46:52.8628136Z * [new tag] ciflow/binaries/157689 -> ciflow/binaries/157689 2025-09-07T07:46:52.8629135Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-09-07T07:46:52.8629894Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-09-07T07:46:52.8631222Z * [new tag] ciflow/binaries/160720 -> ciflow/binaries/160720 2025-09-07T07:46:52.8632118Z * [new tag] ciflow/binaries/162080 -> ciflow/binaries/162080 2025-09-07T07:46:52.8632993Z * [new tag] ciflow/binaries/162329 -> ciflow/binaries/162329 2025-09-07T07:46:52.8634232Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-09-07T07:46:52.8635138Z * [new tag] ciflow/binaries_libtorch/156711 -> ciflow/binaries_libtorch/156711 2025-09-07T07:46:52.8635993Z * [new tag] ciflow/binaries_libtorch/157432 -> ciflow/binaries_libtorch/157432 2025-09-07T07:46:52.8637220Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-09-07T07:46:52.8637994Z * [new tag] ciflow/binaries_wheel/156711 -> ciflow/binaries_wheel/156711 2025-09-07T07:46:52.8638950Z * [new tag] ciflow/binaries_wheel/157432 -> ciflow/binaries_wheel/157432 2025-09-07T07:46:52.8639812Z * [new tag] ciflow/binaries_wheel/162136 -> ciflow/binaries_wheel/162136 2025-09-07T07:46:52.8641153Z * [new tag] ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252 2025-09-07T07:46:52.8642058Z * [new tag] ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325 2025-09-07T07:46:52.8643372Z * [new tag] ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703 2025-09-07T07:46:52.8644609Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-09-07T07:46:52.8645531Z * [new tag] ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984 2025-09-07T07:46:52.8646411Z * [new tag] ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003 2025-09-07T07:46:52.8647275Z * [new tag] ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011 2025-09-07T07:46:52.8648195Z * [new tag] ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026 2025-09-07T07:46:52.8649045Z * [new tag] ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033 2025-09-07T07:46:52.8649931Z * [new tag] ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040 2025-09-07T07:46:52.8651051Z * [new tag] ciflow/h100-symm-mem/162041 -> ciflow/h100-symm-mem/162041 2025-09-07T07:46:52.8652003Z * [new tag] ciflow/h100-symm-mem/162142 -> ciflow/h100-symm-mem/162142 2025-09-07T07:46:52.8652922Z * [new tag] ciflow/h100-symm-mem/162150 -> ciflow/h100-symm-mem/162150 2025-09-07T07:46:52.8653788Z * [new tag] ciflow/h100-symm-mem/162243 -> ciflow/h100-symm-mem/162243 2025-09-07T07:46:52.8654712Z * [new tag] ciflow/h100-symm-mem/162320 -> ciflow/h100-symm-mem/162320 2025-09-07T07:46:52.8655873Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-09-07T07:46:52.8657246Z * [new tag] ciflow/h100/160480 -> ciflow/h100/160480 2025-09-07T07:46:52.8658217Z * [new tag] ciflow/h100/161749 -> ciflow/h100/161749 2025-09-07T07:46:52.8659398Z * [new tag] ciflow/h100/162022 -> ciflow/h100/162022 2025-09-07T07:46:52.8660063Z * [new tag] ciflow/h100/162278 -> ciflow/h100/162278 2025-09-07T07:46:52.8661826Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592 2025-09-07T07:46:52.8662991Z * [new tag] ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592 2025-09-07T07:46:52.8664311Z * [new tag] ciflow/inductor-periodic/162063 -> ciflow/inductor-periodic/162063 2025-09-07T07:46:52.8665196Z * [new tag] ciflow/inductor-periodic/162227 -> ciflow/inductor-periodic/162227 2025-09-07T07:46:52.8666198Z * [new tag] ciflow/inductor-periodic/162323 -> ciflow/inductor-periodic/162323 2025-09-07T07:46:52.8667575Z * [new tag] ciflow/inductor-rocm/154170 -> ciflow/inductor-rocm/154170 2025-09-07T07:46:52.8668623Z * [new tag] ciflow/inductor-rocm/159146 -> ciflow/inductor-rocm/159146 2025-09-07T07:46:52.8669492Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-09-07T07:46:52.8670679Z * [new tag] ciflow/inductor-rocm/161715 -> ciflow/inductor-rocm/161715 2025-09-07T07:46:52.8671880Z * [new tag] ciflow/inductor-rocm/162053 -> ciflow/inductor-rocm/162053 2025-09-07T07:46:52.8672954Z * [new tag] ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056 2025-09-07T07:46:52.8674115Z * [new tag] ciflow/inductor/137400 -> ciflow/inductor/137400 2025-09-07T07:46:52.8675015Z * [new tag] ciflow/inductor/148180 -> ciflow/inductor/148180 2025-09-07T07:46:52.8675919Z * [new tag] ciflow/inductor/148328 -> ciflow/inductor/148328 2025-09-07T07:46:52.8676833Z * [new tag] ciflow/inductor/148484 -> ciflow/inductor/148484 2025-09-07T07:46:52.8677702Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-09-07T07:46:52.8678614Z * [new tag] ciflow/inductor/152624 -> ciflow/inductor/152624 2025-09-07T07:46:52.8679478Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-09-07T07:46:52.8680532Z * [new tag] ciflow/inductor/156049 -> ciflow/inductor/156049 2025-09-07T07:46:52.8681492Z * [new tag] ciflow/inductor/156592 -> ciflow/inductor/156592 2025-09-07T07:46:52.8682345Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-09-07T07:46:52.8683217Z * [new tag] ciflow/inductor/157685 -> ciflow/inductor/157685 2025-09-07T07:46:52.8684181Z * [new tag] ciflow/inductor/157686 -> ciflow/inductor/157686 2025-09-07T07:46:52.8685028Z * [new tag] ciflow/inductor/157689 -> ciflow/inductor/157689 2025-09-07T07:46:52.8685908Z * [new tag] ciflow/inductor/157699 -> ciflow/inductor/157699 2025-09-07T07:46:52.8686934Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-09-07T07:46:52.8687967Z * [new tag] ciflow/inductor/157994 -> ciflow/inductor/157994 2025-09-07T07:46:52.8688880Z * [new tag] ciflow/inductor/158091 -> ciflow/inductor/158091 2025-09-07T07:46:52.8689767Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-09-07T07:46:52.8691020Z * [new tag] ciflow/inductor/158404 -> ciflow/inductor/158404 2025-09-07T07:46:52.8692013Z * [new tag] ciflow/inductor/158647 -> ciflow/inductor/158647 2025-09-07T07:46:52.8693098Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-09-07T07:46:52.8694020Z * [new tag] ciflow/inductor/159146 -> ciflow/inductor/159146 2025-09-07T07:46:52.8695112Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-09-07T07:46:52.8696076Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-09-07T07:46:52.8696947Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-09-07T07:46:52.8698039Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-09-07T07:46:52.8699003Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-09-07T07:46:52.8700056Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-09-07T07:46:52.8701426Z * [new tag] ciflow/inductor/160161 -> ciflow/inductor/160161 2025-09-07T07:46:52.8702385Z * [new tag] ciflow/inductor/160174 -> ciflow/inductor/160174 2025-09-07T07:46:52.8703538Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-09-07T07:46:52.8704721Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-09-07T07:46:52.8705766Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-09-07T07:46:52.8706921Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-09-07T07:46:52.8707887Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-09-07T07:46:52.8708953Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-09-07T07:46:52.8710003Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-09-07T07:46:52.8711246Z * [new tag] ciflow/inductor/160480 -> ciflow/inductor/160480 2025-09-07T07:46:52.8712347Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-09-07T07:46:52.8713873Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-09-07T07:46:52.8714786Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-09-07T07:46:52.8715762Z * [new tag] ciflow/inductor/160685 -> ciflow/inductor/160685 2025-09-07T07:46:52.8716697Z * [new tag] ciflow/inductor/160686 -> ciflow/inductor/160686 2025-09-07T07:46:52.8717621Z * [new tag] ciflow/inductor/160687 -> ciflow/inductor/160687 2025-09-07T07:46:52.8718574Z * [new tag] ciflow/inductor/160688 -> ciflow/inductor/160688 2025-09-07T07:46:52.8719525Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-09-07T07:46:52.8720648Z * [new tag] ciflow/inductor/160706 -> ciflow/inductor/160706 2025-09-07T07:46:52.8721718Z * [new tag] ciflow/inductor/160729 -> ciflow/inductor/160729 2025-09-07T07:46:52.8722815Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-09-07T07:46:52.8723900Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-09-07T07:46:52.8724868Z * [new tag] ciflow/inductor/160843 -> ciflow/inductor/160843 2025-09-07T07:46:52.8726097Z * [new tag] ciflow/inductor/160869 -> ciflow/inductor/160869 2025-09-07T07:46:52.8727061Z * [new tag] ciflow/inductor/160920 -> ciflow/inductor/160920 2025-09-07T07:46:52.8728045Z * [new tag] ciflow/inductor/160928 -> ciflow/inductor/160928 2025-09-07T07:46:52.8729007Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-09-07T07:46:52.8729989Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-09-07T07:46:52.8731201Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-09-07T07:46:52.8732250Z * [new tag] ciflow/inductor/161109 -> ciflow/inductor/161109 2025-09-07T07:46:52.8733254Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-09-07T07:46:52.8734594Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-09-07T07:46:52.8735457Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-09-07T07:46:52.8736415Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-09-07T07:46:52.8737428Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-09-07T07:46:52.8738381Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-09-07T07:46:52.8739510Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-09-07T07:46:52.8740629Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-09-07T07:46:52.8741850Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-09-07T07:46:52.8742875Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-09-07T07:46:52.8744271Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-09-07T07:46:52.8745181Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-09-07T07:46:52.8746454Z * [new tag] ciflow/inductor/161442 -> ciflow/inductor/161442 2025-09-07T07:46:52.8747387Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-09-07T07:46:52.8748319Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-09-07T07:46:52.8749381Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-09-07T07:46:52.8750798Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-09-07T07:46:52.8751873Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-09-07T07:46:52.8752877Z * [new tag] ciflow/inductor/161534 -> ciflow/inductor/161534 2025-09-07T07:46:52.8753852Z * [new tag] ciflow/inductor/161595 -> ciflow/inductor/161595 2025-09-07T07:46:52.8754878Z * [new tag] ciflow/inductor/161596 -> ciflow/inductor/161596 2025-09-07T07:46:52.8756302Z * [new tag] ciflow/inductor/161630 -> ciflow/inductor/161630 2025-09-07T07:46:52.8757305Z * [new tag] ciflow/inductor/161667 -> ciflow/inductor/161667 2025-09-07T07:46:52.8758336Z * [new tag] ciflow/inductor/161670 -> ciflow/inductor/161670 2025-09-07T07:46:52.8759381Z * [new tag] ciflow/inductor/161673 -> ciflow/inductor/161673 2025-09-07T07:46:52.8760460Z * [new tag] ciflow/inductor/161674 -> ciflow/inductor/161674 2025-09-07T07:46:52.8761594Z * [new tag] ciflow/inductor/161675 -> ciflow/inductor/161675 2025-09-07T07:46:52.8762599Z * [new tag] ciflow/inductor/161693 -> ciflow/inductor/161693 2025-09-07T07:46:52.8763652Z * [new tag] ciflow/inductor/161695 -> ciflow/inductor/161695 2025-09-07T07:46:52.8764621Z * [new tag] ciflow/inductor/161715 -> ciflow/inductor/161715 2025-09-07T07:46:52.8765617Z * [new tag] ciflow/inductor/161730 -> ciflow/inductor/161730 2025-09-07T07:46:52.8766635Z * [new tag] ciflow/inductor/161732 -> ciflow/inductor/161732 2025-09-07T07:46:52.8767783Z * [new tag] ciflow/inductor/161744 -> ciflow/inductor/161744 2025-09-07T07:46:52.8768811Z * [new tag] ciflow/inductor/161746 -> ciflow/inductor/161746 2025-09-07T07:46:52.8769837Z * [new tag] ciflow/inductor/161747 -> ciflow/inductor/161747 2025-09-07T07:46:52.8771059Z * [new tag] ciflow/inductor/161819 -> ciflow/inductor/161819 2025-09-07T07:46:52.8772121Z * [new tag] ciflow/inductor/161821 -> ciflow/inductor/161821 2025-09-07T07:46:52.8773254Z * [new tag] ciflow/inductor/161828 -> ciflow/inductor/161828 2025-09-07T07:46:52.8774164Z * [new tag] ciflow/inductor/161879 -> ciflow/inductor/161879 2025-09-07T07:46:52.8775168Z * [new tag] ciflow/inductor/161880 -> ciflow/inductor/161880 2025-09-07T07:46:52.8776168Z * [new tag] ciflow/inductor/161881 -> ciflow/inductor/161881 2025-09-07T07:46:52.8777326Z * [new tag] ciflow/inductor/161907 -> ciflow/inductor/161907 2025-09-07T07:46:52.8778363Z * [new tag] ciflow/inductor/161914 -> ciflow/inductor/161914 2025-09-07T07:46:52.8779613Z * [new tag] ciflow/inductor/161924 -> ciflow/inductor/161924 2025-09-07T07:46:52.8780968Z * [new tag] ciflow/inductor/161936 -> ciflow/inductor/161936 2025-09-07T07:46:52.8782126Z * [new tag] ciflow/inductor/161938 -> ciflow/inductor/161938 2025-09-07T07:46:52.8783238Z * [new tag] ciflow/inductor/161939 -> ciflow/inductor/161939 2025-09-07T07:46:52.8784301Z * [new tag] ciflow/inductor/161940 -> ciflow/inductor/161940 2025-09-07T07:46:52.8785292Z * [new tag] ciflow/inductor/161955 -> ciflow/inductor/161955 2025-09-07T07:46:52.8786338Z * [new tag] ciflow/inductor/161957 -> ciflow/inductor/161957 2025-09-07T07:46:52.8787393Z * [new tag] ciflow/inductor/161975 -> ciflow/inductor/161975 2025-09-07T07:46:52.8788440Z * [new tag] ciflow/inductor/161977 -> ciflow/inductor/161977 2025-09-07T07:46:52.8789500Z * [new tag] ciflow/inductor/161978 -> ciflow/inductor/161978 2025-09-07T07:46:52.8790614Z * [new tag] ciflow/inductor/161979 -> ciflow/inductor/161979 2025-09-07T07:46:52.8791801Z * [new tag] ciflow/inductor/161980 -> ciflow/inductor/161980 2025-09-07T07:46:52.8792818Z * [new tag] ciflow/inductor/161988 -> ciflow/inductor/161988 2025-09-07T07:46:52.8793895Z * [new tag] ciflow/inductor/161994 -> ciflow/inductor/161994 2025-09-07T07:46:52.8794908Z * [new tag] ciflow/inductor/162013 -> ciflow/inductor/162013 2025-09-07T07:46:52.8795967Z * [new tag] ciflow/inductor/162014 -> ciflow/inductor/162014 2025-09-07T07:46:52.8797074Z * [new tag] ciflow/inductor/162017 -> ciflow/inductor/162017 2025-09-07T07:46:52.8798140Z * [new tag] ciflow/inductor/162021 -> ciflow/inductor/162021 2025-09-07T07:46:52.8799188Z * [new tag] ciflow/inductor/162023 -> ciflow/inductor/162023 2025-09-07T07:46:52.8800197Z * [new tag] ciflow/inductor/162027 -> ciflow/inductor/162027 2025-09-07T07:46:52.8801706Z * [new tag] ciflow/inductor/162029 -> ciflow/inductor/162029 2025-09-07T07:46:52.8802756Z * [new tag] ciflow/inductor/162030 -> ciflow/inductor/162030 2025-09-07T07:46:52.8803865Z * [new tag] ciflow/inductor/162031 -> ciflow/inductor/162031 2025-09-07T07:46:52.8804915Z * [new tag] ciflow/inductor/162033 -> ciflow/inductor/162033 2025-09-07T07:46:52.8806223Z * [new tag] ciflow/inductor/162052 -> ciflow/inductor/162052 2025-09-07T07:46:52.8807280Z * [new tag] ciflow/inductor/162053 -> ciflow/inductor/162053 2025-09-07T07:46:52.8808330Z * [new tag] ciflow/inductor/162056 -> ciflow/inductor/162056 2025-09-07T07:46:52.8809494Z * [new tag] ciflow/inductor/162063 -> ciflow/inductor/162063 2025-09-07T07:46:52.8810798Z * [new tag] ciflow/inductor/162066 -> ciflow/inductor/162066 2025-09-07T07:46:52.8811887Z * [new tag] ciflow/inductor/162068 -> ciflow/inductor/162068 2025-09-07T07:46:52.8813144Z * [new tag] ciflow/inductor/162081 -> ciflow/inductor/162081 2025-09-07T07:46:52.8814398Z * [new tag] ciflow/inductor/162088 -> ciflow/inductor/162088 2025-09-07T07:46:52.8815357Z * [new tag] ciflow/inductor/162089 -> ciflow/inductor/162089 2025-09-07T07:46:52.8816395Z * [new tag] ciflow/inductor/162094 -> ciflow/inductor/162094 2025-09-07T07:46:52.8817463Z * [new tag] ciflow/inductor/162098 -> ciflow/inductor/162098 2025-09-07T07:46:52.8818580Z * [new tag] ciflow/inductor/162101 -> ciflow/inductor/162101 2025-09-07T07:46:52.8819667Z * [new tag] ciflow/inductor/162102 -> ciflow/inductor/162102 2025-09-07T07:46:52.8820959Z * [new tag] ciflow/inductor/162104 -> ciflow/inductor/162104 2025-09-07T07:46:52.8822026Z * [new tag] ciflow/inductor/162106 -> ciflow/inductor/162106 2025-09-07T07:46:52.8823200Z * [new tag] ciflow/inductor/162108 -> ciflow/inductor/162108 2025-09-07T07:46:52.8824441Z * [new tag] ciflow/inductor/162126 -> ciflow/inductor/162126 2025-09-07T07:46:52.8825509Z * [new tag] ciflow/inductor/162149 -> ciflow/inductor/162149 2025-09-07T07:46:52.8826580Z * [new tag] ciflow/inductor/162164 -> ciflow/inductor/162164 2025-09-07T07:46:52.8827674Z * [new tag] ciflow/inductor/162166 -> ciflow/inductor/162166 2025-09-07T07:46:52.8828814Z * [new tag] ciflow/inductor/162169 -> ciflow/inductor/162169 2025-09-07T07:46:52.8829879Z * [new tag] ciflow/inductor/162170 -> ciflow/inductor/162170 2025-09-07T07:46:52.8831213Z * [new tag] ciflow/inductor/162171 -> ciflow/inductor/162171 2025-09-07T07:46:52.8832284Z * [new tag] ciflow/inductor/162183 -> ciflow/inductor/162183 2025-09-07T07:46:52.8833411Z * [new tag] ciflow/inductor/162189 -> ciflow/inductor/162189 2025-09-07T07:46:52.8834475Z * [new tag] ciflow/inductor/162190 -> ciflow/inductor/162190 2025-09-07T07:46:52.8835598Z * [new tag] ciflow/inductor/162191 -> ciflow/inductor/162191 2025-09-07T07:46:52.8836694Z * [new tag] ciflow/inductor/162194 -> ciflow/inductor/162194 2025-09-07T07:46:52.8838028Z * [new tag] ciflow/inductor/162200 -> ciflow/inductor/162200 2025-09-07T07:46:52.8839162Z * [new tag] ciflow/inductor/162201 -> ciflow/inductor/162201 2025-09-07T07:46:52.8840452Z * [new tag] ciflow/inductor/162208 -> ciflow/inductor/162208 2025-09-07T07:46:52.8841801Z * [new tag] ciflow/inductor/162211 -> ciflow/inductor/162211 2025-09-07T07:46:52.8842892Z * [new tag] ciflow/inductor/162216 -> ciflow/inductor/162216 2025-09-07T07:46:52.8844006Z * [new tag] ciflow/inductor/162220 -> ciflow/inductor/162220 2025-09-07T07:46:52.8845216Z * [new tag] ciflow/inductor/162222 -> ciflow/inductor/162222 2025-09-07T07:46:52.8846349Z * [new tag] ciflow/inductor/162227 -> ciflow/inductor/162227 2025-09-07T07:46:52.8847454Z * [new tag] ciflow/inductor/162238 -> ciflow/inductor/162238 2025-09-07T07:46:52.8848583Z * [new tag] ciflow/inductor/162239 -> ciflow/inductor/162239 2025-09-07T07:46:52.8849744Z * [new tag] ciflow/inductor/162240 -> ciflow/inductor/162240 2025-09-07T07:46:52.8851042Z * [new tag] ciflow/inductor/162244 -> ciflow/inductor/162244 2025-09-07T07:46:52.8852233Z * [new tag] ciflow/inductor/162245 -> ciflow/inductor/162245 2025-09-07T07:46:52.8853404Z * [new tag] ciflow/inductor/162262 -> ciflow/inductor/162262 2025-09-07T07:46:52.8854548Z * [new tag] ciflow/inductor/162275 -> ciflow/inductor/162275 2025-09-07T07:46:52.8855665Z * [new tag] ciflow/inductor/162278 -> ciflow/inductor/162278 2025-09-07T07:46:52.8856975Z * [new tag] ciflow/inductor/162284 -> ciflow/inductor/162284 2025-09-07T07:46:52.8857958Z * [new tag] ciflow/inductor/162286 -> ciflow/inductor/162286 2025-09-07T07:46:52.8859038Z * [new tag] ciflow/inductor/162288 -> ciflow/inductor/162288 2025-09-07T07:46:52.8860176Z * [new tag] ciflow/inductor/162293 -> ciflow/inductor/162293 2025-09-07T07:46:52.8861574Z * [new tag] ciflow/inductor/162294 -> ciflow/inductor/162294 2025-09-07T07:46:52.8862718Z * [new tag] ciflow/inductor/162295 -> ciflow/inductor/162295 2025-09-07T07:46:52.8863926Z * [new tag] ciflow/inductor/162296 -> ciflow/inductor/162296 2025-09-07T07:46:52.8865042Z * [new tag] ciflow/inductor/162298 -> ciflow/inductor/162298 2025-09-07T07:46:52.8866147Z * [new tag] ciflow/inductor/162307 -> ciflow/inductor/162307 2025-09-07T07:46:52.8867294Z * [new tag] ciflow/inductor/162309 -> ciflow/inductor/162309 2025-09-07T07:46:52.8868492Z * [new tag] ciflow/inductor/162311 -> ciflow/inductor/162311 2025-09-07T07:46:52.8869687Z * [new tag] ciflow/inductor/162312 -> ciflow/inductor/162312 2025-09-07T07:46:52.8871047Z * [new tag] ciflow/inductor/162315 -> ciflow/inductor/162315 2025-09-07T07:46:52.8873683Z * [new tag] ciflow/inductor/162316 -> ciflow/inductor/162316 2025-09-07T07:46:52.8875037Z * [new tag] ciflow/inductor/162318 -> ciflow/inductor/162318 2025-09-07T07:46:52.8876274Z * [new tag] ciflow/inductor/162323 -> ciflow/inductor/162323 2025-09-07T07:46:52.8877398Z * [new tag] ciflow/inductor/162341 -> ciflow/inductor/162341 2025-09-07T07:46:52.8878568Z * [new tag] ciflow/inductor/162345 -> ciflow/inductor/162345 2025-09-07T07:46:52.8880120Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-09-07T07:46:52.8881836Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-09-07T07:46:52.8883069Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-09-07T07:46:52.8884392Z * [new tag] ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994 2025-09-07T07:46:52.8885274Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-09-07T07:46:52.8886196Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-09-07T07:46:52.8887336Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-09-07T07:46:52.8888213Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-09-07T07:46:52.8889110Z * [new tag] ciflow/mps/161988 -> ciflow/mps/161988 2025-09-07T07:46:52.8889947Z * [new tag] ciflow/mps/162108 -> ciflow/mps/162108 2025-09-07T07:46:52.8891041Z * [new tag] ciflow/mps/162153 -> ciflow/mps/162153 2025-09-07T07:46:52.8891890Z * [new tag] ciflow/mps/162281 -> ciflow/mps/162281 2025-09-07T07:46:52.8893116Z * [new tag] ciflow/nightly/156049 -> ciflow/nightly/156049 2025-09-07T07:46:52.8894008Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-09-07T07:46:52.8895181Z * [new tag] ciflow/op-benchmark/157994 -> ciflow/op-benchmark/157994 2025-09-07T07:46:52.8896613Z * [new tag] ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529 2025-09-07T07:46:52.8897382Z * [new tag] ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715 2025-09-07T07:46:52.8898873Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-09-07T07:46:52.8899935Z * [new tag] ciflow/periodic/156703 -> ciflow/periodic/156703 2025-09-07T07:46:52.8900712Z * [new tag] ciflow/periodic/161715 -> ciflow/periodic/161715 2025-09-07T07:46:52.8901710Z * [new tag] ciflow/periodic/162021 -> ciflow/periodic/162021 2025-09-07T07:46:52.8902604Z * [new tag] ciflow/periodic/162323 -> ciflow/periodic/162323 2025-09-07T07:46:52.8903805Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-09-07T07:46:52.8904802Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-09-07T07:46:52.8905797Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-09-07T07:46:52.8906897Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-09-07T07:46:52.8908042Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-09-07T07:46:52.8909501Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-09-07T07:46:52.8910693Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-09-07T07:46:52.8911993Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-09-07T07:46:52.8913104Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-09-07T07:46:52.8914298Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-09-07T07:46:52.8915441Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-09-07T07:46:52.8916595Z * [new tag] ciflow/rocm-mi300/154170 -> ciflow/rocm-mi300/154170 2025-09-07T07:46:52.8917676Z * [new tag] ciflow/rocm-mi300/158747 -> ciflow/rocm-mi300/158747 2025-09-07T07:46:52.8918542Z * [new tag] ciflow/rocm-mi300/159146 -> ciflow/rocm-mi300/159146 2025-09-07T07:46:52.8919411Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-09-07T07:46:52.8920441Z * [new tag] ciflow/rocm-mi300/161715 -> ciflow/rocm-mi300/161715 2025-09-07T07:46:52.8921368Z * [new tag] ciflow/rocm-mi300/161957 -> ciflow/rocm-mi300/161957 2025-09-07T07:46:52.8922215Z * [new tag] ciflow/rocm-mi300/162053 -> ciflow/rocm-mi300/162053 2025-09-07T07:46:52.8923074Z * [new tag] ciflow/rocm-mi300/162056 -> ciflow/rocm-mi300/162056 2025-09-07T07:46:52.8924125Z * [new tag] ciflow/rocm-mi300/162112 -> ciflow/rocm-mi300/162112 2025-09-07T07:46:52.8924822Z * [new tag] ciflow/rocm-mi300/162245 -> ciflow/rocm-mi300/162245 2025-09-07T07:46:52.8925678Z * [new tag] ciflow/rocm-mi300/162278 -> ciflow/rocm-mi300/162278 2025-09-07T07:46:52.8926636Z * [new tag] ciflow/rocm-mi300/162288 -> ciflow/rocm-mi300/162288 2025-09-07T07:46:52.8927815Z * [new tag] ciflow/rocm-mi355/162053 -> ciflow/rocm-mi355/162053 2025-09-07T07:46:52.8928609Z * [new tag] ciflow/rocm-mi355/162056 -> ciflow/rocm-mi355/162056 2025-09-07T07:46:52.8929782Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-09-07T07:46:52.8930823Z * [new tag] ciflow/rocm/154170 -> ciflow/rocm/154170 2025-09-07T07:46:52.8932005Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-09-07T07:46:52.8932760Z * [new tag] ciflow/rocm/156592 -> ciflow/rocm/156592 2025-09-07T07:46:52.8933601Z * [new tag] ciflow/rocm/158747 -> ciflow/rocm/158747 2025-09-07T07:46:52.8934484Z * [new tag] ciflow/rocm/159146 -> ciflow/rocm/159146 2025-09-07T07:46:52.8935627Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-09-07T07:46:52.8936558Z * [new tag] ciflow/rocm/161715 -> ciflow/rocm/161715 2025-09-07T07:46:52.8937428Z * [new tag] ciflow/rocm/161972 -> ciflow/rocm/161972 2025-09-07T07:46:52.8938283Z * [new tag] ciflow/rocm/162052 -> ciflow/rocm/162052 2025-09-07T07:46:52.8939018Z * [new tag] ciflow/rocm/162053 -> ciflow/rocm/162053 2025-09-07T07:46:52.8939868Z * [new tag] ciflow/rocm/162056 -> ciflow/rocm/162056 2025-09-07T07:46:52.8940951Z * [new tag] ciflow/rocm/162112 -> ciflow/rocm/162112 2025-09-07T07:46:52.8942083Z * [new tag] ciflow/rocm/162278 -> ciflow/rocm/162278 2025-09-07T07:46:52.8942925Z * [new tag] ciflow/rocm/162288 -> ciflow/rocm/162288 2025-09-07T07:46:52.8943820Z * [new tag] ciflow/rocm/162305 -> ciflow/rocm/162305 2025-09-07T07:46:52.8945220Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-09-07T07:46:52.8946247Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-09-07T07:46:52.8947601Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-09-07T07:46:52.8948457Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-09-07T07:46:52.8949347Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-09-07T07:46:52.8950665Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-09-07T07:46:52.8951774Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-09-07T07:46:52.8952844Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-09-07T07:46:52.8953693Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-09-07T07:46:52.8954847Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-09-07T07:46:52.8955916Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-09-07T07:46:52.8956814Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-09-07T07:46:52.8957866Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-09-07T07:46:52.8959243Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-09-07T07:46:52.8959899Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-09-07T07:46:52.8961348Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-09-07T07:46:52.8962377Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-09-07T07:46:52.8963403Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-09-07T07:46:52.8964448Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-09-07T07:46:52.8965836Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-09-07T07:46:52.8966751Z * [new tag] ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329 2025-09-07T07:46:52.8967921Z * [new tag] ciflow/trunk/113258 -> ciflow/trunk/113258 2025-09-07T07:46:52.8968688Z * [new tag] ciflow/trunk/137400 -> ciflow/trunk/137400 2025-09-07T07:46:52.8969548Z * [new tag] ciflow/trunk/148180 -> ciflow/trunk/148180 2025-09-07T07:46:52.8970492Z * [new tag] ciflow/trunk/148328 -> ciflow/trunk/148328 2025-09-07T07:46:52.8971560Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-09-07T07:46:52.8972655Z * [new tag] ciflow/trunk/148919 -> ciflow/trunk/148919 2025-09-07T07:46:52.8973594Z * [new tag] ciflow/trunk/152624 -> ciflow/trunk/152624 2025-09-07T07:46:52.8974294Z * [new tag] ciflow/trunk/154170 -> ciflow/trunk/154170 2025-09-07T07:46:52.8975137Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-09-07T07:46:52.8976204Z * [new tag] ciflow/trunk/156049 -> ciflow/trunk/156049 2025-09-07T07:46:52.8976902Z * [new tag] ciflow/trunk/156703 -> ciflow/trunk/156703 2025-09-07T07:46:52.8977749Z * [new tag] ciflow/trunk/156711 -> ciflow/trunk/156711 2025-09-07T07:46:52.8978622Z * [new tag] ciflow/trunk/157432 -> ciflow/trunk/157432 2025-09-07T07:46:52.8979497Z * [new tag] ciflow/trunk/157685 -> ciflow/trunk/157685 2025-09-07T07:46:52.8980528Z * [new tag] ciflow/trunk/157689 -> ciflow/trunk/157689 2025-09-07T07:46:52.8981589Z * [new tag] ciflow/trunk/157699 -> ciflow/trunk/157699 2025-09-07T07:46:52.8982309Z * [new tag] ciflow/trunk/157813 -> ciflow/trunk/157813 2025-09-07T07:46:52.8983253Z * [new tag] ciflow/trunk/157994 -> ciflow/trunk/157994 2025-09-07T07:46:52.8984149Z * [new tag] ciflow/trunk/158091 -> ciflow/trunk/158091 2025-09-07T07:46:52.8984983Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-09-07T07:46:52.8986055Z * [new tag] ciflow/trunk/158404 -> ciflow/trunk/158404 2025-09-07T07:46:52.8986782Z * [new tag] ciflow/trunk/158647 -> ciflow/trunk/158647 2025-09-07T07:46:52.8987935Z * [new tag] ciflow/trunk/158846 -> ciflow/trunk/158846 2025-09-07T07:46:52.8988770Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-09-07T07:46:52.8989818Z * [new tag] ciflow/trunk/159682 -> ciflow/trunk/159682 2025-09-07T07:46:52.8990868Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-09-07T07:46:52.8991765Z * [new tag] ciflow/trunk/160161 -> ciflow/trunk/160161 2025-09-07T07:46:52.8992642Z * [new tag] ciflow/trunk/160236 -> ciflow/trunk/160236 2025-09-07T07:46:52.8993513Z * [new tag] ciflow/trunk/160329 -> ciflow/trunk/160329 2025-09-07T07:46:52.8994421Z * [new tag] ciflow/trunk/160480 -> ciflow/trunk/160480 2025-09-07T07:46:52.8995286Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-09-07T07:46:52.8996145Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-09-07T07:46:52.8997037Z * [new tag] ciflow/trunk/160843 -> ciflow/trunk/160843 2025-09-07T07:46:52.8997919Z * [new tag] ciflow/trunk/160869 -> ciflow/trunk/160869 2025-09-07T07:46:52.8998793Z * [new tag] ciflow/trunk/160928 -> ciflow/trunk/160928 2025-09-07T07:46:52.8999936Z * [new tag] ciflow/trunk/160940 -> ciflow/trunk/160940 2025-09-07T07:46:52.9001168Z * [new tag] ciflow/trunk/160943 -> ciflow/trunk/160943 2025-09-07T07:46:52.9002238Z * [new tag] ciflow/trunk/160953 -> ciflow/trunk/160953 2025-09-07T07:46:52.9003299Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-09-07T07:46:52.9004132Z * [new tag] ciflow/trunk/161178 -> ciflow/trunk/161178 2025-09-07T07:46:52.9005034Z * [new tag] ciflow/trunk/161349 -> ciflow/trunk/161349 2025-09-07T07:46:52.9006074Z * [new tag] ciflow/trunk/161350 -> ciflow/trunk/161350 2025-09-07T07:46:52.9006899Z * [new tag] ciflow/trunk/161351 -> ciflow/trunk/161351 2025-09-07T07:46:52.9007915Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-09-07T07:46:52.9008651Z * [new tag] ciflow/trunk/161405 -> ciflow/trunk/161405 2025-09-07T07:46:52.9009539Z * [new tag] ciflow/trunk/161406 -> ciflow/trunk/161406 2025-09-07T07:46:52.9010582Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-09-07T07:46:52.9011707Z * [new tag] ciflow/trunk/161468 -> ciflow/trunk/161468 2025-09-07T07:46:52.9012525Z * [new tag] ciflow/trunk/161499 -> ciflow/trunk/161499 2025-09-07T07:46:52.9013799Z * [new tag] ciflow/trunk/161527 -> ciflow/trunk/161527 2025-09-07T07:46:52.9014643Z * [new tag] ciflow/trunk/161534 -> ciflow/trunk/161534 2025-09-07T07:46:52.9015703Z * [new tag] ciflow/trunk/161591 -> ciflow/trunk/161591 2025-09-07T07:46:52.9016463Z * [new tag] ciflow/trunk/161595 -> ciflow/trunk/161595 2025-09-07T07:46:52.9017371Z * [new tag] ciflow/trunk/161596 -> ciflow/trunk/161596 2025-09-07T07:46:52.9018268Z * [new tag] ciflow/trunk/161633 -> ciflow/trunk/161633 2025-09-07T07:46:52.9019168Z * [new tag] ciflow/trunk/161634 -> ciflow/trunk/161634 2025-09-07T07:46:52.9020046Z * [new tag] ciflow/trunk/161635 -> ciflow/trunk/161635 2025-09-07T07:46:52.9021277Z * [new tag] ciflow/trunk/161667 -> ciflow/trunk/161667 2025-09-07T07:46:52.9022192Z * [new tag] ciflow/trunk/161670 -> ciflow/trunk/161670 2025-09-07T07:46:52.9023420Z * [new tag] ciflow/trunk/161692 -> ciflow/trunk/161692 2025-09-07T07:46:52.9024264Z * [new tag] ciflow/trunk/161693 -> ciflow/trunk/161693 2025-09-07T07:46:52.9025152Z * [new tag] ciflow/trunk/161695 -> ciflow/trunk/161695 2025-09-07T07:46:52.9026233Z * [new tag] ciflow/trunk/161730 -> ciflow/trunk/161730 2025-09-07T07:46:52.9027180Z * [new tag] ciflow/trunk/161744 -> ciflow/trunk/161744 2025-09-07T07:46:52.9028020Z * [new tag] ciflow/trunk/161749 -> ciflow/trunk/161749 2025-09-07T07:46:52.9028909Z * [new tag] ciflow/trunk/161881 -> ciflow/trunk/161881 2025-09-07T07:46:52.9029964Z * [new tag] ciflow/trunk/161924 -> ciflow/trunk/161924 2025-09-07T07:46:52.9031586Z * [new tag] ciflow/trunk/161926 -> ciflow/trunk/161926 2025-09-07T07:46:52.9032400Z * [new tag] ciflow/trunk/161936 -> ciflow/trunk/161936 2025-09-07T07:46:52.9033438Z * [new tag] ciflow/trunk/161952 -> ciflow/trunk/161952 2025-09-07T07:46:52.9034243Z * [new tag] ciflow/trunk/161955 -> ciflow/trunk/161955 2025-09-07T07:46:52.9035270Z * [new tag] ciflow/trunk/161957 -> ciflow/trunk/161957 2025-09-07T07:46:52.9036097Z * [new tag] ciflow/trunk/161959 -> ciflow/trunk/161959 2025-09-07T07:46:52.9037119Z * [new tag] ciflow/trunk/161977 -> ciflow/trunk/161977 2025-09-07T07:46:52.9037971Z * [new tag] ciflow/trunk/161988 -> ciflow/trunk/161988 2025-09-07T07:46:52.9039055Z * [new tag] ciflow/trunk/161994 -> ciflow/trunk/161994 2025-09-07T07:46:52.9040094Z * [new tag] ciflow/trunk/162007 -> ciflow/trunk/162007 2025-09-07T07:46:52.9041393Z * [new tag] ciflow/trunk/162013 -> ciflow/trunk/162013 2025-09-07T07:46:52.9042274Z * [new tag] ciflow/trunk/162017 -> ciflow/trunk/162017 2025-09-07T07:46:52.9043308Z * [new tag] ciflow/trunk/162021 -> ciflow/trunk/162021 2025-09-07T07:46:52.9044132Z * [new tag] ciflow/trunk/162022 -> ciflow/trunk/162022 2025-09-07T07:46:52.9045349Z * [new tag] ciflow/trunk/162040 -> ciflow/trunk/162040 2025-09-07T07:46:52.9046077Z * [new tag] ciflow/trunk/162041 -> ciflow/trunk/162041 2025-09-07T07:46:52.9047286Z * [new tag] ciflow/trunk/162062 -> ciflow/trunk/162062 2025-09-07T07:46:52.9048117Z * [new tag] ciflow/trunk/162066 -> ciflow/trunk/162066 2025-09-07T07:46:52.9049153Z * [new tag] ciflow/trunk/162089 -> ciflow/trunk/162089 2025-09-07T07:46:52.9050030Z * [new tag] ciflow/trunk/162099 -> ciflow/trunk/162099 2025-09-07T07:46:52.9051384Z * [new tag] ciflow/trunk/162104 -> ciflow/trunk/162104 2025-09-07T07:46:52.9052256Z * [new tag] ciflow/trunk/162106 -> ciflow/trunk/162106 2025-09-07T07:46:52.9053289Z * [new tag] ciflow/trunk/162112 -> ciflow/trunk/162112 2025-09-07T07:46:52.9054374Z * [new tag] ciflow/trunk/162119 -> ciflow/trunk/162119 2025-09-07T07:46:52.9055404Z * [new tag] ciflow/trunk/162142 -> ciflow/trunk/162142 2025-09-07T07:46:52.9056259Z * [new tag] ciflow/trunk/162169 -> ciflow/trunk/162169 2025-09-07T07:46:52.9057291Z * [new tag] ciflow/trunk/162183 -> ciflow/trunk/162183 2025-09-07T07:46:52.9058190Z * [new tag] ciflow/trunk/162190 -> ciflow/trunk/162190 2025-09-07T07:46:52.9059261Z * [new tag] ciflow/trunk/162194 -> ciflow/trunk/162194 2025-09-07T07:46:52.9060179Z * [new tag] ciflow/trunk/162200 -> ciflow/trunk/162200 2025-09-07T07:46:52.9061504Z * [new tag] ciflow/trunk/162206 -> ciflow/trunk/162206 2025-09-07T07:46:52.9062374Z * [new tag] ciflow/trunk/162208 -> ciflow/trunk/162208 2025-09-07T07:46:52.9063539Z * [new tag] ciflow/trunk/162222 -> ciflow/trunk/162222 2025-09-07T07:46:52.9064450Z * [new tag] ciflow/trunk/162238 -> ciflow/trunk/162238 2025-09-07T07:46:52.9065520Z * [new tag] ciflow/trunk/162244 -> ciflow/trunk/162244 2025-09-07T07:46:52.9066764Z * [new tag] ciflow/trunk/162267 -> ciflow/trunk/162267 2025-09-07T07:46:52.9067876Z * [new tag] ciflow/trunk/162269 -> ciflow/trunk/162269 2025-09-07T07:46:52.9068888Z * [new tag] ciflow/trunk/162278 -> ciflow/trunk/162278 2025-09-07T07:46:52.9069951Z * [new tag] ciflow/trunk/162286 -> ciflow/trunk/162286 2025-09-07T07:46:52.9071189Z * [new tag] ciflow/trunk/162288 -> ciflow/trunk/162288 2025-09-07T07:46:52.9072057Z * [new tag] ciflow/trunk/162293 -> ciflow/trunk/162293 2025-09-07T07:46:52.9073134Z * [new tag] ciflow/trunk/162310 -> ciflow/trunk/162310 2025-09-07T07:46:52.9074044Z * [new tag] ciflow/trunk/162311 -> ciflow/trunk/162311 2025-09-07T07:46:52.9075125Z * [new tag] ciflow/trunk/162315 -> ciflow/trunk/162315 2025-09-07T07:46:52.9076028Z * [new tag] ciflow/trunk/162325 -> ciflow/trunk/162325 2025-09-07T07:46:52.9077340Z * [new tag] ciflow/trunk/162328 -> ciflow/trunk/162328 2025-09-07T07:46:52.9078257Z * [new tag] ciflow/trunk/162329 -> ciflow/trunk/162329 2025-09-07T07:46:52.9079723Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-09-07T07:46:52.9081242Z * [new tag] ciflow/vllm/162292 -> ciflow/vllm/162292 2025-09-07T07:46:52.9082436Z * [new tag] ciflow/win-arm64/156049 -> ciflow/win-arm64/156049 2025-09-07T07:46:52.9083176Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-09-07T07:46:52.9084569Z * [new tag] ciflow/xpu/157699 -> ciflow/xpu/157699 2025-09-07T07:46:52.9085160Z * [new tag] ciflow/xpu/157994 -> ciflow/xpu/157994 2025-09-07T07:46:52.9086234Z * [new tag] ciflow/xpu/159459 -> ciflow/xpu/159459 2025-09-07T07:46:52.9087008Z * [new tag] ciflow/xpu/159718 -> ciflow/xpu/159718 2025-09-07T07:46:52.9087847Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-09-07T07:46:52.9088892Z * [new tag] ciflow/xpu/160867 -> ciflow/xpu/160867 2025-09-07T07:46:52.9089728Z * [new tag] ciflow/xpu/160938 -> ciflow/xpu/160938 2025-09-07T07:46:52.9090793Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-09-07T07:46:52.9091679Z * [new tag] ciflow/xpu/160953 -> ciflow/xpu/160953 2025-09-07T07:46:52.9092716Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-09-07T07:46:52.9093780Z * [new tag] ciflow/xpu/161058 -> ciflow/xpu/161058 2025-09-07T07:46:52.9094542Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-09-07T07:46:52.9095396Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-09-07T07:46:52.9096246Z * [new tag] ciflow/xpu/161485 -> ciflow/xpu/161485 2025-09-07T07:46:52.9097115Z * [new tag] ciflow/xpu/161988 -> ciflow/xpu/161988 2025-09-07T07:46:52.9097962Z * [new tag] ciflow/xpu/162062 -> ciflow/xpu/162062 2025-09-07T07:46:52.9099032Z * [new tag] cslpull75 -> cslpull75 2025-09-07T07:46:52.9099861Z * [new tag] cslpull76 -> cslpull76 2025-09-07T07:46:52.9101152Z * [new tag] cslpull77 -> cslpull77 2025-09-07T07:46:52.9102162Z * [new tag] cslpull78 -> cslpull78 2025-09-07T07:46:52.9103067Z * [new tag] cslpull79 -> cslpull79 2025-09-07T07:46:52.9104185Z * [new tag] cslpull80 -> cslpull80 2025-09-07T07:46:52.9105216Z * [new tag] cslpull81 -> cslpull81 2025-09-07T07:46:52.9106274Z * [new tag] cslpull82 -> cslpull82 2025-09-07T07:46:52.9107153Z * [new tag] cslpull83 -> cslpull83 2025-09-07T07:46:52.9108211Z * [new tag] cslpull84 -> cslpull84 2025-09-07T07:46:52.9109041Z * [new tag] cslpull85 -> cslpull85 2025-09-07T07:46:52.9110123Z * [new tag] cslpull86 -> cslpull86 2025-09-07T07:46:52.9111369Z * [new tag] cslpull87 -> cslpull87 2025-09-07T07:46:52.9112464Z * [new tag] cslpull88 -> cslpull88 2025-09-07T07:46:52.9113218Z * [new tag] cslpull89 -> cslpull89 2025-09-07T07:46:52.9113993Z * [new tag] cslpull90 -> cslpull90 2025-09-07T07:46:52.9115345Z * [new tag] cslpull91 -> cslpull91 2025-09-07T07:46:52.9116206Z * [new tag] cslpull92 -> cslpull92 2025-09-07T07:46:52.9117288Z * [new tag] flight_5 -> flight_5 2025-09-07T07:46:52.9118303Z * [new tag] flight_5.1 -> flight_5.1 2025-09-07T07:46:52.9119323Z * [new tag] flight_5.2 -> flight_5.2 2025-09-07T07:46:52.9120175Z * [new tag] flight_5.3 -> flight_5.3 2025-09-07T07:46:52.9121671Z * [new tag] forpull1 -> forpull1 2025-09-07T07:46:52.9122954Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-09-07T07:46:52.9124151Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-09-07T07:46:52.9124892Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-09-07T07:46:52.9126023Z * [new tag] nightly-binary -> nightly-binary 2025-09-07T07:46:52.9126787Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-09-07T07:46:52.9127949Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-09-07T07:46:52.9129383Z * [new tag] trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608 2025-09-07T07:46:52.9130603Z * [new tag] trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 2025-09-07T07:46:52.9131727Z * [new tag] trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544 2025-09-07T07:46:52.9132799Z * [new tag] trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b 2025-09-07T07:46:52.9133797Z * [new tag] trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388 2025-09-07T07:46:52.9134851Z * [new tag] trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 2025-09-07T07:46:52.9135917Z * [new tag] trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4 2025-09-07T07:46:52.9136965Z * [new tag] trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 2025-09-07T07:46:52.9138102Z * [new tag] trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23 2025-09-07T07:46:52.9139121Z * [new tag] trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 2025-09-07T07:46:52.9140095Z * [new tag] trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 2025-09-07T07:46:52.9141410Z * [new tag] trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 2025-09-07T07:46:52.9142383Z * [new tag] trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 2025-09-07T07:46:52.9144094Z * [new tag] trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 2025-09-07T07:46:52.9145006Z * [new tag] trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 2025-09-07T07:46:52.9146058Z * [new tag] trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c 2025-09-07T07:46:52.9147162Z * [new tag] trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 2025-09-07T07:46:52.9148144Z * [new tag] trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e 2025-09-07T07:46:52.9149189Z * [new tag] trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 2025-09-07T07:46:52.9150361Z * [new tag] trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f 2025-09-07T07:46:52.9151530Z * [new tag] trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f 2025-09-07T07:46:52.9152512Z * [new tag] trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0 2025-09-07T07:46:52.9153559Z * [new tag] trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c 2025-09-07T07:46:52.9154690Z * [new tag] trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 2025-09-07T07:46:52.9155542Z * [new tag] trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 2025-09-07T07:46:52.9156606Z * [new tag] trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb 2025-09-07T07:46:52.9157624Z * [new tag] trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 2025-09-07T07:46:52.9158691Z * [new tag] trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 2025-09-07T07:46:52.9160400Z * [new tag] trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c 2025-09-07T07:46:52.9161519Z * [new tag] trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 2025-09-07T07:46:52.9162548Z * [new tag] trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 2025-09-07T07:46:52.9163406Z * [new tag] trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 2025-09-07T07:46:52.9164479Z * [new tag] trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a 2025-09-07T07:46:52.9165532Z * [new tag] trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 2025-09-07T07:46:52.9166574Z * [new tag] trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 2025-09-07T07:46:52.9167621Z * [new tag] trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a 2025-09-07T07:46:52.9168697Z * [new tag] trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b 2025-09-07T07:46:52.9169829Z * [new tag] trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc 2025-09-07T07:46:52.9171063Z * [new tag] trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05 2025-09-07T07:46:52.9172163Z * [new tag] trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 2025-09-07T07:46:52.9173187Z * [new tag] trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd 2025-09-07T07:46:52.9174253Z * [new tag] trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 2025-09-07T07:46:52.9175316Z * [new tag] trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f 2025-09-07T07:46:52.9176330Z * [new tag] trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23 2025-09-07T07:46:52.9177326Z * [new tag] trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 2025-09-07T07:46:52.9178667Z * [new tag] trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f 2025-09-07T07:46:52.9179570Z * [new tag] trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 2025-09-07T07:46:52.9180915Z * [new tag] trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9 2025-09-07T07:46:52.9182111Z * [new tag] trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 2025-09-07T07:46:52.9183365Z * [new tag] trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef 2025-09-07T07:46:52.9184648Z * [new tag] trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c 2025-09-07T07:46:52.9185531Z * [new tag] trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6 2025-09-07T07:46:52.9186586Z * [new tag] trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 2025-09-07T07:46:52.9189064Z * [new tag] trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a 2025-09-07T07:46:52.9189694Z * [new tag] trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 2025-09-07T07:46:52.9190603Z * [new tag] trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 2025-09-07T07:46:52.9191247Z * [new tag] trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 2025-09-07T07:46:52.9192130Z * [new tag] trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 2025-09-07T07:46:52.9193147Z * [new tag] trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176 2025-09-07T07:46:52.9194197Z * [new tag] trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 2025-09-07T07:46:52.9195118Z * [new tag] trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b 2025-09-07T07:46:52.9196044Z * [new tag] trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 2025-09-07T07:46:52.9197107Z * [new tag] trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287 2025-09-07T07:46:52.9198160Z * [new tag] trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f 2025-09-07T07:46:52.9199250Z * [new tag] trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 2025-09-07T07:46:52.9200566Z * [new tag] trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 2025-09-07T07:46:52.9202076Z * [new tag] trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f 2025-09-07T07:46:52.9203022Z * [new tag] trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf 2025-09-07T07:46:52.9204065Z * [new tag] trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 2025-09-07T07:46:52.9205150Z * [new tag] trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d 2025-09-07T07:46:52.9206299Z * [new tag] trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa 2025-09-07T07:46:52.9207359Z * [new tag] trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 2025-09-07T07:46:52.9208454Z * [new tag] trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336 2025-09-07T07:46:52.9209599Z * [new tag] trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63 2025-09-07T07:46:52.9210925Z * [new tag] trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3 2025-09-07T07:46:52.9212004Z * [new tag] trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c 2025-09-07T07:46:52.9213295Z * [new tag] trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 2025-09-07T07:46:52.9214207Z * [new tag] trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf 2025-09-07T07:46:52.9215193Z * [new tag] trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e 2025-09-07T07:46:52.9216392Z * [new tag] trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 2025-09-07T07:46:52.9217501Z * [new tag] trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215 2025-09-07T07:46:52.9218623Z * [new tag] trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d 2025-09-07T07:46:52.9219766Z * [new tag] trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 2025-09-07T07:46:52.9221734Z * [new tag] trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c 2025-09-07T07:46:52.9222827Z * [new tag] trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 2025-09-07T07:46:52.9223927Z * [new tag] trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b 2025-09-07T07:46:52.9225222Z * [new tag] trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 2025-09-07T07:46:52.9226302Z * [new tag] trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503 2025-09-07T07:46:52.9227390Z * [new tag] trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 2025-09-07T07:46:52.9228539Z * [new tag] trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 2025-09-07T07:46:52.9229704Z * [new tag] trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 2025-09-07T07:46:52.9231021Z * [new tag] trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 2025-09-07T07:46:52.9232141Z * [new tag] trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a 2025-09-07T07:46:52.9233188Z * [new tag] trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 2025-09-07T07:46:52.9234297Z * [new tag] trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 2025-09-07T07:46:52.9235595Z * [new tag] trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c 2025-09-07T07:46:52.9236748Z * [new tag] trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 2025-09-07T07:46:52.9237855Z * [new tag] trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806 2025-09-07T07:46:52.9238960Z * [new tag] trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 2025-09-07T07:46:52.9240068Z * [new tag] trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 2025-09-07T07:46:52.9241463Z * [new tag] trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 2025-09-07T07:46:52.9242544Z * [new tag] trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251 2025-09-07T07:46:52.9244421Z * [new tag] trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 2025-09-07T07:46:52.9245199Z * [new tag] trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c 2025-09-07T07:46:52.9246296Z * [new tag] trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a 2025-09-07T07:46:52.9247492Z * [new tag] trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db 2025-09-07T07:46:52.9248670Z * [new tag] trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536 2025-09-07T07:46:52.9249773Z * [new tag] trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f 2025-09-07T07:46:52.9251395Z * [new tag] trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 2025-09-07T07:46:52.9252442Z * [new tag] trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b 2025-09-07T07:46:52.9253815Z * [new tag] trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda 2025-09-07T07:46:52.9254824Z * [new tag] trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b 2025-09-07T07:46:52.9256008Z * [new tag] trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 2025-09-07T07:46:52.9257168Z * [new tag] trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8 2025-09-07T07:46:52.9258321Z * [new tag] trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b 2025-09-07T07:46:52.9259483Z * [new tag] trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab 2025-09-07T07:46:52.9261006Z * [new tag] trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 2025-09-07T07:46:52.9261968Z * [new tag] trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe 2025-09-07T07:46:52.9263030Z * [new tag] trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 2025-09-07T07:46:52.9264185Z * [new tag] trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 2025-09-07T07:46:52.9265359Z * [new tag] trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 2025-09-07T07:46:52.9266484Z * [new tag] trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c 2025-09-07T07:46:52.9267594Z * [new tag] trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d 2025-09-07T07:46:52.9268573Z * [new tag] trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429 2025-09-07T07:46:52.9269931Z * [new tag] trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 2025-09-07T07:46:52.9271219Z * [new tag] trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c 2025-09-07T07:46:52.9272309Z * [new tag] trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895 2025-09-07T07:46:52.9273481Z * [new tag] trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 2025-09-07T07:46:52.9274624Z * [new tag] trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435 2025-09-07T07:46:52.9276149Z * [new tag] trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965 2025-09-07T07:46:52.9277080Z * [new tag] trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 2025-09-07T07:46:52.9278263Z * [new tag] trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 2025-09-07T07:46:52.9279429Z * [new tag] trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 2025-09-07T07:46:52.9280949Z * [new tag] trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 2025-09-07T07:46:52.9282153Z * [new tag] trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 2025-09-07T07:46:52.9283487Z * [new tag] trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f 2025-09-07T07:46:52.9284569Z * [new tag] trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 2025-09-07T07:46:52.9285890Z * [new tag] trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610 2025-09-07T07:46:52.9286964Z * [new tag] trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 2025-09-07T07:46:52.9288171Z * [new tag] trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af 2025-09-07T07:46:52.9289725Z * [new tag] trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 2025-09-07T07:46:52.9291184Z * [new tag] trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d 2025-09-07T07:46:52.9292385Z * [new tag] trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 2025-09-07T07:46:52.9293528Z * [new tag] trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 2025-09-07T07:46:52.9294951Z * [new tag] trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab 2025-09-07T07:46:52.9296020Z * [new tag] trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d 2025-09-07T07:46:52.9297396Z * [new tag] trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:52.9298508Z * [new tag] trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c 2025-09-07T07:46:52.9299694Z * [new tag] trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e 2025-09-07T07:46:52.9301570Z * [new tag] trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 2025-09-07T07:46:52.9302580Z * [new tag] trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1 2025-09-07T07:46:52.9304005Z * [new tag] trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 2025-09-07T07:46:52.9304986Z * [new tag] trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a 2025-09-07T07:46:52.9306180Z * [new tag] trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500 2025-09-07T07:46:52.9307557Z * [new tag] trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 2025-09-07T07:46:52.9308683Z * [new tag] trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6 2025-09-07T07:46:52.9309658Z * [new tag] trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 2025-09-07T07:46:52.9311026Z * [new tag] trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd 2025-09-07T07:46:52.9312109Z * [new tag] trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57 2025-09-07T07:46:52.9313258Z * [new tag] trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4 2025-09-07T07:46:52.9314401Z * [new tag] trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e 2025-09-07T07:46:52.9315495Z * [new tag] trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839 2025-09-07T07:46:52.9316623Z * [new tag] trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60 2025-09-07T07:46:52.9317784Z * [new tag] trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 2025-09-07T07:46:52.9319208Z * [new tag] trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 2025-09-07T07:46:52.9320446Z * [new tag] trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 2025-09-07T07:46:52.9321802Z * [new tag] trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 2025-09-07T07:46:52.9322733Z * [new tag] trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d 2025-09-07T07:46:52.9323869Z * [new tag] trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 2025-09-07T07:46:52.9324965Z * [new tag] trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92 2025-09-07T07:46:52.9326126Z * [new tag] trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098 2025-09-07T07:46:52.9327284Z * [new tag] trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356 2025-09-07T07:46:52.9328257Z * [new tag] trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae 2025-09-07T07:46:52.9329415Z * [new tag] trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 2025-09-07T07:46:52.9330788Z * [new tag] trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e 2025-09-07T07:46:52.9332131Z * [new tag] trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 2025-09-07T07:46:52.9333188Z * [new tag] trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 2025-09-07T07:46:52.9334524Z * [new tag] trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c 2025-09-07T07:46:52.9335556Z * [new tag] trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 2025-09-07T07:46:52.9336727Z * [new tag] trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d 2025-09-07T07:46:52.9337760Z * [new tag] trunk/ada43ed39c80b746b4822c92640a1882619e2795 -> trunk/ada43ed39c80b746b4822c92640a1882619e2795 2025-09-07T07:46:52.9339097Z * [new tag] trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa 2025-09-07T07:46:52.9340547Z * [new tag] trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c 2025-09-07T07:46:52.9341662Z * [new tag] trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d 2025-09-07T07:46:52.9342872Z * [new tag] trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 2025-09-07T07:46:52.9344246Z * [new tag] trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f 2025-09-07T07:46:52.9345242Z * [new tag] trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 2025-09-07T07:46:52.9346327Z * [new tag] trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 2025-09-07T07:46:52.9347484Z * [new tag] trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de 2025-09-07T07:46:52.9348590Z * [new tag] trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b 2025-09-07T07:46:52.9363460Z * [new tag] trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 2025-09-07T07:46:52.9364452Z * [new tag] trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 2025-09-07T07:46:52.9365094Z * [new tag] trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b 2025-09-07T07:46:52.9365699Z * [new tag] trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde 2025-09-07T07:46:52.9366314Z * [new tag] trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c 2025-09-07T07:46:52.9366938Z * [new tag] trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 2025-09-07T07:46:52.9367550Z * [new tag] trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052 2025-09-07T07:46:52.9368144Z * [new tag] trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e 2025-09-07T07:46:52.9368744Z * [new tag] trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 2025-09-07T07:46:52.9369352Z * [new tag] trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 2025-09-07T07:46:52.9369952Z * [new tag] trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85 2025-09-07T07:46:52.9370756Z * [new tag] trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d 2025-09-07T07:46:52.9371386Z * [new tag] trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 2025-09-07T07:46:52.9371997Z * [new tag] trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865 2025-09-07T07:46:52.9372607Z * [new tag] trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 2025-09-07T07:46:52.9373232Z * [new tag] trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 2025-09-07T07:46:52.9373857Z * [new tag] trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 2025-09-07T07:46:52.9374476Z * [new tag] trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf 2025-09-07T07:46:52.9375240Z * [new tag] trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 2025-09-07T07:46:52.9375854Z * [new tag] trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad 2025-09-07T07:46:52.9376449Z * [new tag] trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 2025-09-07T07:46:52.9377072Z * [new tag] trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 2025-09-07T07:46:52.9377656Z * [new tag] trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76 2025-09-07T07:46:52.9378245Z * [new tag] trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5 2025-09-07T07:46:52.9378858Z * [new tag] trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 2025-09-07T07:46:52.9379928Z * [new tag] trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd 2025-09-07T07:46:52.9381288Z * [new tag] trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741 2025-09-07T07:46:52.9382442Z * [new tag] trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b 2025-09-07T07:46:52.9383621Z * [new tag] trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 2025-09-07T07:46:52.9384743Z * [new tag] trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 2025-09-07T07:46:52.9385895Z * [new tag] trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b 2025-09-07T07:46:52.9386992Z * [new tag] trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8 2025-09-07T07:46:52.9388176Z * [new tag] trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 2025-09-07T07:46:52.9389552Z * [new tag] trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7 2025-09-07T07:46:52.9390676Z * [new tag] trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87 2025-09-07T07:46:52.9392087Z * [new tag] trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e 2025-09-07T07:46:52.9393090Z * [new tag] trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e 2025-09-07T07:46:52.9394445Z * [new tag] trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d 2025-09-07T07:46:52.9395811Z * [new tag] trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 2025-09-07T07:46:52.9396805Z * [new tag] trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e 2025-09-07T07:46:52.9397932Z * [new tag] trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 2025-09-07T07:46:52.9399043Z * [new tag] trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 2025-09-07T07:46:52.9400154Z * [new tag] trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 2025-09-07T07:46:52.9401443Z * [new tag] trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462 2025-09-07T07:46:52.9402628Z * [new tag] trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 2025-09-07T07:46:52.9404495Z * [new tag] trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285 2025-09-07T07:46:52.9405488Z * [new tag] trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643 2025-09-07T07:46:52.9406638Z * [new tag] trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 2025-09-07T07:46:52.9407809Z * [new tag] trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661 2025-09-07T07:46:52.9408942Z * [new tag] trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab 2025-09-07T07:46:52.9410118Z * [new tag] trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 2025-09-07T07:46:52.9411357Z * [new tag] trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 2025-09-07T07:46:52.9412747Z * [new tag] trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061 2025-09-07T07:46:52.9413607Z * [new tag] trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a 2025-09-07T07:46:52.9414699Z * [new tag] trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 2025-09-07T07:46:52.9416069Z * [new tag] trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d 2025-09-07T07:46:52.9417068Z * [new tag] trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717 2025-09-07T07:46:52.9418256Z * [new tag] trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 2025-09-07T07:46:52.9419595Z * [new tag] trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 2025-09-07T07:46:52.9420875Z * [new tag] trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439 2025-09-07T07:46:52.9422342Z * [new tag] trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 2025-09-07T07:46:52.9423390Z * [new tag] trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 2025-09-07T07:46:52.9424366Z * [new tag] trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 2025-09-07T07:46:52.9425488Z * [new tag] trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b 2025-09-07T07:46:52.9426616Z * [new tag] trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090 2025-09-07T07:46:52.9427608Z * [new tag] trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087 2025-09-07T07:46:52.9428967Z * [new tag] trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 2025-09-07T07:46:52.9430039Z * [new tag] trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de 2025-09-07T07:46:52.9431645Z * [new tag] trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 2025-09-07T07:46:52.9432676Z * [new tag] trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 2025-09-07T07:46:52.9434009Z * [new tag] trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b 2025-09-07T07:46:52.9435335Z * [new tag] trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37 2025-09-07T07:46:52.9436400Z * [new tag] trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 2025-09-07T07:46:52.9437748Z * [new tag] trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd 2025-09-07T07:46:52.9438784Z * [new tag] trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb 2025-09-07T07:46:52.9439788Z * [new tag] trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c 2025-09-07T07:46:52.9441280Z * [new tag] trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8 2025-09-07T07:46:52.9442344Z * [new tag] trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c 2025-09-07T07:46:52.9443651Z * [new tag] trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c 2025-09-07T07:46:52.9444661Z * [new tag] trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 2025-09-07T07:46:52.9445851Z * [new tag] trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 2025-09-07T07:46:52.9447050Z * [new tag] trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa 2025-09-07T07:46:52.9448408Z * [new tag] trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab 2025-09-07T07:46:52.9449775Z * [new tag] trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd 2025-09-07T07:46:52.9450825Z * [new tag] v0.1.1 -> v0.1.1 2025-09-07T07:46:52.9451960Z * [new tag] v0.1.10 -> v0.1.10 2025-09-07T07:46:52.9452818Z * [new tag] v0.1.11 -> v0.1.11 2025-09-07T07:46:52.9453966Z * [new tag] v0.1.12 -> v0.1.12 2025-09-07T07:46:52.9454778Z * [new tag] v0.1.2 -> v0.1.2 2025-09-07T07:46:52.9455811Z * [new tag] v0.1.3 -> v0.1.3 2025-09-07T07:46:52.9456843Z * [new tag] v0.1.4 -> v0.1.4 2025-09-07T07:46:52.9457891Z * [new tag] v0.1.5 -> v0.1.5 2025-09-07T07:46:52.9458917Z * [new tag] v0.1.6 -> v0.1.6 2025-09-07T07:46:52.9459749Z * [new tag] v0.1.7 -> v0.1.7 2025-09-07T07:46:52.9461024Z * [new tag] v0.1.8 -> v0.1.8 2025-09-07T07:46:52.9462007Z * [new tag] v0.1.9 -> v0.1.9 2025-09-07T07:46:52.9463120Z * [new tag] v0.2.0 -> v0.2.0 2025-09-07T07:46:52.9464249Z * [new tag] v0.3.0 -> v0.3.0 2025-09-07T07:46:52.9465429Z * [new tag] v0.3.1 -> v0.3.1 2025-09-07T07:46:52.9466532Z * [new tag] v0.4.0 -> v0.4.0 2025-09-07T07:46:52.9467561Z * [new tag] v0.4.1 -> v0.4.1 2025-09-07T07:46:52.9468584Z * [new tag] v1.0.0 -> v1.0.0 2025-09-07T07:46:52.9469638Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-09-07T07:46:52.9470950Z * [new tag] v1.0.1 -> v1.0.1 2025-09-07T07:46:52.9471982Z * [new tag] v1.0rc0 -> v1.0rc0 2025-09-07T07:46:52.9472779Z * [new tag] v1.0rc1 -> v1.0rc1 2025-09-07T07:46:52.9474130Z * [new tag] v1.1.0 -> v1.1.0 2025-09-07T07:46:52.9475033Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-09-07T07:46:52.9476253Z * [new tag] v1.10.0 -> v1.10.0 2025-09-07T07:46:52.9477446Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-09-07T07:46:52.9478565Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-09-07T07:46:52.9479462Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-09-07T07:46:52.9480801Z * [new tag] v1.10.1 -> v1.10.1 2025-09-07T07:46:52.9481773Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-09-07T07:46:52.9482634Z * [new tag] v1.10.2 -> v1.10.2 2025-09-07T07:46:52.9483492Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-09-07T07:46:52.9484615Z * [new tag] v1.11.0 -> v1.11.0 2025-09-07T07:46:52.9485814Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-09-07T07:46:52.9486987Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-09-07T07:46:52.9488130Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-09-07T07:46:52.9489205Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-09-07T07:46:52.9490456Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-09-07T07:46:52.9491441Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-09-07T07:46:52.9492343Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-09-07T07:46:52.9493561Z * [new tag] v1.12.0 -> v1.12.0 2025-09-07T07:46:52.9494657Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-09-07T07:46:52.9495776Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-09-07T07:46:52.9496841Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-09-07T07:46:52.9498019Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-09-07T07:46:52.9499152Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-09-07T07:46:52.9500392Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-09-07T07:46:52.9501538Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-09-07T07:46:52.9502384Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-09-07T07:46:52.9503396Z * [new tag] v1.12.1 -> v1.12.1 2025-09-07T07:46:52.9504666Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-09-07T07:46:52.9505889Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-09-07T07:46:52.9507122Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-09-07T07:46:52.9508341Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-09-07T07:46:52.9509257Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-09-07T07:46:52.9510541Z * [new tag] v1.13.0 -> v1.13.0 2025-09-07T07:46:52.9511696Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-09-07T07:46:52.9512747Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-09-07T07:46:52.9513848Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-09-07T07:46:52.9515035Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-09-07T07:46:52.9515962Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-09-07T07:46:52.9516897Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-09-07T07:46:52.9518123Z * [new tag] v1.13.1 -> v1.13.1 2025-09-07T07:46:52.9519254Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-09-07T07:46:52.9520321Z * [new tag] v1.2.0 -> v1.2.0 2025-09-07T07:46:52.9521575Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-09-07T07:46:52.9522690Z * [new tag] v1.3.0 -> v1.3.0 2025-09-07T07:46:52.9523773Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-09-07T07:46:52.9524680Z * [new tag] v1.3.1 -> v1.3.1 2025-09-07T07:46:52.9525811Z * [new tag] v1.4.0 -> v1.4.0 2025-09-07T07:46:52.9526914Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-09-07T07:46:52.9527835Z * [new tag] v1.4.1 -> v1.4.1 2025-09-07T07:46:52.9529001Z * [new tag] v1.5.0 -> v1.5.0 2025-09-07T07:46:52.9530187Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-09-07T07:46:52.9531597Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-09-07T07:46:52.9532782Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-09-07T07:46:52.9533796Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-09-07T07:46:52.9534714Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-09-07T07:46:52.9535993Z * [new tag] v1.5.1 -> v1.5.1 2025-09-07T07:46:52.9536977Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-09-07T07:46:52.9537892Z * [new tag] v1.6.0 -> v1.6.0 2025-09-07T07:46:52.9539058Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-09-07T07:46:52.9540196Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-09-07T07:46:52.9541631Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-09-07T07:46:52.9542789Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-09-07T07:46:52.9543999Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-09-07T07:46:52.9545139Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-09-07T07:46:52.9546073Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-09-07T07:46:52.9547273Z * [new tag] v1.7.0 -> v1.7.0 2025-09-07T07:46:52.9548413Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-09-07T07:46:52.9549635Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-09-07T07:46:52.9551216Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-09-07T07:46:52.9552138Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-09-07T07:46:52.9553274Z * [new tag] v1.7.1 -> v1.7.1 2025-09-07T07:46:52.9554560Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-09-07T07:46:52.9555832Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-09-07T07:46:52.9556742Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-09-07T07:46:52.9557906Z * [new tag] v1.8.0 -> v1.8.0 2025-09-07T07:46:52.9558882Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-09-07T07:46:52.9560072Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-09-07T07:46:52.9561489Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-09-07T07:46:52.9562554Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-09-07T07:46:52.9563481Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-09-07T07:46:52.9564440Z * [new tag] v1.8.1 -> v1.8.1 2025-09-07T07:46:52.9565822Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-09-07T07:46:52.9566719Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-09-07T07:46:52.9567735Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-09-07T07:46:52.9569293Z * [new tag] v1.8.2 -> v1.8.2 2025-09-07T07:46:52.9570367Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-09-07T07:46:52.9571738Z * [new tag] v1.9.0 -> v1.9.0 2025-09-07T07:46:52.9572986Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-09-07T07:46:52.9574196Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-09-07T07:46:52.9575406Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-09-07T07:46:52.9576370Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-09-07T07:46:52.9577540Z * [new tag] v1.9.1 -> v1.9.1 2025-09-07T07:46:52.9578911Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-09-07T07:46:52.9579908Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-09-07T07:46:52.9581418Z * [new tag] v2.0.0 -> v2.0.0 2025-09-07T07:46:52.9582525Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-09-07T07:46:52.9583965Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-09-07T07:46:52.9585103Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-09-07T07:46:52.9586245Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-09-07T07:46:52.9587510Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-09-07T07:46:52.9588466Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-09-07T07:46:52.9589781Z * [new tag] v2.0.1 -> v2.0.1 2025-09-07T07:46:52.9591199Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-09-07T07:46:52.9592158Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-09-07T07:46:52.9593276Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-09-07T07:46:52.9594229Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-09-07T07:46:52.9595839Z * [new tag] v2.1.0 -> v2.1.0 2025-09-07T07:46:52.9596970Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-09-07T07:46:52.9598202Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-09-07T07:46:52.9599447Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-09-07T07:46:52.9601006Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-09-07T07:46:52.9602313Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-09-07T07:46:52.9603245Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-09-07T07:46:52.9604448Z * [new tag] v2.1.1 -> v2.1.1 2025-09-07T07:46:52.9605688Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-09-07T07:46:52.9606827Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-09-07T07:46:52.9608158Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-09-07T07:46:52.9609381Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-09-07T07:46:52.9610664Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-09-07T07:46:52.9611717Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-09-07T07:46:52.9612911Z * [new tag] v2.1.2 -> v2.1.2 2025-09-07T07:46:52.9614210Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-09-07T07:46:52.9615471Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-09-07T07:46:52.9616616Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-09-07T07:46:52.9617704Z * [new tag] v2.2.0 -> v2.2.0 2025-09-07T07:46:52.9619020Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-09-07T07:46:52.9620173Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-09-07T07:46:52.9621975Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-09-07T07:46:52.9623212Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-09-07T07:46:52.9624397Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-09-07T07:46:52.9625637Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-09-07T07:46:52.9626631Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-09-07T07:46:52.9627640Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-09-07T07:46:52.9628932Z * [new tag] v2.2.1 -> v2.2.1 2025-09-07T07:46:52.9630198Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-09-07T07:46:52.9631512Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-09-07T07:46:52.9632527Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-09-07T07:46:52.9633573Z * [new tag] v2.2.2 -> v2.2.2 2025-09-07T07:46:52.9634876Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-09-07T07:46:52.9635886Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-09-07T07:46:52.9636870Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-09-07T07:46:52.9638086Z * [new tag] v2.3.0 -> v2.3.0 2025-09-07T07:46:52.9639336Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-09-07T07:46:52.9640764Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-09-07T07:46:52.9642122Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-09-07T07:46:52.9643170Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-09-07T07:46:52.9644402Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-09-07T07:46:52.9645658Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-09-07T07:46:52.9646875Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-09-07T07:46:52.9648071Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-09-07T07:46:52.9649090Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-09-07T07:46:52.9650524Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-09-07T07:46:52.9651833Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-09-07T07:46:52.9652822Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-09-07T07:46:52.9653848Z * [new tag] v2.3.1 -> v2.3.1 2025-09-07T07:46:52.9655069Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-09-07T07:46:52.9656295Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-09-07T07:46:52.9658199Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-09-07T07:46:52.9659383Z * [new tag] v2.4.0 -> v2.4.0 2025-09-07T07:46:52.9660799Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-09-07T07:46:52.9662080Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-09-07T07:46:52.9663364Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-09-07T07:46:52.9664579Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-09-07T07:46:52.9665820Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-09-07T07:46:52.9667311Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-09-07T07:46:52.9668341Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-09-07T07:46:52.9669493Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-09-07T07:46:52.9670982Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-09-07T07:46:52.9672130Z * [new tag] v2.4.1 -> v2.4.1 2025-09-07T07:46:52.9673399Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-09-07T07:46:52.9674631Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-09-07T07:46:52.9675864Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-09-07T07:46:52.9677050Z * [new tag] v2.5.0 -> v2.5.0 2025-09-07T07:46:52.9678221Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-09-07T07:46:52.9679233Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-09-07T07:46:52.9680503Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-09-07T07:46:52.9681887Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-09-07T07:46:52.9683065Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-09-07T07:46:52.9684297Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-09-07T07:46:52.9685625Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-09-07T07:46:52.9686808Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-09-07T07:46:52.9688044Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-09-07T07:46:52.9689277Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-09-07T07:46:52.9690495Z * [new tag] v2.5.1 -> v2.5.1 2025-09-07T07:46:52.9691607Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-09-07T07:46:52.9692594Z * [new tag] v2.6.0 -> v2.6.0 2025-09-07T07:46:52.9693886Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-09-07T07:46:52.9695210Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-09-07T07:46:52.9696452Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-09-07T07:46:52.9697633Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-09-07T07:46:52.9699079Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-09-07T07:46:52.9700624Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-09-07T07:46:52.9702036Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-09-07T07:46:52.9703363Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-09-07T07:46:52.9704691Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-09-07T07:46:52.9706137Z * [new tag] v2.7.0 -> v2.7.0 2025-09-07T07:46:52.9707391Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-09-07T07:46:52.9708401Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-09-07T07:46:52.9709724Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-09-07T07:46:52.9711275Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-09-07T07:46:52.9712514Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-09-07T07:46:52.9713753Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-09-07T07:46:52.9714958Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-09-07T07:46:52.9716203Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-09-07T07:46:52.9717555Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-09-07T07:46:52.9718975Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-09-07T07:46:52.9719875Z * [new tag] v2.7.1 -> v2.7.1 2025-09-07T07:46:52.9721367Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-09-07T07:46:52.9722589Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-09-07T07:46:52.9723807Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-09-07T07:46:52.9725160Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-09-07T07:46:52.9726197Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-09-07T07:46:52.9727276Z * [new tag] v2.8.0 -> v2.8.0 2025-09-07T07:46:52.9728510Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-09-07T07:46:52.9729708Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-09-07T07:46:52.9731268Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-09-07T07:46:52.9732516Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-09-07T07:46:52.9733818Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-09-07T07:46:52.9735212Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-09-07T07:46:52.9736543Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-09-07T07:46:52.9737805Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-09-07T07:46:52.9739082Z * [new tag] whc_flight_1 -> whc_flight_1 2025-09-07T07:46:52.9740568Z * [new tag] whc_flight_2 -> whc_flight_2 2025-09-07T07:46:52.9741673Z * [new tag] whc_flight_4 -> whc_flight_4 2025-09-07T07:46:53.0587068Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:46:53.0617472Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:46:53.0622173Z ##[endgroup] 2025-09-07T07:46:53.0622412Z ##[group]Determining the checkout info 2025-09-07T07:46:53.0623256Z ##[endgroup] 2025-09-07T07:46:53.0627061Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:46:53.0675447Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:46:53.0707113Z ##[group]Checking out the ref 2025-09-07T07:46:53.0710564Z [command]/usr/bin/git checkout --progress 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You can look around, make experimental 2025-09-07T07:46:54.4144629Z changes and commit them, and you can discard any commits you make in this 2025-09-07T07:46:54.4145134Z state without impacting any branches by switching back to a branch. 2025-09-07T07:46:54.4145417Z 2025-09-07T07:46:54.4145611Z If you want to create a new branch to retain commits you create, you may 2025-09-07T07:46:54.4146065Z do so (now or later) by using -c with the switch command. Example: 2025-09-07T07:46:54.4146355Z 2025-09-07T07:46:54.4146462Z git switch -c 2025-09-07T07:46:54.4146644Z 2025-09-07T07:46:54.4146747Z Or undo this operation with: 2025-09-07T07:46:54.4146909Z 2025-09-07T07:46:54.4146994Z git switch - 2025-09-07T07:46:54.4147119Z 2025-09-07T07:46:54.4147334Z Turn off this advice by setting config variable advice.detachedHead to false 2025-09-07T07:46:54.4147647Z 2025-09-07T07:46:54.4147807Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:46:54.4271753Z ##[endgroup] 2025-09-07T07:46:54.4272161Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:46:54.4277406Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:46:54.4319659Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:46:54.4350779Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:46:54.4381356Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:46:54.4412726Z ##[endgroup] 2025-09-07T07:46:54.4413039Z ##[group]Fetching submodules 2025-09-07T07:46:54.4416255Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:46:54.4691229Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-09-07T07:46:54.4950101Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-09-07T07:46:54.4958850Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-09-07T07:46:54.4968821Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-09-07T07:46:54.4978820Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-09-07T07:46:54.4989160Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-09-07T07:46:54.5000148Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-09-07T07:46:54.5010489Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-09-07T07:46:54.5021114Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-09-07T07:46:54.5031872Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-09-07T07:46:54.5042974Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-09-07T07:46:54.5053436Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-09-07T07:46:54.5063936Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-09-07T07:46:54.5074397Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-09-07T07:46:54.5085585Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-09-07T07:46:54.5096577Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-09-07T07:46:54.5107729Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-09-07T07:46:54.5119324Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-09-07T07:46:54.5131075Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-09-07T07:46:54.5142791Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:46:54.5153655Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-09-07T07:46:54.5164708Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-09-07T07:46:54.5176152Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-09-07T07:46:54.5187721Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-09-07T07:46:54.5199347Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-09-07T07:46:54.5210730Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-09-07T07:46:54.5222083Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-09-07T07:46:54.5234008Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-09-07T07:46:54.5245381Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-09-07T07:46:54.5257498Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-09-07T07:46:54.5268853Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-09-07T07:46:54.5280616Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-09-07T07:46:54.5292047Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-09-07T07:46:54.5303631Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-09-07T07:46:54.5315168Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-09-07T07:46:54.5327620Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-09-07T07:46:54.5339470Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-09-07T07:46:54.5351785Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-09-07T07:46:54.5385116Z Cloning into '/home/charlie/_work/pytorch/pytorch/android/libs/fbjni'... 2025-09-07T07:46:54.9143208Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/FP16'... 2025-09-07T07:46:55.4268448Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/FXdiv'... 2025-09-07T07:46:55.7099873Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/NNPACK'... 2025-09-07T07:46:56.0792051Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/NVTX'... 2025-09-07T07:46:56.6369265Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-09-07T07:46:57.7793164Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-09-07T07:47:08.6004545Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/aiter'... 2025-09-07T07:47:12.6456427Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/benchmark'... 2025-09-07T07:47:14.7407023Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-09-07T07:47:17.9914448Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-09-07T07:47:18.6327915Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-09-07T07:47:19.3362213Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-09-07T07:47:20.4390667Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/cutlass'... 2025-09-07T07:47:23.3732228Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm'... 2025-09-07T07:47:25.5808088Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/flash-attention'... 2025-09-07T07:47:26.8326833Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-09-07T07:47:28.6224068Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fmt'... 2025-09-07T07:47:30.3356851Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-09-07T07:47:31.3408106Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/gloo'... 2025-09-07T07:47:32.1734378Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/googletest'... 2025-09-07T07:47:33.1098622Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/ideep'... 2025-09-07T07:47:33.5449535Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/ittapi'... 2025-09-07T07:47:34.1411466Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto'... 2025-09-07T07:47:35.3491627Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kleidiai'... 2025-09-07T07:47:35.9230453Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/mimalloc'... 2025-09-07T07:47:36.8240664Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/nlohmann'... 2025-09-07T07:47:43.8364358Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/onnx'... 2025-09-07T07:47:46.7264494Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-09-07T07:47:51.2000587Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/pocketfft'... 2025-09-07T07:47:51.5858042Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/protobuf'... 2025-09-07T07:47:59.9564180Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/psimd'... 2025-09-07T07:48:00.2487802Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-09-07T07:48:01.7896623Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/pybind11'... 2025-09-07T07:48:02.7273635Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-09-07T07:48:03.1297589Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/sleef'... 2025-09-07T07:48:03.9972078Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-09-07T07:48:04.5255091Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-09-07T07:48:04.5408198Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-09-07T07:48:04.5525904Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:48:04.5817673Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:48:04.6698770Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:48:04.7297441Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:48:05.5173544Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:48:05.6747843Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:48:05.6782364Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:48:05.6815889Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-09-07T07:48:09.0128336Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:48:09.0388990Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:48:09.4228299Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-09-07T07:48:09.4721510Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246' 2025-09-07T07:48:09.5775886Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-09-07T07:48:09.6204406Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-09-07T07:48:10.2728634Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-09-07T07:48:10.4190064Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d' 2025-09-07T07:48:10.4222763Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-09-07T07:48:10.4232568Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:48:10.4241857Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:48:10.4252027Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-09-07T07:48:10.4262181Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-09-07T07:48:10.4272485Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:48:10.4282565Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-09-07T07:48:10.4314215Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-09-07T07:48:11.7386788Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-09-07T07:48:12.7569586Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-09-07T07:48:13.4646998Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-09-07T07:48:15.1749190Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-09-07T07:48:16.0735594Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-09-07T07:48:16.4994582Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-09-07T07:48:26.5158114Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-09-07T07:48:26.8096328Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-09-07T07:48:26.9123820Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-09-07T07:48:27.5625317Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917' 2025-09-07T07:48:27.6080138Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:27.6208122Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691' 2025-09-07T07:48:27.7256760Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-09-07T07:48:27.7995287Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-09-07T07:48:27.8027504Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:48:27.8041386Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:48:27.8071732Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-09-07T07:48:30.8663648Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-09-07T07:48:34.1827646Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-09-07T07:48:34.7684182Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-09-07T07:48:35.0077477Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-09-07T07:48:35.0406341Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-09-07T07:48:35.0818039Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-09-07T07:48:35.1085090Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-09-07T07:48:35.1529526Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-09-07T07:48:35.1673664Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-09-07T07:48:35.1699448Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-09-07T07:48:35.1733062Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-09-07T07:48:51.6051832Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:48:51.6303648Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:48:51.7968070Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:48:51.8065190Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:48:51.8283701Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:48:51.8577346Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:48:51.8611353Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-09-07T07:48:52.9468856Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-09-07T07:48:54.6757370Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-09-07T07:48:56.6565429Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:48:56.7011016Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:48:56.7051848Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:48:56.7193627Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:48:56.7329464Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:48:56.7472081Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:48:56.7688553Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:48:56.7802316Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:48:56.8004991Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:48:56.8041649Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-09-07T07:48:58.4132355Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-09-07T07:48:59.4264916Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-09-07T07:49:01.0407562Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-09-07T07:49:01.9226104Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-09-07T07:49:02.9261300Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-09-07T07:49:04.4059981Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-09-07T07:49:14.1771873Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-09-07T07:49:15.5670698Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:49:15.5909873Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:49:15.6339659Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:49:15.6525252Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:49:15.6638771Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:49:15.6669387Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-09-07T07:49:16.6355036Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:49:16.6647696Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:49:16.8537046Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:49:16.9628791Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:49:16.9825996Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-09-07T07:49:17.0229045Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-09-07T07:49:17.0831706Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-09-07T07:49:17.1286292Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-09-07T07:49:17.3995864Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e' 2025-09-07T07:49:17.5172570Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72' 2025-09-07T07:49:19.6551789Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83' 2025-09-07T07:49:19.6781824Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11' 2025-09-07T07:49:19.6819814Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'... 2025-09-07T07:49:21.1064304Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4' 2025-09-07T07:49:21.2152410Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878' 2025-09-07T07:49:21.2262123Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:49:21.2474762Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:49:21.2665559Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:49:21.2797662Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:49:21.2940073Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:49:21.3065250Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:49:21.3277786Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:49:21.3510963Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:49:21.3542501Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-09-07T07:49:22.3723202Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-09-07T07:49:24.0500860Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-09-07T07:49:24.9057145Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-09-07T07:49:36.2802558Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-09-07T07:49:37.2390144Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-09-07T07:49:37.9354989Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-09-07T07:49:38.8537071Z Cloning into '/home/charlie/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-09-07T07:49:45.5779641Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-09-07T07:49:45.7989135Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-09-07T07:49:45.8914522Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa' 2025-09-07T07:49:46.2132284Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d' 2025-09-07T07:49:46.3633040Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce' 2025-09-07T07:49:46.3797259Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5' 2025-09-07T07:49:46.3974044Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d' 2025-09-07T07:49:46.5335599Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:49:46.5367730Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 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2025-09-07T07:50:00.1250953Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:00.1301054Z Entering 'third_party/sleef' 2025-09-07T07:50:00.1352129Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:00.1401225Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:00.1448183Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:00.1495419Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:00.1541509Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:00.1588214Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:00.1667244Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url" 2025-09-07T07:50:00.1929281Z Entering 'android/libs/fbjni' 2025-09-07T07:50:00.1972156Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:50:00.1995008Z Entering 'third_party/FP16' 2025-09-07T07:50:00.2037324Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:50:00.2060087Z Entering 'third_party/FXdiv' 2025-09-07T07:50:00.2104385Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:50:00.2126893Z Entering 'third_party/NNPACK' 2025-09-07T07:50:00.2167564Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:50:00.2190431Z Entering 'third_party/NVTX' 2025-09-07T07:50:00.2233922Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:50:00.2255883Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:00.2299765Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:50:00.2323589Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:00.2367141Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:50:00.2406614Z Entering 'third_party/aiter' 2025-09-07T07:50:00.2449383Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:50:00.2470712Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:00.2511380Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:50:00.2542977Z Entering 'third_party/benchmark' 2025-09-07T07:50:00.2585617Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:00.2608671Z Entering 'third_party/composable_kernel' 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file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T07:50:00.3016251Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:00.3056769Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T07:50:00.3078823Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:00.3119842Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T07:50:00.3149785Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:00.3192229Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T07:50:00.3214044Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:00.3254897Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T07:50:00.3286959Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:00.3328631Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T07:50:00.3349887Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:00.3391990Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T07:50:00.3413006Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:00.3455471Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T07:50:00.3480908Z Entering 'third_party/flash-attention' 2025-09-07T07:50:00.3523655Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:50:00.3546977Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:00.3589488Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:50:00.3617334Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:00.3659038Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:50:00.3690139Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:00.3733176Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:50:00.3758063Z Entering 'third_party/fmt' 2025-09-07T07:50:00.3799900Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:50:00.3822310Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:00.3865699Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T07:50:00.3888282Z Entering 'third_party/gloo' 2025-09-07T07:50:00.3931102Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T07:50:00.3953527Z Entering 'third_party/googletest' 2025-09-07T07:50:00.3995641Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:00.4018180Z Entering 'third_party/ideep' 2025-09-07T07:50:00.4059800Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T07:50:00.4080610Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:00.4121686Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T07:50:00.4150671Z Entering 'third_party/ittapi' 2025-09-07T07:50:00.4192853Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:50:00.4215237Z Entering 'third_party/kineto' 2025-09-07T07:50:00.4259081Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:50:00.4280427Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:00.4323487Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:50:00.4343619Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:00.4387607Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:50:00.4410730Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:00.4453025Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T07:50:00.4474571Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:00.4516679Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:50:00.4539073Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:00.4581411Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T07:50:00.4600776Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:00.4643544Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T07:50:00.4668931Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:00.4711498Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T07:50:00.4733038Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:00.4776268Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:00.4797852Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:00.4841539Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T07:50:00.4864350Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:00.4907007Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:50:00.4932754Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:00.4975289Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:50:00.4996230Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:00.5037190Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:50:00.5060875Z Entering 'third_party/kleidiai' 2025-09-07T07:50:00.5102889Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:50:00.5125128Z Entering 'third_party/mimalloc' 2025-09-07T07:50:00.5166663Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:50:00.5188816Z Entering 'third_party/nlohmann' 2025-09-07T07:50:00.5230752Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:50:00.5254361Z Entering 'third_party/onnx' 2025-09-07T07:50:00.5299336Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:50:00.5336499Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:00.5379265Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:00.5406446Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:00.5450148Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T07:50:00.5472366Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:00.5515314Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:00.5537999Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:00.5582371Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:00.5604206Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:00.5647041Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config remote.origin.url 2025-09-07T07:50:00.5668279Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:00.5711605Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config remote.origin.url 2025-09-07T07:50:00.5733310Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:00.5773661Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config remote.origin.url 2025-09-07T07:50:00.5793863Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:00.5835381Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config remote.origin.url 2025-09-07T07:50:00.5856811Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:00.5897439Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config remote.origin.url 2025-09-07T07:50:00.5917240Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:00.5959325Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config remote.origin.url 2025-09-07T07:50:00.5982924Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:00.6025200Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/googletest/config remote.origin.url 2025-09-07T07:50:00.6049504Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:00.6090428Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/tools/vcpkg/config remote.origin.url 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'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:03.2200522Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2236737Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:03.2264125Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2302152Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:03.2329328Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2364923Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:03.2394191Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2431741Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:03.2458877Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2496865Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:03.2524880Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2563892Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:03.2590894Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2626864Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:03.2655195Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2693281Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:03.2720918Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2758416Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:03.2785894Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2825864Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:03.2852885Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2889095Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:03.2915200Z http.https://github.com/.extraheader 2025-09-07T07:50:03.2953294Z Entering 'third_party/kleidiai' 2025-09-07T07:50:03.2980723Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3016758Z Entering 'third_party/mimalloc' 2025-09-07T07:50:03.3045237Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3081457Z Entering 'third_party/nlohmann' 2025-09-07T07:50:03.3110515Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3148282Z Entering 'third_party/onnx' 2025-09-07T07:50:03.3176639Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3226604Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:03.3254061Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3297185Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:03.3325983Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3365318Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:03.3392455Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3429101Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:03.3457096Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3492915Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:03.3521481Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3559106Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:03.3585979Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3625032Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:03.3652537Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3688650Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:03.3716967Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3752539Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:03.3779498Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3814578Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:03.3841110Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3879085Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:03.3906684Z http.https://github.com/.extraheader 2025-09-07T07:50:03.3947464Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:03.3974420Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4029919Z Entering 'third_party/pocketfft' 2025-09-07T07:50:03.4059056Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4096813Z Entering 'third_party/protobuf' 2025-09-07T07:50:03.4125941Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4165464Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:03.4194124Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4232257Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:03.4258867Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4298511Z Entering 'third_party/psimd' 2025-09-07T07:50:03.4327377Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4365048Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:03.4393964Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4429858Z Entering 'third_party/pybind11' 2025-09-07T07:50:03.4458059Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4494140Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:03.4523207Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4560955Z Entering 'third_party/sleef' 2025-09-07T07:50:03.4590498Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4627778Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:03.4658561Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4693918Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:03.4720861Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4757740Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:03.4783948Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4820556Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:03.4848957Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4885267Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:03.4910910Z http.https://github.com/.extraheader 2025-09-07T07:50:03.4945666Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:03.4973130Z http.https://github.com/.extraheader 2025-09-07T07:50:03.5035866Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:50:03.5074981Z ##[endgroup] 2025-09-07T07:50:03.5075345Z ##[group]Fetching the repository 2025-09-07T07:50:03.5082933Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-09-07T07:50:04.0854329Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object} 2025-09-07T07:50:04.0882721Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:04.0887857Z ##[endgroup] 2025-09-07T07:50:04.0888243Z ##[group]Determining the checkout info 2025-09-07T07:50:04.0889141Z ##[endgroup] 2025-09-07T07:50:04.0892684Z [command]/usr/bin/git sparse-checkout disable 2025-09-07T07:50:04.1076805Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-09-07T07:50:04.1105323Z ##[group]Checking out the ref 2025-09-07T07:50:04.1109343Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:04.1434510Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000) 2025-09-07T07:50:04.1444741Z ##[endgroup] 2025-09-07T07:50:04.1445097Z ##[group]Setting up auth for fetching submodules 2025-09-07T07:50:04.1448720Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-09-07T07:50:04.1486133Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-09-07T07:50:04.1515969Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-09-07T07:50:04.1551133Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-09-07T07:50:04.1579377Z ##[endgroup] 2025-09-07T07:50:04.1579802Z ##[group]Fetching submodules 2025-09-07T07:50:04.1582637Z [command]/usr/bin/git submodule sync --recursive 2025-09-07T07:50:04.1860617Z Synchronizing submodule url for 'android/libs/fbjni' 2025-09-07T07:50:04.1886249Z Synchronizing submodule url for 'third_party/FP16' 2025-09-07T07:50:04.1912290Z Synchronizing submodule url for 'third_party/FXdiv' 2025-09-07T07:50:04.1936421Z Synchronizing submodule url for 'third_party/NNPACK' 2025-09-07T07:50:04.1960767Z Synchronizing submodule url for 'third_party/NVTX' 2025-09-07T07:50:04.1985894Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:04.2009914Z Synchronizing submodule url for 'third_party/XNNPACK' 2025-09-07T07:50:04.2047649Z Synchronizing submodule url for 'third_party/aiter' 2025-09-07T07:50:04.2071678Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:04.2105941Z Synchronizing submodule url for 'third_party/benchmark' 2025-09-07T07:50:04.2131886Z Synchronizing submodule url for 'third_party/composable_kernel' 2025-09-07T07:50:04.2164156Z Synchronizing submodule url for 'third_party/cpp-httplib' 2025-09-07T07:50:04.2191199Z Synchronizing submodule url for 'third_party/cpuinfo' 2025-09-07T07:50:04.2216413Z Synchronizing submodule url for 'third_party/cudnn_frontend' 2025-09-07T07:50:04.2242118Z Synchronizing submodule url for 'third_party/cutlass' 2025-09-07T07:50:04.2275382Z Synchronizing submodule url for 'third_party/fbgemm' 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'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:04.2578803Z Synchronizing submodule url for 'third_party/flatbuffers' 2025-09-07T07:50:04.2606854Z Synchronizing submodule url for 'third_party/fmt' 2025-09-07T07:50:04.2631961Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:04.2656122Z Synchronizing submodule url for 'third_party/gloo' 2025-09-07T07:50:04.2680884Z Synchronizing submodule url for 'third_party/googletest' 2025-09-07T07:50:04.2705692Z Synchronizing submodule url for 'third_party/ideep' 2025-09-07T07:50:04.2727346Z Synchronizing submodule url for 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:04.2760376Z Synchronizing submodule url for 'third_party/ittapi' 2025-09-07T07:50:04.2785631Z Synchronizing submodule url for 'third_party/kineto' 2025-09-07T07:50:04.2808980Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:04.2832602Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:04.2857765Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:04.2883041Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:04.2906705Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:04.2930380Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:04.2958747Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:04.2983225Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:04.3009037Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:04.3034388Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:04.3059044Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:04.3082493Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:04.3109151Z Synchronizing submodule url for 'third_party/kleidiai' 2025-09-07T07:50:04.3134896Z Synchronizing submodule url for 'third_party/mimalloc' 2025-09-07T07:50:04.3159440Z Synchronizing submodule url for 'third_party/nlohmann' 2025-09-07T07:50:04.3185751Z Synchronizing submodule url for 'third_party/onnx' 2025-09-07T07:50:04.3222818Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:04.3253046Z Synchronizing submodule url for 'third_party/opentelemetry-cpp' 2025-09-07T07:50:04.3277724Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:04.3301952Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:04.3325218Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:04.3348249Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:04.3372598Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:04.3395659Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:04.3418364Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:04.3440013Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:04.3465128Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:04.3489364Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:04.3532724Z Synchronizing submodule url for 'third_party/pocketfft' 2025-09-07T07:50:04.3557927Z Synchronizing submodule url for 'third_party/protobuf' 2025-09-07T07:50:04.3583466Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:04.3606891Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:04.3634319Z Synchronizing submodule url for 'third_party/psimd' 2025-09-07T07:50:04.3659373Z Synchronizing submodule url for 'third_party/pthreadpool' 2025-09-07T07:50:04.3683764Z Synchronizing submodule url for 'third_party/pybind11' 2025-09-07T07:50:04.3708612Z Synchronizing submodule url for 'third_party/python-peachpy' 2025-09-07T07:50:04.3733164Z Synchronizing submodule url for 'third_party/sleef' 2025-09-07T07:50:04.3758365Z Synchronizing submodule url for 'third_party/tensorpipe' 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'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-09-07T07:50:04.4779310Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-09-07T07:50:04.5603958Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-09-07T07:50:04.5989547Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-09-07T07:50:05.2823088Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-09-07T07:50:05.4845191Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-09-07T07:50:05.5096169Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-09-07T07:50:05.5306993Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-09-07T07:50:05.8501311Z Submodule path 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'8d263e693366ef8db40acc569cc7d8edf644556d' 2025-09-07T07:50:09.8157539Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-09-07T07:50:09.9008411Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-09-07T07:50:10.0420595Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-09-07T07:50:10.2157287Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-09-07T07:50:10.2323979Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-09-07T07:50:10.2631267Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-09-07T07:50:10.2779890Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-09-07T07:50:10.2884418Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-09-07T07:50:10.3051613Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-09-07T07:50:10.3394895Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-09-07T07:50:10.4245113Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-09-07T07:50:10.4411303Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 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2025-09-07T07:50:12.2364503Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:12.2407528Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:12.2448707Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:12.2492669Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:12.2533291Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:12.2575237Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:12.2616696Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:12.2662109Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:12.2707156Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:12.2768906Z Entering 'third_party/pocketfft' 2025-09-07T07:50:12.2814157Z Entering 'third_party/protobuf' 2025-09-07T07:50:12.2860414Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:12.2903107Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:12.2951859Z Entering 'third_party/psimd' 2025-09-07T07:50:12.2996617Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:12.3040069Z Entering 'third_party/pybind11' 2025-09-07T07:50:12.3084623Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:12.3128898Z Entering 'third_party/sleef' 2025-09-07T07:50:12.3174788Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:12.3217703Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:12.3260558Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:12.3301294Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:12.3342992Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:12.3384505Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:12.3448562Z ##[endgroup] 2025-09-07T07:50:12.3449003Z ##[group]Persisting credentials for submodules 2025-09-07T07:50:12.3456127Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'url\.https\:\/\/github\.com\/\.insteadOf' && git config --local --unset-all 'url.https://github.com/.insteadOf' || :" 2025-09-07T07:50:12.3725991Z Entering 'android/libs/fbjni' 2025-09-07T07:50:12.3750365Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3750655Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3786952Z Entering 'third_party/FP16' 2025-09-07T07:50:12.3815616Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3815934Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3854615Z Entering 'third_party/FXdiv' 2025-09-07T07:50:12.3884483Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3884953Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3920976Z Entering 'third_party/NNPACK' 2025-09-07T07:50:12.3948672Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3948963Z url.https://github.com/.insteadof 2025-09-07T07:50:12.3985413Z Entering 'third_party/NVTX' 2025-09-07T07:50:12.4013795Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4014089Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4051283Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:12.4081007Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4081440Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4119505Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:12.4148380Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4148672Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4200555Z Entering 'third_party/aiter' 2025-09-07T07:50:12.4229276Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4229571Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4267648Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:12.4295382Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4295689Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4340162Z Entering 'third_party/benchmark' 2025-09-07T07:50:12.4369351Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4369665Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4406093Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:12.4435270Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4435604Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4481275Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:12.4510325Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4510629Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4546193Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:12.4575047Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4575357Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4612735Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:12.4640063Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4640524Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4677721Z Entering 'third_party/cutlass' 2025-09-07T07:50:12.4706386Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4706694Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4755539Z Entering 'third_party/fbgemm' 2025-09-07T07:50:12.4784590Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4784875Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4822402Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:12.4850156Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4850522Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4885636Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:12.4912293Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4912547Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4953953Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:12.4981051Z url.https://github.com/.insteadof 2025-09-07T07:50:12.4981338Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5016621Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:12.5044214Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5044523Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5095295Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:12.5124539Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5124862Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5160023Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:12.5187597Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5187873Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5222915Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:12.5250482Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5250795Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5291952Z Entering 'third_party/flash-attention' 2025-09-07T07:50:12.5320011Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5320484Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5358272Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:12.5385400Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5385677Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5426201Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:12.5454350Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5454667Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5500837Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:12.5529171Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5529467Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5569018Z Entering 'third_party/fmt' 2025-09-07T07:50:12.5597157Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5599203Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5634120Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:12.5662422Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5662809Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5700035Z Entering 'third_party/gloo' 2025-09-07T07:50:12.5728464Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5728759Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5764711Z Entering 'third_party/googletest' 2025-09-07T07:50:12.5792135Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5792408Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5828917Z Entering 'third_party/ideep' 2025-09-07T07:50:12.5856605Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5856865Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5892481Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:12.5919810Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5920106Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5966124Z Entering 'third_party/ittapi' 2025-09-07T07:50:12.5995544Z url.https://github.com/.insteadof 2025-09-07T07:50:12.5995839Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6033306Z Entering 'third_party/kineto' 2025-09-07T07:50:12.6061360Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6061652Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6113347Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:12.6127376Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6127641Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6163977Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:12.6192107Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6192378Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6229110Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:12.6256302Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6256611Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6291875Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:12.6318293Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6318579Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6355652Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:12.6383425Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6383707Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6418512Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:12.6445295Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6445597Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6484429Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:12.6513743Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6514008Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6550457Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:12.6578573Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6578866Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6615427Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:12.6643513Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6643843Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6682062Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:12.6708895Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6709331Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6748254Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:12.6775470Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6775769Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6811029Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:12.6838606Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6839064Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6877135Z Entering 'third_party/kleidiai' 2025-09-07T07:50:12.6905325Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6905641Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6944232Z Entering 'third_party/mimalloc' 2025-09-07T07:50:12.6973106Z url.https://github.com/.insteadof 2025-09-07T07:50:12.6973401Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7009367Z Entering 'third_party/nlohmann' 2025-09-07T07:50:12.7037288Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7037619Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7076960Z Entering 'third_party/onnx' 2025-09-07T07:50:12.7108106Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7108836Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7161945Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:12.7192389Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7192758Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7233129Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:12.7260754Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7261036Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7299453Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:12.7326763Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7327156Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7363937Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:12.7392104Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7392402Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7428325Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:12.7457214Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7457507Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7491855Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:12.7519128Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7519381Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7556131Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:12.7583831Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7619785Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7620148Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:12.7646850Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7647120Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7681946Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:12.7707864Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7708140Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7742547Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:12.7771473Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7771782Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7811260Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:12.7838010Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7838300Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7877206Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:12.7903447Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7903956Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7959972Z Entering 'third_party/pocketfft' 2025-09-07T07:50:12.7988629Z url.https://github.com/.insteadof 2025-09-07T07:50:12.7988937Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8025513Z Entering 'third_party/protobuf' 2025-09-07T07:50:12.8053213Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8053527Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8092581Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:12.8120031Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8120506Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8156318Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:12.8182860Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8183131Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8222606Z Entering 'third_party/psimd' 2025-09-07T07:50:12.8250852Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8251167Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8286834Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:12.8315964Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8316294Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8352166Z Entering 'third_party/pybind11' 2025-09-07T07:50:12.8381552Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8381849Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8417333Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:12.8445712Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8446019Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8481696Z Entering 'third_party/sleef' 2025-09-07T07:50:12.8510195Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8510593Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8548201Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:12.8576143Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8576440Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8612594Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:12.8641047Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8641370Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8677629Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:12.8704257Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8704536Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8740440Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:12.8767842Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8768144Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8804844Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:12.8834007Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8834274Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8868357Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:12.8896103Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8896398Z url.https://github.com/.insteadof 2025-09-07T07:50:12.8959792Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url" 2025-09-07T07:50:12.9224547Z Entering 'android/libs/fbjni' 2025-09-07T07:50:12.9267395Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-09-07T07:50:12.9291109Z Entering 'third_party/FP16' 2025-09-07T07:50:12.9334147Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-09-07T07:50:12.9356549Z Entering 'third_party/FXdiv' 2025-09-07T07:50:12.9398362Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-09-07T07:50:12.9419664Z Entering 'third_party/NNPACK' 2025-09-07T07:50:12.9463611Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config remote.origin.url 2025-09-07T07:50:12.9486246Z Entering 'third_party/NVTX' 2025-09-07T07:50:12.9528482Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config remote.origin.url 2025-09-07T07:50:12.9552186Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:12.9594062Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config remote.origin.url 2025-09-07T07:50:12.9616581Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:12.9659942Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config remote.origin.url 2025-09-07T07:50:12.9698351Z Entering 'third_party/aiter' 2025-09-07T07:50:12.9742878Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/aiter/config remote.origin.url 2025-09-07T07:50:12.9769819Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:12.9808819Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config remote.origin.url 2025-09-07T07:50:12.9839029Z Entering 'third_party/benchmark' 2025-09-07T07:50:12.9881920Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:12.9903439Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:12.9947826Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config remote.origin.url 2025-09-07T07:50:12.9978355Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:13.0021816Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config remote.origin.url 2025-09-07T07:50:13.0044094Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:13.0086830Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config remote.origin.url 2025-09-07T07:50:13.0112946Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:13.0155323Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config remote.origin.url 2025-09-07T07:50:13.0178341Z Entering 'third_party/cutlass' 2025-09-07T07:50:13.0223105Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config remote.origin.url 2025-09-07T07:50:13.0255021Z Entering 'third_party/fbgemm' 2025-09-07T07:50:13.0298333Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config remote.origin.url 2025-09-07T07:50:13.0321574Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:13.0362731Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config remote.origin.url 2025-09-07T07:50:13.0383382Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:13.0424123Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config remote.origin.url 2025-09-07T07:50:13.0453319Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:13.0495745Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config remote.origin.url 2025-09-07T07:50:13.0517430Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:13.0561546Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config remote.origin.url 2025-09-07T07:50:13.0590520Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:13.0634036Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config remote.origin.url 2025-09-07T07:50:13.0655950Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:13.0698517Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config remote.origin.url 2025-09-07T07:50:13.0721544Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:13.0764787Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config remote.origin.url 2025-09-07T07:50:13.0791210Z Entering 'third_party/flash-attention' 2025-09-07T07:50:13.0838128Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config remote.origin.url 2025-09-07T07:50:13.0861091Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:13.0901702Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config remote.origin.url 2025-09-07T07:50:13.0931246Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:13.0972678Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config remote.origin.url 2025-09-07T07:50:13.1003774Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:13.1046130Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config remote.origin.url 2025-09-07T07:50:13.1071504Z Entering 'third_party/fmt' 2025-09-07T07:50:13.1113758Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:50:13.1136354Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:13.1179601Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config remote.origin.url 2025-09-07T07:50:13.1202560Z Entering 'third_party/gloo' 2025-09-07T07:50:13.1244686Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/gloo/config remote.origin.url 2025-09-07T07:50:13.1266640Z Entering 'third_party/googletest' 2025-09-07T07:50:13.1309551Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:13.1332786Z Entering 'third_party/ideep' 2025-09-07T07:50:13.1373800Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/ideep/config remote.origin.url 2025-09-07T07:50:13.1393792Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:13.1435480Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config remote.origin.url 2025-09-07T07:50:13.1465327Z Entering 'third_party/ittapi' 2025-09-07T07:50:13.1507566Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config remote.origin.url 2025-09-07T07:50:13.1529548Z Entering 'third_party/kineto' 2025-09-07T07:50:13.1575527Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/config remote.origin.url 2025-09-07T07:50:13.1596725Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:13.1640710Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config remote.origin.url 2025-09-07T07:50:13.1660991Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:13.1706024Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config remote.origin.url 2025-09-07T07:50:13.1729035Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:13.1769605Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config remote.origin.url 2025-09-07T07:50:13.1791590Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:13.1833439Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config remote.origin.url 2025-09-07T07:50:13.1854927Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:13.1898117Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config remote.origin.url 2025-09-07T07:50:13.1918621Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:13.1962024Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config remote.origin.url 2025-09-07T07:50:13.1987183Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:13.2031461Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config remote.origin.url 2025-09-07T07:50:13.2052850Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:13.2093760Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:13.2114940Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:13.2156809Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config remote.origin.url 2025-09-07T07:50:13.2179126Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:13.2224542Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config remote.origin.url 2025-09-07T07:50:13.2248498Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:13.2289743Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config remote.origin.url 2025-09-07T07:50:13.2310381Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:13.2350625Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config remote.origin.url 2025-09-07T07:50:13.2373495Z Entering 'third_party/kleidiai' 2025-09-07T07:50:13.2417880Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config remote.origin.url 2025-09-07T07:50:13.2440470Z Entering 'third_party/mimalloc' 2025-09-07T07:50:13.2483438Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config remote.origin.url 2025-09-07T07:50:13.2506471Z Entering 'third_party/nlohmann' 2025-09-07T07:50:13.2546966Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config remote.origin.url 2025-09-07T07:50:13.2570092Z Entering 'third_party/onnx' 2025-09-07T07:50:13.2612699Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/onnx/config remote.origin.url 2025-09-07T07:50:13.2648719Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:13.2692621Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:13.2719177Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:13.2761694Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config remote.origin.url 2025-09-07T07:50:13.2784687Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:13.2828789Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:13.2850660Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:13.2892874Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:13.2916208Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:13.2958080Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config remote.origin.url 2025-09-07T07:50:13.2979100Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:13.3019512Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config remote.origin.url 2025-09-07T07:50:13.3041188Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:13.3084986Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config remote.origin.url 2025-09-07T07:50:13.3106326Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:13.3149644Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config remote.origin.url 2025-09-07T07:50:13.3170403Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:13.3211995Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config remote.origin.url 2025-09-07T07:50:13.3233046Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:13.3274625Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config remote.origin.url 2025-09-07T07:50:13.3298548Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:13.3340196Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/googletest/config remote.origin.url 2025-09-07T07:50:13.3364863Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:13.3406034Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/tools/vcpkg/config remote.origin.url 2025-09-07T07:50:13.3446905Z Entering 'third_party/pocketfft' 2025-09-07T07:50:13.3490021Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/pocketfft/config remote.origin.url 2025-09-07T07:50:13.3511503Z Entering 'third_party/protobuf' 2025-09-07T07:50:13.3552707Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/protobuf/config remote.origin.url 2025-09-07T07:50:13.3576929Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:13.3619593Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/benchmark/config remote.origin.url 2025-09-07T07:50:13.3640950Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:13.3683654Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:13.3708224Z Entering 'third_party/psimd' 2025-09-07T07:50:13.3751077Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/psimd/config remote.origin.url 2025-09-07T07:50:13.3772353Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:13.3815215Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/pthreadpool/config remote.origin.url 2025-09-07T07:50:13.3837942Z Entering 'third_party/pybind11' 2025-09-07T07:50:13.3881247Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:13.3903335Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:13.3946657Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/python-peachpy/config remote.origin.url 2025-09-07T07:50:13.3968680Z Entering 'third_party/sleef' 2025-09-07T07:50:13.4011206Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/sleef/config remote.origin.url 2025-09-07T07:50:13.4034437Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:13.4076335Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/config remote.origin.url 2025-09-07T07:50:13.4097935Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:13.4139720Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/googletest/config remote.origin.url 2025-09-07T07:50:13.4160342Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:13.4201224Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libnop/config remote.origin.url 2025-09-07T07:50:13.4222510Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:13.4263930Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libuv/config remote.origin.url 2025-09-07T07:50:13.4285521Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:13.4326031Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/config remote.origin.url 2025-09-07T07:50:13.4346200Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:13.4387759Z file:/home/charlie/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/modules/tools/clang/config remote.origin.url 2025-09-07T07:50:13.4663218Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'git@github.com:' 2025-09-07T07:50:13.4927235Z Entering 'android/libs/fbjni' 2025-09-07T07:50:13.4972166Z Entering 'third_party/FP16' 2025-09-07T07:50:13.5017318Z Entering 'third_party/FXdiv' 2025-09-07T07:50:13.5064021Z Entering 'third_party/NNPACK' 2025-09-07T07:50:13.5108021Z Entering 'third_party/NVTX' 2025-09-07T07:50:13.5153896Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:13.5198431Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:13.5256569Z Entering 'third_party/aiter' 2025-09-07T07:50:13.5301737Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:13.5354289Z Entering 'third_party/benchmark' 2025-09-07T07:50:13.5398193Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:13.5451583Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:13.5495420Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:13.5541072Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:13.5585340Z Entering 'third_party/cutlass' 2025-09-07T07:50:13.5637932Z Entering 'third_party/fbgemm' 2025-09-07T07:50:13.5689497Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:13.5972057Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:13.6023325Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:13.6066607Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:13.6116676Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:13.6157598Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:13.6205309Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:13.6252900Z Entering 'third_party/flash-attention' 2025-09-07T07:50:13.6296999Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:13.6349110Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:13.6400715Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:13.6446081Z Entering 'third_party/fmt' 2025-09-07T07:50:13.6489833Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:13.6535133Z Entering 'third_party/gloo' 2025-09-07T07:50:13.6579067Z Entering 'third_party/googletest' 2025-09-07T07:50:13.6624231Z Entering 'third_party/ideep' 2025-09-07T07:50:13.6667475Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:13.6719261Z Entering 'third_party/ittapi' 2025-09-07T07:50:13.6763378Z Entering 'third_party/kineto' 2025-09-07T07:50:13.6806308Z Entering 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'third_party/psimd' 2025-09-07T07:50:13.8289375Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:13.8334487Z Entering 'third_party/pybind11' 2025-09-07T07:50:13.8379472Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:13.8424305Z Entering 'third_party/sleef' 2025-09-07T07:50:13.8469594Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:13.8513524Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:13.8555113Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:13.8598678Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:13.8641518Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:13.8682209Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:13.8746969Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-09-07T07:50:13.9011525Z Entering 'android/libs/fbjni' 2025-09-07T07:50:13.9055588Z Entering 'third_party/FP16' 2025-09-07T07:50:13.9111233Z Entering 'third_party/FXdiv' 2025-09-07T07:50:13.9155022Z Entering 'third_party/NNPACK' 2025-09-07T07:50:13.9199831Z Entering 'third_party/NVTX' 2025-09-07T07:50:13.9244673Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T07:50:13.9288190Z Entering 'third_party/XNNPACK' 2025-09-07T07:50:13.9347445Z Entering 'third_party/aiter' 2025-09-07T07:50:13.9392098Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T07:50:13.9442810Z Entering 'third_party/benchmark' 2025-09-07T07:50:13.9487345Z Entering 'third_party/composable_kernel' 2025-09-07T07:50:13.9538884Z Entering 'third_party/cpp-httplib' 2025-09-07T07:50:13.9583961Z Entering 'third_party/cpuinfo' 2025-09-07T07:50:13.9628702Z Entering 'third_party/cudnn_frontend' 2025-09-07T07:50:13.9673739Z Entering 'third_party/cutlass' 2025-09-07T07:50:13.9727084Z Entering 'third_party/fbgemm' 2025-09-07T07:50:13.9775223Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T07:50:13.9820543Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T07:50:13.9869268Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T07:50:13.9910703Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T07:50:13.9963151Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T07:50:14.0006180Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T07:50:14.0047947Z Entering 'third_party/fbgemm/external/json' 2025-09-07T07:50:14.0093181Z Entering 'third_party/flash-attention' 2025-09-07T07:50:14.0137587Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T07:50:14.0185227Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T07:50:14.0236817Z Entering 'third_party/flatbuffers' 2025-09-07T07:50:14.0283357Z Entering 'third_party/fmt' 2025-09-07T07:50:14.0329427Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T07:50:14.0373977Z Entering 'third_party/gloo' 2025-09-07T07:50:14.0417748Z Entering 'third_party/googletest' 2025-09-07T07:50:14.0461454Z Entering 'third_party/ideep' 2025-09-07T07:50:14.0503989Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T07:50:14.0557502Z Entering 'third_party/ittapi' 2025-09-07T07:50:14.0601222Z Entering 'third_party/kineto' 2025-09-07T07:50:14.0645348Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T07:50:14.0689316Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T07:50:14.0732939Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T07:50:14.0773852Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T07:50:14.0815063Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T07:50:14.0856496Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T07:50:14.0898675Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T07:50:14.0941049Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T07:50:14.0983968Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T07:50:14.1025937Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T07:50:14.1069680Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T07:50:14.1111358Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T07:50:14.1154816Z Entering 'third_party/kleidiai' 2025-09-07T07:50:14.1201323Z Entering 'third_party/mimalloc' 2025-09-07T07:50:14.1248074Z Entering 'third_party/nlohmann' 2025-09-07T07:50:14.1296410Z Entering 'third_party/onnx' 2025-09-07T07:50:14.1354786Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T07:50:14.1402991Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T07:50:14.1449607Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T07:50:14.1491428Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T07:50:14.1532441Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T07:50:14.1575449Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T07:50:14.1617546Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T07:50:14.1658875Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T07:50:14.1700718Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T07:50:14.1740798Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T07:50:14.1784654Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T07:50:14.1829813Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T07:50:14.1893596Z Entering 'third_party/pocketfft' 2025-09-07T07:50:14.1941422Z Entering 'third_party/protobuf' 2025-09-07T07:50:14.1987623Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T07:50:14.2029061Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T07:50:14.2074712Z Entering 'third_party/psimd' 2025-09-07T07:50:14.2119276Z Entering 'third_party/pthreadpool' 2025-09-07T07:50:14.2163749Z Entering 'third_party/pybind11' 2025-09-07T07:50:14.2207752Z Entering 'third_party/python-peachpy' 2025-09-07T07:50:14.2251624Z Entering 'third_party/sleef' 2025-09-07T07:50:14.2296198Z Entering 'third_party/tensorpipe' 2025-09-07T07:50:14.2344597Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T07:50:14.2387239Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T07:50:14.2429512Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T07:50:14.2472921Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T07:50:14.2513604Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T07:50:14.2576841Z ##[endgroup] 2025-09-07T07:50:14.2621894Z [command]/usr/bin/git log -1 --format=%H 2025-09-07T07:50:14.2649572Z 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:14.2829291Z Prepare all required actions 2025-09-07T07:50:14.2829778Z Getting action download info 2025-09-07T07:50:14.4361567Z ##[group]Run ./.github/actions/setup-linux 2025-09-07T07:50:14.4361810Z env: 2025-09-07T07:50:14.4361969Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:14.4362169Z ##[endgroup] 2025-09-07T07:50:14.4414843Z ##[group]Run set -euo pipefail 2025-09-07T07:50:14.4415135Z set -euo pipefail 2025-09-07T07:50:14.4415376Z function get_ec2_metadata() { 2025-09-07T07:50:14.4415878Z  # Pulled from instance metadata endpoint for EC2 2025-09-07T07:50:14.4416351Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-09-07T07:50:14.4416771Z  category=$1 2025-09-07T07:50:14.4417040Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-09-07T07:50:14.4417381Z  runner_name_str=i-0b7d0f7dc0527ca9b-1003 2025-09-07T07:50:14.4417660Z  if [[ -f /.inarc ]]; then 2025-09-07T07:50:14.4417915Z  echo "ARC Runner, no info on ec2 metadata" 2025-09-07T07:50:14.4418185Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-09-07T07:50:14.4418516Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-09-07T07:50:14.4418820Z  else 2025-09-07T07:50:14.4419425Z  curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}" 2025-09-07T07:50:14.4420056Z  fi 2025-09-07T07:50:14.4420395Z } 2025-09-07T07:50:14.4420590Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-09-07T07:50:14.4420911Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-09-07T07:50:14.4421253Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-09-07T07:50:14.4421559Z echo "system info $(uname -a)" 2025-09-07T07:50:14.4436423Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:14.4436713Z env: 2025-09-07T07:50:14.4436884Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:14.4437076Z ##[endgroup] 2025-09-07T07:50:14.4475272Z ami-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:50:14.4480108Z instance-id: ARC Runner, no info on ec2 metadata 2025-09-07T07:50:14.4486790Z instance-type: ARC Runner, no info on ec2 metadata 2025-09-07T07:50:14.4498649Z system info Linux 5b251226417a 6.8.0-1017-aws #18~22.04.1-Ubuntu SMP Thu Oct 3 19:57:42 UTC 2024 x86_64 x86_64 x86_64 GNU/Linux 2025-09-07T07:50:14.4516683Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:50:14.4517384Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T07:50:14.4531181Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:14.4531478Z env: 2025-09-07T07:50:14.4531642Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:14.4531835Z ##[endgroup] 2025-09-07T07:50:14.4605429Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T07:50:14.4605653Z with: 2025-09-07T07:50:14.4605804Z shell: bash 2025-09-07T07:50:14.4605981Z timeout_minutes: 5 2025-09-07T07:50:14.4606168Z max_attempts: 3 2025-09-07T07:50:14.4606339Z retry_wait_seconds: 30 2025-09-07T07:50:14.4608250Z command: AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\") aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" # For LF Runners we need to make sure we also login to Meta's ECR docker registry too. META_AWS_ACCOUNT_ID=308535385114 if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" fi 2025-09-07T07:50:14.4609880Z polling_interval_seconds: 1 2025-09-07T07:50:14.4610085Z warning_on_retry: true 2025-09-07T07:50:14.4610478Z continue_on_error: false 2025-09-07T07:50:14.4610672Z env: 2025-09-07T07:50:14.4610833Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:14.4611024Z AWS_RETRY_MODE: standard 2025-09-07T07:50:14.4611211Z AWS_MAX_ATTEMPTS: 5 2025-09-07T07:50:14.4611410Z AWS_DEFAULT_REGION: us-east-1 2025-09-07T07:50:14.4611812Z ##[endgroup] 2025-09-07T07:50:16.0105204Z 2025-09-07T07:50:16.0105778Z WARNING! Your credentials are stored unencrypted in '/home/charlie/.docker/config.json'. 2025-09-07T07:50:16.0106299Z Configure a credential helper to remove this warning. See 2025-09-07T07:50:16.0106702Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:50:16.0106944Z 2025-09-07T07:50:16.0107041Z Login Succeeded 2025-09-07T07:50:16.5349982Z Command completed after 1 attempt(s). 2025-09-07T07:50:16.5423771Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:50:16.5424180Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:50:16.5424514Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T07:50:16.5439321Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:16.5439620Z env: 2025-09-07T07:50:16.5439789Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.5439999Z ##[endgroup] 2025-09-07T07:50:16.5532328Z ##[group]Run set +e 2025-09-07T07:50:16.5532550Z set +e 2025-09-07T07:50:16.5532720Z set -x 2025-09-07T07:50:16.5532879Z  2025-09-07T07:50:16.5533056Z PT_DOMAIN=download.pytorch.org 2025-09-07T07:50:16.5533486Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-09-07T07:50:16.5534031Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-09-07T07:50:16.5534583Z # one is returned at random 2025-09-07T07:50:16.5534892Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-09-07T07:50:16.5535166Z  2025-09-07T07:50:16.5535339Z if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:50:16.5535657Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-09-07T07:50:16.5536038Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-09-07T07:50:16.5536343Z  2025-09-07T07:50:16.5536511Z  if [ -z "${RESOLVED_IP}" ]; then 2025-09-07T07:50:16.5536799Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-09-07T07:50:16.5537061Z  exit 1 2025-09-07T07:50:16.5537243Z  fi 2025-09-07T07:50:16.5537389Z fi 2025-09-07T07:50:16.5537538Z  2025-09-07T07:50:16.5537724Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-09-07T07:50:16.5537991Z  # Clean up any old records first 2025-09-07T07:50:16.5538249Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-09-07T07:50:16.5538481Z fi 2025-09-07T07:50:16.5538629Z  2025-09-07T07:50:16.5538861Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-09-07T07:50:16.5539140Z cat /etc/hosts 2025-09-07T07:50:16.5553563Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:16.5553865Z env: 2025-09-07T07:50:16.5554055Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.5554260Z ##[endgroup] 2025-09-07T07:50:16.5585979Z + PT_DOMAIN=download.pytorch.org 2025-09-07T07:50:16.5594489Z ++ dig -4 +short download.pytorch.org 2025-09-07T07:50:16.5594734Z ++ tail -n1 2025-09-07T07:50:16.5788638Z + RESOLVED_IP=3.170.131.102 2025-09-07T07:50:16.5788901Z + '[' -z 3.170.131.102 ']' 2025-09-07T07:50:16.5789161Z + grep -r download.pytorch.org /etc/hosts 2025-09-07T07:50:16.5803777Z + echo '3.170.131.102 download.pytorch.org' 2025-09-07T07:50:16.5805284Z + sudo tee -a /etc/hosts 2025-09-07T07:50:16.5866269Z 3.170.131.102 download.pytorch.org 2025-09-07T07:50:16.5875825Z + cat /etc/hosts 2025-09-07T07:50:16.5883588Z 127.0.0.1 localhost 2025-09-07T07:50:16.5888167Z ::1 localhost ip6-localhost ip6-loopback 2025-09-07T07:50:16.5888467Z fe00:: ip6-localnet 2025-09-07T07:50:16.5888656Z ff00:: ip6-mcastprefix 2025-09-07T07:50:16.5888859Z ff02::1 ip6-allnodes 2025-09-07T07:50:16.5889053Z ff02::2 ip6-allrouters 2025-09-07T07:50:16.5889230Z 172.17.0.2 5b251226417a 2025-09-07T07:50:16.5889681Z 3.170.131.102 download.pytorch.org 2025-09-07T07:50:16.5906205Z ##[group]Run set +x 2025-09-07T07:50:16.5906417Z set +x 2025-09-07T07:50:16.5906577Z  2025-09-07T07:50:16.5906732Z max_attempts=30 2025-09-07T07:50:16.5906925Z delay=10 2025-09-07T07:50:16.5907087Z attempt=1 2025-09-07T07:50:16.5907249Z  2025-09-07T07:50:16.5907423Z for attempt in $(seq 1 $max_attempts); do 2025-09-07T07:50:16.5907937Z  echo "Attempt $attempt of $max_attempts: Checking if Docker daemon is running..." 2025-09-07T07:50:16.5908304Z  if docker info > /dev/null 2>&1; then 2025-09-07T07:50:16.5908612Z  echo "Docker is running. Proceeding with the next steps" 2025-09-07T07:50:16.5908892Z  exit 0 2025-09-07T07:50:16.5909069Z  else 2025-09-07T07:50:16.5909262Z  echo "Docker is not running yet." 2025-09-07T07:50:16.5909518Z  echo "Retrying in $delay seconds..." 2025-09-07T07:50:16.5909763Z  sleep $delay 2025-09-07T07:50:16.5909941Z  fi 2025-09-07T07:50:16.5910098Z done 2025-09-07T07:50:16.5910506Z echo "Reached maximum attempts to connect to Docker. Exiting." 2025-09-07T07:50:16.5910804Z exit 1 2025-09-07T07:50:16.5923813Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:16.5924102Z env: 2025-09-07T07:50:16.5924265Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.5924457Z ##[endgroup] 2025-09-07T07:50:16.5965788Z Attempt 1 of 30: Checking if Docker daemon is running... 2025-09-07T07:50:16.6418033Z Docker is running. Proceeding with the next steps 2025-09-07T07:50:16.6544677Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-09-07T07:50:16.6545065Z with: 2025-09-07T07:50:16.6545737Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6546501Z use-custom-docker-registry: true 2025-09-07T07:50:16.6546727Z docker-build-dir: .ci/docker 2025-09-07T07:50:16.6546951Z docker-build-script: ./build.sh 2025-09-07T07:50:16.6547163Z working-directory: . 2025-09-07T07:50:16.6547416Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:16.6547698Z force-push: false 2025-09-07T07:50:16.6547863Z env: 2025-09-07T07:50:16.6548013Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.6548199Z ##[endgroup] 2025-09-07T07:50:16.6564299Z ##[group]Run set -ex 2025-09-07T07:50:16.6564539Z set -ex 2025-09-07T07:50:16.6564704Z  2025-09-07T07:50:16.6565026Z # If the docker build directory or the build script doesn't exist, the action will 2025-09-07T07:50:16.6565504Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-09-07T07:50:16.6565913Z # job could then download the pre-built image as usual 2025-09-07T07:50:16.6566412Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-09-07T07:50:16.6566881Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6567128Z else 2025-09-07T07:50:16.6567316Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6567642Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6567932Z  2025-09-07T07:50:16.6568333Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-09-07T07:50:16.6568783Z  exit 0 2025-09-07T07:50:16.6568934Z fi 2025-09-07T07:50:16.6569080Z  2025-09-07T07:50:16.6569325Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-09-07T07:50:16.6569754Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-09-07T07:50:16.6570497Z  # use it as it is, but first let's extract the tag 2025-09-07T07:50:16.6570854Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-09-07T07:50:16.6571215Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6571557Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6571840Z else 2025-09-07T07:50:16.6572024Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-09-07T07:50:16.6572307Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-09-07T07:50:16.6572586Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-09-07T07:50:16.6572815Z  fi 2025-09-07T07:50:16.6573133Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-09-07T07:50:16.6573561Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6574025Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6574519Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6574816Z fi 2025-09-07T07:50:16.6618736Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:16.6619020Z env: 2025-09-07T07:50:16.6619181Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.6619369Z REPO_NAME: pytorch 2025-09-07T07:50:16.6620439Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6621179Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:50:16.6621389Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-09-07T07:50:16.6621652Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:16.6621948Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-09-07T07:50:16.6622149Z CUSTOM_TAG_PREFIX: 2025-09-07T07:50:16.6622317Z ##[endgroup] 2025-09-07T07:50:16.6653689Z + [[ -d .ci/docker ]] 2025-09-07T07:50:16.6653919Z + [[ -f .ci/docker/./build.sh ]] 2025-09-07T07:50:16.6654128Z + [[ true == \t\r\u\e ]] 2025-09-07T07:50:16.6654318Z + echo skip=false 2025-09-07T07:50:16.6655185Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 == *\3\0\8\5\3\5\3\8\5\1\1\4\.\d\k\r\.\e\c\r\.\u\s\-\e\a\s\t\-\1\.\a\m\a\z\o\n\a\w\s\.\c\o\m\/\p\y\t\o\r\c\h* ]] 2025-09-07T07:50:16.6662853Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6663757Z ++ awk -F '[:,]' '{print $2}' 2025-09-07T07:50:16.6677239Z + DOCKER_TAG=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6678227Z + echo docker-tag=pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6679529Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6700093Z ##[group]Run set +e 2025-09-07T07:50:16.6700479Z set +e 2025-09-07T07:50:16.6700656Z set -x 2025-09-07T07:50:16.6700816Z  2025-09-07T07:50:16.6700968Z login() { 2025-09-07T07:50:16.6701334Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:50:16.6701710Z } 2025-09-07T07:50:16.6701861Z  2025-09-07T07:50:16.6702007Z retry () { 2025-09-07T07:50:16.6702196Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:50:16.6702641Z } 2025-09-07T07:50:16.6702874Z  2025-09-07T07:50:16.6703043Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:50:16.6703253Z  2025-09-07T07:50:16.6703408Z START_TIME=$(date +%s) 2025-09-07T07:50:16.6703632Z # Wait up to 120 minutes 2025-09-07T07:50:16.6703893Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-09-07T07:50:16.6704245Z  # Check if image already exists, if it does then skip building it 2025-09-07T07:50:16.6704603Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-09-07T07:50:16.6704856Z  exit 0 2025-09-07T07:50:16.6705018Z  fi 2025-09-07T07:50:16.6705164Z  2025-09-07T07:50:16.6705436Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-09-07T07:50:16.6705905Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-09-07T07:50:16.6706368Z  # latter, it will wait for the Docker images to become available before continuing 2025-09-07T07:50:16.6706737Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-09-07T07:50:16.6707030Z  # It's a Docker build job, let's build the image 2025-09-07T07:50:16.6707280Z  break 2025-09-07T07:50:16.6707445Z  else 2025-09-07T07:50:16.6707687Z  # It's a regular build job, wait for the image to become available 2025-09-07T07:50:16.6707981Z  sleep 300 2025-09-07T07:50:16.6708159Z  fi 2025-09-07T07:50:16.6708312Z done 2025-09-07T07:50:16.6708461Z  2025-09-07T07:50:16.6708882Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-09-07T07:50:16.6709292Z # be empty. The default action would be to continue rebuild the image 2025-09-07T07:50:16.6709672Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-09-07T07:50:16.6709999Z  # if we're on the base branch then use the parent commit 2025-09-07T07:50:16.6710416Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-09-07T07:50:16.6710636Z else 2025-09-07T07:50:16.6710868Z  # otherwise we're on a PR, so use the most recent base commit 2025-09-07T07:50:16.6711208Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-09-07T07:50:16.6711473Z fi 2025-09-07T07:50:16.6711618Z  2025-09-07T07:50:16.6711786Z if [[ -z "${MERGE_BASE}" ]]; then 2025-09-07T07:50:16.6712044Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6712279Z  2025-09-07T07:50:16.6712614Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-09-07T07:50:16.6713002Z  exit 0 2025-09-07T07:50:16.6713162Z fi 2025-09-07T07:50:16.6713312Z  2025-09-07T07:50:16.6713533Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-09-07T07:50:16.6714011Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-09-07T07:50:16.6714416Z  exit 1 2025-09-07T07:50:16.6714576Z fi 2025-09-07T07:50:16.6714720Z  2025-09-07T07:50:16.6714980Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-09-07T07:50:16.6715443Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-09-07T07:50:16.6715856Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-09-07T07:50:16.6716337Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-09-07T07:50:16.6716882Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-09-07T07:50:16.6717199Z fi 2025-09-07T07:50:16.6717508Z  2025-09-07T07:50:16.6717692Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-09-07T07:50:16.6730948Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:16.6731244Z env: 2025-09-07T07:50:16.6731400Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:16.6731597Z DOCKER_BUILD_DIR: .ci/docker 2025-09-07T07:50:16.6731853Z BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T07:50:16.6732598Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6733582Z DOCKER_TAG: pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:16.6734151Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:16.6734421Z DOCKER_PUSH: 2025-09-07T07:50:16.6734589Z ##[endgroup] 2025-09-07T07:50:16.6762372Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:16.6762733Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:16.6766025Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:50:16.6767016Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:17.4750974Z 2025-09-07T07:50:17.4751354Z Login Succeeded 2025-09-07T07:50:17.4751824Z WARNING! Your credentials are stored unencrypted in '/home/charlie/.docker/config.json'. 2025-09-07T07:50:17.4752354Z Configure a credential helper to remove this warning. See 2025-09-07T07:50:17.4752740Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:50:17.4752957Z 2025-09-07T07:50:17.4782395Z ++ date +%s 2025-09-07T07:50:17.4792319Z + START_TIME=1757231417 2025-09-07T07:50:17.4796431Z ++ date +%s 2025-09-07T07:50:17.4806948Z + [[ 1757224217 -lt 1757231417 ]] 2025-09-07T07:50:17.4807792Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:17.9127848Z { 2025-09-07T07:50:17.9128068Z "schemaVersion": 2, 2025-09-07T07:50:17.9128428Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-09-07T07:50:17.9128791Z "config": { 2025-09-07T07:50:17.9129057Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-09-07T07:50:17.9129384Z "size": 31375, 2025-09-07T07:50:17.9129723Z "digest": "sha256:29d1d8a31b215537637bab7c99e18c255840b899cf7023e4e3cb5efa3270aef8" 2025-09-07T07:50:17.9130112Z }, 2025-09-07T07:50:17.9130608Z "layers": [ 2025-09-07T07:50:17.9130786Z { 2025-09-07T07:50:17.9131076Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9131420Z "size": 30448359, 2025-09-07T07:50:17.9131754Z "digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46" 2025-09-07T07:50:17.9132140Z }, 2025-09-07T07:50:17.9132291Z { 2025-09-07T07:50:17.9132565Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9132891Z "size": 1554, 2025-09-07T07:50:17.9133216Z "digest": "sha256:171dcef20c49de4bc9268f60e02f111b72c638b0f24c3c5636c5013029db6d30" 2025-09-07T07:50:17.9133587Z }, 2025-09-07T07:50:17.9133784Z { 2025-09-07T07:50:17.9134037Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9134363Z "size": 313297922, 2025-09-07T07:50:17.9134699Z "digest": "sha256:4c92b3f72f1df31fe9f487fc1c27fcf1ba475ffb43abd69056306d1247786e40" 2025-09-07T07:50:17.9135077Z }, 2025-09-07T07:50:17.9135218Z { 2025-09-07T07:50:17.9135473Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9135799Z "size": 792, 2025-09-07T07:50:17.9136114Z "digest": "sha256:744f9ba90a6582eb601b3c20409bb10d6dad635dd118c3975f79721f4c82747c" 2025-09-07T07:50:17.9136473Z }, 2025-09-07T07:50:17.9136618Z { 2025-09-07T07:50:17.9136868Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9137567Z "size": 106, 2025-09-07T07:50:17.9137887Z "digest": "sha256:d3c08322a3326e45849dd80264a047c4f42ba4a2419d35c919542e2890e23934" 2025-09-07T07:50:17.9138207Z }, 2025-09-07T07:50:17.9138340Z { 2025-09-07T07:50:17.9138565Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9138860Z "size": 704, 2025-09-07T07:50:17.9139136Z "digest": "sha256:ffd43b71f3ccf3ba563606231cb1d191eb9dd0052f422d54835e6af350525170" 2025-09-07T07:50:17.9139471Z }, 2025-09-07T07:50:17.9139606Z { 2025-09-07T07:50:17.9139849Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9140151Z "size": 1215, 2025-09-07T07:50:17.9140679Z "digest": "sha256:830692b57f6e2758398ec80c3b67a20441d12696b54ed14f2ecebf926198f7d6" 2025-09-07T07:50:17.9141017Z }, 2025-09-07T07:50:17.9141149Z { 2025-09-07T07:50:17.9141376Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9141678Z "size": 482, 2025-09-07T07:50:17.9141964Z "digest": "sha256:5bad36d184686719399be50830a98939d7dbda2313fb407df5915217483fc6a3" 2025-09-07T07:50:17.9142291Z }, 2025-09-07T07:50:17.9142418Z { 2025-09-07T07:50:17.9142651Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9143065Z "size": 110343614, 2025-09-07T07:50:17.9143380Z "digest": "sha256:0e34fdd9ac5c39eb0a9d2c2d258b26f42bb79d7dc0a22014bf201daa2e033eb4" 2025-09-07T07:50:17.9143718Z }, 2025-09-07T07:50:17.9143856Z { 2025-09-07T07:50:17.9144092Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9144386Z "size": 4786, 2025-09-07T07:50:17.9144905Z "digest": "sha256:3c868a62868ef54f82ac11be8dabe1b4365d000bacfe4c104e08022fc96dd767" 2025-09-07T07:50:17.9145254Z }, 2025-09-07T07:50:17.9145387Z { 2025-09-07T07:50:17.9145621Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9145912Z "size": 1710, 2025-09-07T07:50:17.9146222Z "digest": "sha256:62170a22dd571d55ffccac64c0be17f4006d2498cfbf7c6289325f0899cba005" 2025-09-07T07:50:17.9146556Z }, 2025-09-07T07:50:17.9146688Z { 2025-09-07T07:50:17.9146910Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9147206Z "size": 724, 2025-09-07T07:50:17.9147496Z "digest": "sha256:553c1d23b6c4dbd8ab136d0c3659460391ffa14cb9b43be9d7b2f47f90895697" 2025-09-07T07:50:17.9147822Z }, 2025-09-07T07:50:17.9147945Z { 2025-09-07T07:50:17.9148179Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 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"sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:50:17.9211669Z }, 2025-09-07T07:50:17.9211798Z { 2025-09-07T07:50:17.9212011Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9212289Z "size": 104, 2025-09-07T07:50:17.9212563Z "digest": "sha256:951e8ce838415c4257680a9d60d216f3750cbb18d243d9a21e2008cce7e589cf" 2025-09-07T07:50:17.9212875Z }, 2025-09-07T07:50:17.9212998Z { 2025-09-07T07:50:17.9213216Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9213499Z "size": 408, 2025-09-07T07:50:17.9213784Z "digest": "sha256:32340b97ae50ba7b2918ab40d6f4a8db875afee69318f484e4deb0a1e2ec4beb" 2025-09-07T07:50:17.9214098Z }, 2025-09-07T07:50:17.9214229Z { 2025-09-07T07:50:17.9214449Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9214731Z "size": 32, 2025-09-07T07:50:17.9215011Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:50:17.9215338Z }, 2025-09-07T07:50:17.9215472Z { 2025-09-07T07:50:17.9215690Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9215977Z "size": 109, 2025-09-07T07:50:17.9216262Z "digest": "sha256:5bbb04cd6b57ae13d7cf05ab9e9b4ed9752833ee2dba4eeaac47bde6022c4725" 2025-09-07T07:50:17.9216590Z }, 2025-09-07T07:50:17.9216728Z { 2025-09-07T07:50:17.9216946Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9217238Z "size": 1897, 2025-09-07T07:50:17.9217528Z "digest": "sha256:d8c4b845cfc7ca7cc0604f472bf6da8b1f1d4e98dff3c76e1985a7013a5b9e3f" 2025-09-07T07:50:17.9217856Z }, 2025-09-07T07:50:17.9217980Z { 2025-09-07T07:50:17.9218199Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9218485Z "size": 243440375, 2025-09-07T07:50:17.9218773Z "digest": "sha256:b35c180f4d8ddc2396eac4a6b893f438481a8163ceb0b88f203488bc5f2a8ba4" 2025-09-07T07:50:17.9219237Z }, 2025-09-07T07:50:17.9219364Z { 2025-09-07T07:50:17.9219588Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9219875Z "size": 106, 2025-09-07T07:50:17.9220142Z "digest": "sha256:5f967b3c303a99e609441551f7c8988cca4fd464c0c3127506bff8509583091b" 2025-09-07T07:50:17.9220607Z }, 2025-09-07T07:50:17.9220733Z { 2025-09-07T07:50:17.9220955Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9221231Z "size": 166, 2025-09-07T07:50:17.9221590Z "digest": "sha256:04770904f012e5584f1c19a0bc92d9863baaebf08bf75b4a9981f2b7795c8953" 2025-09-07T07:50:17.9221912Z }, 2025-09-07T07:50:17.9222049Z { 2025-09-07T07:50:17.9222356Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9222641Z "size": 7943, 2025-09-07T07:50:17.9223105Z "digest": "sha256:73373941fb321b4cb4a171b1423a68a4c7fedada3a1498868d7efe93cb03170e" 2025-09-07T07:50:17.9223453Z }, 2025-09-07T07:50:17.9223582Z { 2025-09-07T07:50:17.9223805Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9224087Z "size": 8072, 2025-09-07T07:50:17.9224362Z "digest": "sha256:9572e6cd907bfa4888456dbccc6e22146a0044374585f3fa0a8ced19b831ed62" 2025-09-07T07:50:17.9224679Z }, 2025-09-07T07:50:17.9224808Z { 2025-09-07T07:50:17.9225028Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9225311Z "size": 304, 2025-09-07T07:50:17.9225582Z "digest": "sha256:64a544aba233551e38898f138dd6ba3161ccdb9554e0ffb5b9d8f0f7fe4a7fa8" 2025-09-07T07:50:17.9225911Z }, 2025-09-07T07:50:17.9226195Z { 2025-09-07T07:50:17.9226423Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9226700Z "size": 13362696, 2025-09-07T07:50:17.9226985Z "digest": "sha256:7e35418a24997de5428763c93826679486760a1a9563209ae64de66ba45f99c1" 2025-09-07T07:50:17.9227298Z }, 2025-09-07T07:50:17.9227437Z { 2025-09-07T07:50:17.9227652Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9227938Z "size": 108, 2025-09-07T07:50:17.9228218Z "digest": "sha256:2ed8e82748d4a1131f41d9e41322f47a6ffef67a5a2b7bf5392237db5c035c61" 2025-09-07T07:50:17.9228539Z }, 2025-09-07T07:50:17.9228663Z { 2025-09-07T07:50:17.9228882Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9229164Z "size": 54145663, 2025-09-07T07:50:17.9229453Z "digest": "sha256:c988fbcccd708fb158a81c429d32e1060a7e40924fc3c987c629fa69d9484717" 2025-09-07T07:50:17.9229780Z }, 2025-09-07T07:50:17.9229911Z { 2025-09-07T07:50:17.9230133Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-09-07T07:50:17.9230578Z "size": 32, 2025-09-07T07:50:17.9230851Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-09-07T07:50:17.9231176Z } 2025-09-07T07:50:17.9231304Z ] 2025-09-07T07:50:17.9231439Z } 2025-09-07T07:50:17.9254054Z ##[group]Run set -eux 2025-09-07T07:50:17.9254264Z set -eux 2025-09-07T07:50:17.9254576Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-09-07T07:50:17.9255392Z aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token | jq --raw-output '.SecretString' | jq -r .docker_hub_readonly_token | docker login --username pytorchbot --password-stdin || true 2025-09-07T07:50:17.9270779Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:17.9271063Z env: 2025-09-07T07:50:17.9271228Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:17.9271417Z ##[endgroup] 2025-09-07T07:50:17.9308432Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-09-07T07:50:17.9309458Z + jq --raw-output .SecretString 2025-09-07T07:50:17.9311311Z + jq -r .docker_hub_readonly_token 2025-09-07T07:50:17.9312635Z + docker login --username pytorchbot --password-stdin 2025-09-07T07:50:18.4969589Z 2025-09-07T07:50:18.4971820Z An error occurred (AccessDeniedException) when calling the GetSecretValue operation: User: arn:aws:sts::308535385114:assumed-role/gh-ci-github-action-runners-runner-role/i-0b7d0f7dc0527ca9b is not authorized to perform: secretsmanager:GetSecretValue on resource: docker_hub_readonly_token because no identity-based policy allows the secretsmanager:GetSecretValue action 2025-09-07T07:50:18.5625458Z Error: Cannot perform an interactive login from a non TTY device 2025-09-07T07:50:18.5647469Z + true 2025-09-07T07:50:18.5722600Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:50:18.5722916Z tag=${ECR_DOCKER_IMAGE##*:} 2025-09-07T07:50:18.5723211Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-09-07T07:50:18.5737934Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:18.5738219Z env: 2025-09-07T07:50:18.5738392Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:18.5739076Z ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.5739784Z ##[endgroup] 2025-09-07T07:50:18.5774248Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.5846252Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-09-07T07:50:18.5846614Z with: 2025-09-07T07:50:18.5847281Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.5848052Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:18.5848330Z env: 2025-09-07T07:50:18.5848487Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:18.5848682Z ##[endgroup] 2025-09-07T07:50:18.5861387Z ##[group]Run set -x 2025-09-07T07:50:18.5861588Z set -x 2025-09-07T07:50:18.5861774Z set +e 2025-09-07T07:50:18.5861927Z  2025-09-07T07:50:18.5862076Z login() { 2025-09-07T07:50:18.5862430Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-09-07T07:50:18.5862876Z } 2025-09-07T07:50:18.5863028Z  2025-09-07T07:50:18.5863196Z retry () { 2025-09-07T07:50:18.5863400Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-09-07T07:50:18.5863628Z } 2025-09-07T07:50:18.5863779Z  2025-09-07T07:50:18.5863948Z retry login "${DOCKER_REGISTRY}" 2025-09-07T07:50:18.5864168Z  2025-09-07T07:50:18.5864508Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-09-07T07:50:18.5865088Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-09-07T07:50:18.5865360Z  2025-09-07T07:50:18.5865510Z set -e 2025-09-07T07:50:18.5865759Z # ignore output since only exit code is used for conditional 2025-09-07T07:50:18.5866113Z # only pull docker image if it's not available locally 2025-09-07T07:50:18.5866499Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-09-07T07:50:18.5866862Z  retry docker pull "${DOCKER_IMAGE}" 2025-09-07T07:50:18.5867093Z fi 2025-09-07T07:50:18.5881530Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T07:50:18.5881813Z env: 2025-09-07T07:50:18.5881976Z GIT_DEFAULT_BRANCH: main 2025-09-07T07:50:18.5882677Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:18.5883452Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:18.5883725Z ##[endgroup] 2025-09-07T07:50:18.5916914Z + set +e 2025-09-07T07:50:18.5917456Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:18.5917827Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:18.5921284Z + aws ecr get-login-password --region us-east-1 2025-09-07T07:50:18.5922652Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-09-07T07:50:19.3994610Z 2025-09-07T07:50:19.3995189Z WARNING! Your credentials are stored unencrypted in '/home/charlie/.docker/config.json'. 2025-09-07T07:50:19.3995740Z Configure a credential helper to remove this warning. See 2025-09-07T07:50:19.3996127Z https://docs.docker.com/go/credential-store/ 2025-09-07T07:50:19.3996357Z 2025-09-07T07:50:19.3996439Z Login Succeeded 2025-09-07T07:50:19.4034535Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:19.4035874Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-09-07T07:50:19.8016534Z + IMAGE_SIZE=36183.606596946716 2025-09-07T07:50:19.8016905Z + echo 'Compressed size of image in MB: 36183.606596946716' 2025-09-07T07:50:19.8017202Z + set -e 2025-09-07T07:50:19.9520852Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:19.9522499Z Compressed size of image in MB: 36183.606596946716 2025-09-07T07:50:19.9523944Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:19.9526097Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T07:50:20.4546567Z pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image 2025-09-07T07:50:20.4547444Z e6fdc8487bfe: Pulling fs layer 2025-09-07T07:50:20.4547766Z 171dcef20c49: Pulling fs layer 2025-09-07T07:50:20.4548060Z 4c92b3f72f1d: Pulling fs layer 2025-09-07T07:50:20.4548305Z 744f9ba90a65: Pulling fs layer 2025-09-07T07:50:20.4548563Z d3c08322a332: Pulling fs layer 2025-09-07T07:50:20.4548802Z ffd43b71f3cc: Pulling fs layer 2025-09-07T07:50:20.4549035Z 830692b57f6e: Pulling fs layer 2025-09-07T07:50:20.4549269Z 5bad36d18468: Pulling fs layer 2025-09-07T07:50:20.4549510Z 0e34fdd9ac5c: Pulling fs layer 2025-09-07T07:50:20.4549732Z ffd43b71f3cc: Waiting 2025-09-07T07:50:20.4549945Z 3c868a62868e: Pulling fs layer 2025-09-07T07:50:20.4550174Z 744f9ba90a65: Waiting 2025-09-07T07:50:20.4550803Z d3c08322a332: Waiting 2025-09-07T07:50:20.4551000Z 62170a22dd57: Pulling fs layer 2025-09-07T07:50:20.4551241Z 553c1d23b6c4: Pulling fs layer 2025-09-07T07:50:20.4551471Z 9408d557a804: Pulling fs layer 2025-09-07T07:50:20.4551704Z df607cfc7c07: Pulling fs layer 2025-09-07T07:50:20.4551962Z 0e34fdd9ac5c: Waiting 2025-09-07T07:50:20.4552153Z 830692b57f6e: Waiting 2025-09-07T07:50:20.4552339Z 3c868a62868e: Waiting 2025-09-07T07:50:20.4552536Z 4f4fb700ef54: Pulling fs layer 2025-09-07T07:50:20.4552750Z 5bad36d18468: Waiting 2025-09-07T07:50:20.4552940Z 62170a22dd57: Waiting 2025-09-07T07:50:20.4553147Z 40a8e39faeda: Pulling fs layer 2025-09-07T07:50:20.4553365Z 9408d557a804: Waiting 2025-09-07T07:50:20.4553549Z df607cfc7c07: Waiting 2025-09-07T07:50:20.4553750Z d895771c9fac: Pulling fs layer 2025-09-07T07:50:20.4553971Z 40a8e39faeda: Waiting 2025-09-07T07:50:20.4554172Z c4ee04f39d49: Pulling fs layer 2025-09-07T07:50:20.4554386Z 553c1d23b6c4: Waiting 2025-09-07T07:50:20.4554581Z 4f4fb700ef54: Waiting 2025-09-07T07:50:20.4554788Z 3690c9826e48: Pulling fs layer 2025-09-07T07:50:20.4555028Z 57cbc5013733: Pulling fs layer 2025-09-07T07:50:20.4555251Z f5f4b06b58bb: Pulling fs layer 2025-09-07T07:50:20.4555471Z d895771c9fac: Waiting 2025-09-07T07:50:20.4556032Z f59713ce4bf4: Pulling fs layer 2025-09-07T07:50:20.4556266Z fe0486521517: Pulling fs layer 2025-09-07T07:50:20.4556491Z 8c21cc3715a2: Pulling fs layer 2025-09-07T07:50:20.4556715Z c4ee04f39d49: Waiting 2025-09-07T07:50:20.4556909Z 3690c9826e48: Waiting 2025-09-07T07:50:20.4557103Z f5f4b06b58bb: Waiting 2025-09-07T07:50:20.4557296Z f59713ce4bf4: Waiting 2025-09-07T07:50:20.4557499Z d37c58456a6a: Pulling fs layer 2025-09-07T07:50:20.4557719Z 57cbc5013733: Waiting 2025-09-07T07:50:20.4557913Z fe0486521517: Waiting 2025-09-07T07:50:20.4558111Z d042f63abc13: Pulling fs layer 2025-09-07T07:50:20.4558331Z 8c21cc3715a2: Waiting 2025-09-07T07:50:20.4558528Z d37c58456a6a: Waiting 2025-09-07T07:50:20.4558727Z 621284a9c05a: Pulling fs layer 2025-09-07T07:50:20.4558938Z 85f605d2dd3a: Pulling fs layer 2025-09-07T07:50:20.4559130Z 381b5539e598: Pulling fs layer 2025-09-07T07:50:20.4559325Z a487c0c80029: Pulling fs layer 2025-09-07T07:50:20.4559508Z d042f63abc13: Waiting 2025-09-07T07:50:20.4559677Z 48bcb81e2566: Pulling fs layer 2025-09-07T07:50:20.4559862Z 85f605d2dd3a: Waiting 2025-09-07T07:50:20.4560023Z a487c0c80029: Waiting 2025-09-07T07:50:20.4560182Z 381b5539e598: Waiting 2025-09-07T07:50:20.4560519Z 48bcb81e2566: Waiting 2025-09-07T07:50:20.4560685Z e261928c0043: Pulling fs layer 2025-09-07T07:50:20.4560876Z 0fea55428091: Pulling fs layer 2025-09-07T07:50:20.4561318Z b4291bccbb84: Pulling fs layer 2025-09-07T07:50:20.4561515Z ddc91b09189a: Pulling fs layer 2025-09-07T07:50:20.4561717Z 7540c7428627: Pulling fs layer 2025-09-07T07:50:20.4561902Z 003c4e2598fb: Pulling fs layer 2025-09-07T07:50:20.4562083Z 5687149362ae: Pulling fs layer 2025-09-07T07:50:20.4562286Z ddc91b09189a: Waiting 2025-09-07T07:50:20.4562447Z e261928c0043: Waiting 2025-09-07T07:50:20.4562603Z 003c4e2598fb: Waiting 2025-09-07T07:50:20.4562773Z cdd2cf54eb2a: Pulling fs layer 2025-09-07T07:50:20.4562958Z 7540c7428627: Waiting 2025-09-07T07:50:20.4563135Z d3ad4df1ba3a: Pulling fs layer 2025-09-07T07:50:20.4563352Z b4291bccbb84: Waiting 2025-09-07T07:50:20.4563506Z 5687149362ae: Waiting 2025-09-07T07:50:20.4563671Z 3c9055753b4c: Pulling fs layer 2025-09-07T07:50:20.4563866Z 31cf8d0bd21c: Pulling fs layer 2025-09-07T07:50:20.4564056Z d3ad4df1ba3a: Waiting 2025-09-07T07:50:20.4564219Z 6623ea814971: Pulling fs layer 2025-09-07T07:50:20.4564406Z 11696c3aa380: Pulling fs layer 2025-09-07T07:50:20.4564600Z ef4d544e35ca: Pulling fs layer 2025-09-07T07:50:20.4564783Z 5c5108865e5e: Pulling fs layer 2025-09-07T07:50:20.4564953Z 3c9055753b4c: Waiting 2025-09-07T07:50:20.4565120Z 9e97578e9edf: Pulling fs layer 2025-09-07T07:50:20.4565300Z 6623ea814971: Waiting 2025-09-07T07:50:20.4565467Z da5a91b54cb5: Pulling fs layer 2025-09-07T07:50:20.4565640Z 5c5108865e5e: Waiting 2025-09-07T07:50:20.4565794Z 11696c3aa380: Waiting 2025-09-07T07:50:20.4565951Z ef4d544e35ca: Waiting 2025-09-07T07:50:20.4566110Z 1e93be219e89: Pulling fs layer 2025-09-07T07:50:20.4566290Z 9e97578e9edf: Waiting 2025-09-07T07:50:20.4566467Z 136825afebb5: Pulling fs layer 2025-09-07T07:50:20.4566682Z 22b39805302d: Pulling fs layer 2025-09-07T07:50:20.4566874Z d12add675e35: Pulling fs layer 2025-09-07T07:50:20.4567064Z bc127046d33a: Pulling fs layer 2025-09-07T07:50:20.4567246Z d12add675e35: Waiting 2025-09-07T07:50:20.4567418Z 951e8ce83841: Pulling fs layer 2025-09-07T07:50:20.4567594Z 136825afebb5: Waiting 2025-09-07T07:50:20.4567759Z 1e93be219e89: Waiting 2025-09-07T07:50:20.4567925Z bc127046d33a: Waiting 2025-09-07T07:50:20.4568091Z 32340b97ae50: Pulling fs layer 2025-09-07T07:50:20.4568265Z 22b39805302d: Waiting 2025-09-07T07:50:20.4568435Z 5bbb04cd6b57: Pulling fs layer 2025-09-07T07:50:20.4568630Z d8c4b845cfc7: Pulling fs layer 2025-09-07T07:50:20.4568820Z b35c180f4d8d: Pulling fs layer 2025-09-07T07:50:20.4569005Z 5f967b3c303a: Pulling fs layer 2025-09-07T07:50:20.4569194Z 04770904f012: Pulling fs layer 2025-09-07T07:50:20.4569380Z 73373941fb32: Pulling fs layer 2025-09-07T07:50:20.4569562Z 5f967b3c303a: Waiting 2025-09-07T07:50:20.4569711Z 04770904f012: Waiting 2025-09-07T07:50:20.4585798Z b35c180f4d8d: Waiting 2025-09-07T07:50:20.4585967Z d8c4b845cfc7: Waiting 2025-09-07T07:50:20.4586133Z 5bbb04cd6b57: Waiting 2025-09-07T07:50:20.4586303Z 9572e6cd907b: Pulling fs layer 2025-09-07T07:50:20.4586500Z 64a544aba233: Pulling fs layer 2025-09-07T07:50:20.4586685Z 951e8ce83841: Waiting 2025-09-07T07:50:20.4586857Z 7e35418a2499: Pulling fs layer 2025-09-07T07:50:20.4587034Z 9572e6cd907b: Waiting 2025-09-07T07:50:20.4587202Z 2ed8e82748d4: Pulling fs layer 2025-09-07T07:50:20.4587401Z c988fbcccd70: Pulling fs layer 2025-09-07T07:50:20.4587587Z 32340b97ae50: Waiting 2025-09-07T07:50:20.4587741Z 2ed8e82748d4: Waiting 2025-09-07T07:50:20.4587908Z c988fbcccd70: Waiting 2025-09-07T07:50:20.5968037Z 171dcef20c49: Verifying Checksum 2025-09-07T07:50:20.5968471Z 171dcef20c49: Download complete 2025-09-07T07:50:20.7515866Z 744f9ba90a65: Verifying Checksum 2025-09-07T07:50:20.7516131Z 744f9ba90a65: Download complete 2025-09-07T07:50:20.8746749Z e6fdc8487bfe: Verifying Checksum 2025-09-07T07:50:20.8747043Z e6fdc8487bfe: Download complete 2025-09-07T07:50:20.8926756Z d3c08322a332: Verifying Checksum 2025-09-07T07:50:20.8927029Z d3c08322a332: Download complete 2025-09-07T07:50:21.0293260Z ffd43b71f3cc: Verifying Checksum 2025-09-07T07:50:21.0293627Z ffd43b71f3cc: Download complete 2025-09-07T07:50:21.0596398Z 830692b57f6e: Verifying Checksum 2025-09-07T07:50:21.0596981Z 830692b57f6e: Download complete 2025-09-07T07:50:21.1803037Z 5bad36d18468: Verifying Checksum 2025-09-07T07:50:21.1803558Z 5bad36d18468: Download complete 2025-09-07T07:50:21.3579776Z 3c868a62868e: Verifying Checksum 2025-09-07T07:50:21.3580106Z 3c868a62868e: Download complete 2025-09-07T07:50:21.5160083Z 62170a22dd57: Verifying Checksum 2025-09-07T07:50:21.5160688Z 62170a22dd57: Download complete 2025-09-07T07:50:21.6313444Z e6fdc8487bfe: Pull complete 2025-09-07T07:50:21.6735863Z 171dcef20c49: Pull complete 2025-09-07T07:50:21.6738578Z 553c1d23b6c4: Verifying Checksum 2025-09-07T07:50:21.6738994Z 553c1d23b6c4: Download complete 2025-09-07T07:50:21.8416530Z 9408d557a804: Verifying Checksum 2025-09-07T07:50:21.8416853Z 9408d557a804: Download complete 2025-09-07T07:50:22.2965144Z 0e34fdd9ac5c: Verifying Checksum 2025-09-07T07:50:22.2965512Z 0e34fdd9ac5c: Download complete 2025-09-07T07:50:22.4938888Z 4f4fb700ef54: Verifying Checksum 2025-09-07T07:50:22.4939233Z 4f4fb700ef54: Download complete 2025-09-07T07:50:22.6513752Z 40a8e39faeda: Verifying Checksum 2025-09-07T07:50:22.6514062Z 40a8e39faeda: Download complete 2025-09-07T07:50:23.3131845Z d895771c9fac: Verifying Checksum 2025-09-07T07:50:23.3132186Z d895771c9fac: Download complete 2025-09-07T07:50:23.4761275Z c4ee04f39d49: Download complete 2025-09-07T07:50:23.7102083Z 4c92b3f72f1d: Verifying Checksum 2025-09-07T07:50:23.7102495Z 4c92b3f72f1d: Download complete 2025-09-07T07:50:23.7313746Z 3690c9826e48: Verifying Checksum 2025-09-07T07:50:23.7314024Z 3690c9826e48: Download complete 2025-09-07T07:50:23.8672531Z 57cbc5013733: Verifying Checksum 2025-09-07T07:50:23.8672866Z 57cbc5013733: Download complete 2025-09-07T07:50:23.8888835Z f5f4b06b58bb: Download complete 2025-09-07T07:50:24.0183995Z f59713ce4bf4: Verifying Checksum 2025-09-07T07:50:24.0184374Z f59713ce4bf4: Download complete 2025-09-07T07:50:24.0257344Z fe0486521517: Download complete 2025-09-07T07:50:24.1667182Z d37c58456a6a: Verifying Checksum 2025-09-07T07:50:24.1667589Z d37c58456a6a: Download complete 2025-09-07T07:50:24.6564843Z d042f63abc13: Verifying Checksum 2025-09-07T07:50:24.6565192Z d042f63abc13: Download complete 2025-09-07T07:50:24.8297798Z 621284a9c05a: Verifying Checksum 2025-09-07T07:50:24.8298163Z 621284a9c05a: Download complete 2025-09-07T07:50:24.9826955Z 85f605d2dd3a: Verifying Checksum 2025-09-07T07:50:24.9827398Z 85f605d2dd3a: Download complete 2025-09-07T07:50:29.8484311Z 381b5539e598: Download complete 2025-09-07T07:50:30.1419966Z a487c0c80029: Verifying Checksum 2025-09-07T07:50:30.1420821Z a487c0c80029: Download complete 2025-09-07T07:50:30.2898154Z 48bcb81e2566: Verifying Checksum 2025-09-07T07:50:30.3150660Z 48bcb81e2566: Download complete 2025-09-07T07:50:30.4594338Z e261928c0043: Verifying Checksum 2025-09-07T07:50:30.4594655Z e261928c0043: Download complete 2025-09-07T07:50:30.6651611Z 0fea55428091: Verifying Checksum 2025-09-07T07:50:30.6651908Z 0fea55428091: Download complete 2025-09-07T07:50:31.0461666Z b4291bccbb84: Verifying Checksum 2025-09-07T07:50:31.0461967Z b4291bccbb84: Download complete 2025-09-07T07:50:31.3832704Z ddc91b09189a: Verifying Checksum 2025-09-07T07:50:31.3833018Z ddc91b09189a: Download complete 2025-09-07T07:50:31.5285344Z 7540c7428627: Download complete 2025-09-07T07:50:31.7875911Z 003c4e2598fb: Verifying Checksum 2025-09-07T07:50:31.7876359Z 003c4e2598fb: Download complete 2025-09-07T07:50:31.9476476Z 5687149362ae: Verifying Checksum 2025-09-07T07:50:31.9476784Z 5687149362ae: Download complete 2025-09-07T07:50:32.1529370Z cdd2cf54eb2a: Verifying Checksum 2025-09-07T07:50:32.1529861Z cdd2cf54eb2a: Download complete 2025-09-07T07:50:36.8287557Z 4c92b3f72f1d: Pull complete 2025-09-07T07:50:40.6251491Z 744f9ba90a65: Pull complete 2025-09-07T07:50:46.1021713Z d3c08322a332: Pull complete 2025-09-07T07:50:51.3141105Z ffd43b71f3cc: Pull complete 2025-09-07T07:50:54.8129465Z df607cfc7c07: Verifying Checksum 2025-09-07T07:50:54.8129831Z df607cfc7c07: Download complete 2025-09-07T07:50:55.2134645Z 3c9055753b4c: Verifying Checksum 2025-09-07T07:50:55.2135215Z 3c9055753b4c: Download complete 2025-09-07T07:50:57.0698925Z 830692b57f6e: Pull complete 2025-09-07T07:50:58.7379811Z 5bad36d18468: Pull complete 2025-09-07T07:51:06.4449452Z 31cf8d0bd21c: Verifying Checksum 2025-09-07T07:51:06.4449826Z 31cf8d0bd21c: Download complete 2025-09-07T07:51:08.4009315Z 0e34fdd9ac5c: Pull complete 2025-09-07T07:51:11.5579957Z 3c868a62868e: Pull complete 2025-09-07T07:51:14.4457936Z 62170a22dd57: Pull complete 2025-09-07T07:51:16.1356649Z 553c1d23b6c4: Pull complete 2025-09-07T07:51:17.0040149Z 9408d557a804: Pull complete 2025-09-07T07:51:42.8922791Z 8c21cc3715a2: Verifying Checksum 2025-09-07T07:51:42.8923294Z 8c21cc3715a2: Download complete 2025-09-07T07:51:43.0578864Z 11696c3aa380: Download complete 2025-09-07T07:51:43.4980141Z ef4d544e35ca: Verifying Checksum 2025-09-07T07:51:43.4981481Z ef4d544e35ca: Download complete 2025-09-07T07:51:43.6375059Z 5c5108865e5e: Download complete 2025-09-07T07:51:43.7908644Z 9e97578e9edf: Verifying Checksum 2025-09-07T07:51:43.7909135Z 9e97578e9edf: Download complete 2025-09-07T07:51:43.9485804Z da5a91b54cb5: Download complete 2025-09-07T07:51:44.1160086Z 1e93be219e89: Download complete 2025-09-07T07:51:44.2659866Z 136825afebb5: Verifying Checksum 2025-09-07T07:51:44.2660199Z 136825afebb5: Download complete 2025-09-07T07:51:44.4356876Z 22b39805302d: Verifying Checksum 2025-09-07T07:51:44.4357250Z 22b39805302d: Download complete 2025-09-07T07:51:44.5968216Z d12add675e35: Download complete 2025-09-07T07:51:45.1887255Z bc127046d33a: Verifying Checksum 2025-09-07T07:51:45.1887728Z bc127046d33a: Download complete 2025-09-07T07:51:45.3517327Z 951e8ce83841: Download complete 2025-09-07T07:51:45.4949752Z 32340b97ae50: Verifying Checksum 2025-09-07T07:51:45.4961055Z 32340b97ae50: Download complete 2025-09-07T07:51:45.6316796Z 5bbb04cd6b57: Verifying Checksum 2025-09-07T07:51:45.6317138Z 5bbb04cd6b57: Download complete 2025-09-07T07:51:45.7856955Z d8c4b845cfc7: Download complete 2025-09-07T07:51:48.3650554Z b35c180f4d8d: Verifying Checksum 2025-09-07T07:51:48.3651060Z b35c180f4d8d: Download complete 2025-09-07T07:51:48.4995934Z 5f967b3c303a: Download complete 2025-09-07T07:51:48.6509726Z 04770904f012: Verifying Checksum 2025-09-07T07:51:48.6510053Z 04770904f012: Download complete 2025-09-07T07:51:49.2768171Z 73373941fb32: Verifying Checksum 2025-09-07T07:51:49.2768999Z 73373941fb32: Download complete 2025-09-07T07:51:49.4271579Z 9572e6cd907b: Verifying Checksum 2025-09-07T07:51:49.4271877Z 9572e6cd907b: Download complete 2025-09-07T07:51:49.5800071Z 64a544aba233: Download complete 2025-09-07T07:51:49.8508602Z 7e35418a2499: Verifying Checksum 2025-09-07T07:51:49.8508918Z 7e35418a2499: Download complete 2025-09-07T07:51:50.0164814Z 2ed8e82748d4: Verifying Checksum 2025-09-07T07:51:50.0165245Z 2ed8e82748d4: Download complete 2025-09-07T07:51:51.0490015Z c988fbcccd70: Verifying Checksum 2025-09-07T07:51:51.0490552Z c988fbcccd70: Download complete 2025-09-07T07:52:11.9635814Z 6623ea814971: Verifying Checksum 2025-09-07T07:52:11.9636201Z 6623ea814971: Download complete 2025-09-07T07:52:13.1430003Z df607cfc7c07: Pull complete 2025-09-07T07:52:17.8333408Z 4f4fb700ef54: Pull complete 2025-09-07T07:52:23.0433779Z 40a8e39faeda: Pull complete 2025-09-07T07:52:29.5446401Z d895771c9fac: Pull complete 2025-09-07T07:52:35.0751282Z c4ee04f39d49: Pull complete 2025-09-07T07:52:39.2554099Z 3690c9826e48: Pull complete 2025-09-07T07:52:44.3555879Z 57cbc5013733: Pull complete 2025-09-07T07:52:49.6432665Z f5f4b06b58bb: Pull complete 2025-09-07T07:52:53.0486905Z f59713ce4bf4: Pull complete 2025-09-07T07:52:57.6108366Z fe0486521517: Pull complete 2025-09-07T07:55:22.6214667Z d3ad4df1ba3a: Verifying Checksum 2025-09-07T07:55:22.6215232Z d3ad4df1ba3a: Download complete 2025-09-07T07:58:36.4118960Z 8c21cc3715a2: Pull complete 2025-09-07T07:58:44.2710707Z d37c58456a6a: Pull complete 2025-09-07T07:58:52.2092008Z d042f63abc13: Pull complete 2025-09-07T07:59:01.1766912Z 621284a9c05a: Pull complete 2025-09-07T07:59:09.1151568Z 85f605d2dd3a: Pull complete 2025-09-07T07:59:28.5395906Z 381b5539e598: Pull complete 2025-09-07T07:59:35.4078911Z a487c0c80029: Pull complete 2025-09-07T07:59:46.2025383Z 48bcb81e2566: Pull complete 2025-09-07T08:00:01.4826676Z e261928c0043: Pull complete 2025-09-07T08:00:06.6664207Z 0fea55428091: Pull complete 2025-09-07T08:00:12.6636351Z b4291bccbb84: Pull complete 2025-09-07T08:00:17.6497138Z ddc91b09189a: Pull complete 2025-09-07T08:00:21.6605213Z 7540c7428627: Pull complete 2025-09-07T08:00:30.0241730Z 003c4e2598fb: Pull complete 2025-09-07T08:00:34.6541151Z 5687149362ae: Pull complete 2025-09-07T08:00:38.4136828Z cdd2cf54eb2a: Pull complete 2025-09-07T08:11:21.5412430Z d3ad4df1ba3a: Pull complete 2025-09-07T08:11:28.7255122Z 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2025-09-07T08:14:30.0207833Z 5f967b3c303a: Pull complete 2025-09-07T08:14:32.2281522Z 04770904f012: Pull complete 2025-09-07T08:14:35.3974788Z 73373941fb32: Pull complete 2025-09-07T08:14:39.5091156Z 9572e6cd907b: Pull complete 2025-09-07T08:14:43.9544225Z 64a544aba233: Pull complete 2025-09-07T08:14:51.6985712Z 7e35418a2499: Pull complete 2025-09-07T08:14:58.0582701Z 2ed8e82748d4: Pull complete 2025-09-07T08:15:06.0277897Z c988fbcccd70: Pull complete 2025-09-07T08:15:18.0391901Z Digest: sha256:f30843ff9ea9e117a2c8e6d207e85c9e77dfe682f1dfcdfea5b94178d1bf00b3 2025-09-07T08:15:18.5085814Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:15:18.5914696Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:15:18.7958476Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:15:18.7959560Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-09-07T08:15:18.7974492Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:15:18.7974783Z env: 2025-09-07T08:15:18.7974945Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:18.7975140Z ##[endgroup] 2025-09-07T08:15:19.2058578Z ##[group]Run echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:15:19.2059200Z echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}" 2025-09-07T08:15:19.2073966Z shell: /usr/bin/bash -e {0} 2025-09-07T08:15:19.2074172Z env: 2025-09-07T08:15:19.2074333Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:19.2074523Z ##[endgroup] 2025-09-07T08:15:19.7071020Z ##[group]Run echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:15:19.7071710Z echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}" 2025-09-07T08:15:19.7085218Z shell: /usr/bin/bash -e {0} 2025-09-07T08:15:19.7085429Z env: 2025-09-07T08:15:19.7085582Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:19.7085845Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:19.7086106Z ##[endgroup] 2025-09-07T08:15:19.7503904Z Prepare all required actions 2025-09-07T08:15:19.8816418Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-09-07T08:15:19.8816684Z with: 2025-09-07T08:15:19.8817213Z github-token: *** 2025-09-07T08:15:19.8817415Z env: 2025-09-07T08:15:19.8817574Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:19.8817829Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:19.8818187Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:15:19.8818485Z ##[endgroup] 2025-09-07T08:15:20.1420190Z ##[group]Run set -eux 2025-09-07T08:15:20.1420626Z set -eux 2025-09-07T08:15:20.1420968Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T08:15:20.1434750Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:15:20.1435033Z env: 2025-09-07T08:15:20.1435202Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:20.1435457Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:20.1435819Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:15:20.1436324Z GITHUB_TOKEN: *** 2025-09-07T08:15:20.1436517Z ##[endgroup] 2025-09-07T08:15:20.1481997Z + python3 .github/scripts/get_workflow_job_id.py 17525296438 i-0b7d0f7dc0527ca9b-1003 2025-09-07T08:15:20.9209224Z Setting output job-id=49775781854 2025-09-07T08:15:20.9210764Z Setting output job-name=test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:15:20.9997030Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:15:20.9997657Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-09-07T08:15:20.9998357Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-09-07T08:15:20.9998956Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-09-07T08:15:21.0013737Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:15:21.0014025Z env: 2025-09-07T08:15:21.0014200Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:21.0014449Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:21.0014777Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:15:21.0015060Z JOB_ID: 49775781854 2025-09-07T08:15:21.0015410Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:15:21.0016034Z WORKFLOW_NAME: inductor-perf-nightly-h100 2025-09-07T08:15:21.0016282Z WORKFLOW_RUN_ID: 17525296438 2025-09-07T08:15:21.0016489Z MONITOR_LOG_INTERVAL: 15 2025-09-07T08:15:21.0016706Z MONITOR_DATA_COLLECT_INTERVAL: 4 2025-09-07T08:15:21.0016926Z ##[endgroup] 2025-09-07T08:15:21.2852065Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:15:22.2159243Z Collecting psutil==5.9.8 2025-09-07T08:15:22.6514188Z Downloading psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (288 kB) 2025-09-07T08:15:23.2039561Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 KB 507.0 kB/s eta 0:00:00 2025-09-07T08:15:23.6757727Z Collecting dataclasses_json==0.6.7 2025-09-07T08:15:23.6878282Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-09-07T08:15:24.7651222Z Collecting nvidia-ml-py==11.525.84 2025-09-07T08:15:24.7769559Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-09-07T08:15:26.0371264Z Collecting typing-inspect<1,>=0.4.0 2025-09-07T08:15:26.1436845Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-09-07T08:15:27.4893436Z Collecting marshmallow<4.0.0,>=3.18.0 2025-09-07T08:15:27.5012089Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-09-07T08:15:28.1570897Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 50.9/50.9 KB 62.2 kB/s eta 0:00:00 2025-09-07T08:15:29.1895363Z Collecting packaging>=17.0 2025-09-07T08:15:29.6825507Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-09-07T08:15:30.1759383Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 66.5/66.5 KB 114.8 kB/s eta 0:00:00 2025-09-07T08:15:30.6173432Z Collecting mypy-extensions>=0.3.0 2025-09-07T08:15:30.6292516Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-09-07T08:15:31.9423922Z Collecting typing-extensions>=3.7.4 2025-09-07T08:15:31.9549334Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-09-07T08:15:32.6579860Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 44.6/44.6 KB 49.1 kB/s eta 0:00:00 2025-09-07T08:15:32.7219344Z Installing collected packages: nvidia-ml-py, typing-extensions, psutil, packaging, mypy-extensions, typing-inspect, marshmallow, dataclasses_json 2025-09-07T08:15:44.0621871Z Successfully installed dataclasses_json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 nvidia-ml-py-11.525.84 packaging-25.0 psutil-5.9.8 typing-extensions-4.15.0 typing-inspect-0.9.0 2025-09-07T08:15:44.1195113Z Prepare all required actions 2025-09-07T08:15:44.1195436Z Getting action download info 2025-09-07T08:15:44.3016720Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-09-07T08:15:46.4297329Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-09-07T08:15:52.8452834Z ##[group]Run ./.github/actions/download-build-artifacts 2025-09-07T08:15:52.8453136Z with: 2025-09-07T08:15:52.8453355Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:15:52.8453647Z s3-bucket: gha-artifacts 2025-09-07T08:15:52.8453855Z env: 2025-09-07T08:15:52.8454024Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:52.8454293Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:52.8454656Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:15:52.8454967Z ##[endgroup] 2025-09-07T08:15:52.8490950Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:15:52.8491203Z with: 2025-09-07T08:15:52.8491394Z name: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:15:52.8491655Z s3-bucket: gha-artifacts 2025-09-07T08:15:52.8491859Z region: us-east-1 2025-09-07T08:15:52.8492022Z env: 2025-09-07T08:15:52.8492177Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:15:52.8492423Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:15:52.8492749Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:15:52.8493029Z ##[endgroup] 2025-09-07T08:15:53.3569828Z (node:8498) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:15:53.3570413Z 2025-09-07T08:15:53.3570594Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:15:53.3571105Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:15:53.3571634Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:15:53.4874399Z Found 1 objects with prefix pytorch/pytorch/17525296438/linux-jammy-cuda12.8-py3.10-gcc9-sm90/ 2025-09-07T08:15:53.4875017Z Starting download (1/1): /home/charlie/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:16:03.3441277Z Finished download (1/1): /home/charlie/_work/pytorch/pytorch/artifacts.zip 2025-09-07T08:16:03.3449258Z Artifact download has finished successfully 2025-09-07T08:16:03.8192663Z ##[group]Run unzip -o artifacts.zip 2025-09-07T08:16:03.8192974Z unzip -o artifacts.zip 2025-09-07T08:16:03.8207568Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:03.8207881Z env: 2025-09-07T08:16:03.8208049Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:03.8208305Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:03.8208634Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:03.8208908Z ##[endgroup] 2025-09-07T08:16:03.8275813Z Archive: artifacts.zip 2025-09-07T08:16:03.8276912Z creating: dist/ 2025-09-07T08:16:08.2138700Z inflating: dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T08:16:08.2139184Z creating: dist/vision/ 2025-09-07T08:16:08.2246434Z inflating: dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:16:08.2246918Z creating: dist/audio/ 2025-09-07T08:16:08.2302080Z inflating: dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:16:08.2302519Z creating: dist/torchrec/ 2025-09-07T08:16:08.2326097Z inflating: dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:16:08.2326487Z creating: dist/fbgemm_gpu/ 2025-09-07T08:16:09.9730739Z inflating: dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:16:09.9731182Z creating: dist/ao/ 2025-09-07T08:16:09.9768947Z inflating: dist/ao/torchao-0.7.0+git51c87b6e-py3-none-any.whl 2025-09-07T08:16:09.9890940Z inflating: dist/.ninja_log 2025-09-07T08:16:09.9892100Z creating: build/custom_test_artifacts/ 2025-09-07T08:16:09.9893629Z creating: build/custom_test_artifacts/custom-op-build/ 2025-09-07T08:16:09.9894897Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/ 2025-09-07T08:16:09.9895793Z creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/pkgRedirects/ 2025-09-07T08:16:09.9902773Z inflating: 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build/bin/vec_test_all_types_AVX512 2025-09-07T08:16:28.2252398Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_catches_stream 2025-09-07T08:16:28.2302448Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_1_var_test 2025-09-07T08:16:28.2353384Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_multiple_writes_from_blocks_and_threads 2025-09-07T08:16:28.2403128Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_multiple_writes_from_same_block 2025-09-07T08:16:28.2452430Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_from_2_processes 2025-09-07T08:16:28.2502205Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_catches_thread_and_block_and_device 2025-09-07T08:16:28.2552371Z inflating: build/bin/c10_cuda_CUDAAssertionsTest_multiple_writes_from_multiple_blocks 2025-09-07T08:16:28.2602427Z inflating: build/bin/BackoffTest 2025-09-07T08:16:28.3474611Z inflating: build/bin/TCPStoreTest 2025-09-07T08:16:28.3525563Z inflating: build/bin/HashStoreTest 2025-09-07T08:16:28.3575826Z inflating: build/bin/FileStoreTest 2025-09-07T08:16:28.3588518Z inflating: build/bin/ProcessGroupMPITest 2025-09-07T08:16:28.3591362Z inflating: build/bin/example_allreduce 2025-09-07T08:16:28.3660857Z inflating: build/bin/Dict_test 2025-09-07T08:16:28.3710355Z inflating: build/bin/Dimname_test 2025-09-07T08:16:28.3765721Z inflating: build/bin/NamedTensor_test 2025-09-07T08:16:28.3826523Z inflating: build/bin/MaybeOwned_test 2025-09-07T08:16:28.3882750Z inflating: build/bin/atest 2025-09-07T08:16:28.3943174Z inflating: build/bin/basic 2025-09-07T08:16:28.3999056Z inflating: build/bin/apply_utils_test 2025-09-07T08:16:28.4051310Z inflating: build/bin/broadcast_test 2025-09-07T08:16:28.4099578Z inflating: build/bin/cpu_allocator_test 2025-09-07T08:16:28.4155025Z inflating: build/bin/cpu_generator_test 2025-09-07T08:16:28.4205536Z inflating: build/bin/cpu_profiling_allocator_test 2025-09-07T08:16:28.4292918Z inflating: build/bin/cpu_rng_test 2025-09-07T08:16:28.4342366Z inflating: build/bin/dlconvertor_test 2025-09-07T08:16:28.4396941Z inflating: build/bin/extension_backend_test 2025-09-07T08:16:28.4449361Z inflating: build/bin/half_test 2025-09-07T08:16:28.4496729Z inflating: build/bin/lazy_tensor_test 2025-09-07T08:16:28.4548068Z inflating: build/bin/memory_format_test 2025-09-07T08:16:28.4599173Z inflating: build/bin/math_kernel_test 2025-09-07T08:16:28.4689126Z inflating: build/bin/ivalue_test 2025-09-07T08:16:28.4739758Z inflating: build/bin/memory_overlapping_test 2025-09-07T08:16:28.4790322Z inflating: build/bin/mobile_memory_cleanup 2025-09-07T08:16:28.4843573Z inflating: build/bin/native_test 2025-09-07T08:16:28.4891797Z inflating: build/bin/operator_name_test 2025-09-07T08:16:28.4941423Z inflating: build/bin/operators_test 2025-09-07T08:16:28.4990532Z inflating: build/bin/packedtensoraccessor_test 2025-09-07T08:16:28.5053536Z inflating: build/bin/pow_test 2025-09-07T08:16:28.5107545Z inflating: build/bin/quantized_test 2025-09-07T08:16:28.5155567Z inflating: build/bin/reduce_ops_test 2025-09-07T08:16:28.5204554Z inflating: build/bin/reportMemoryUsage_test 2025-09-07T08:16:28.5258080Z inflating: build/bin/scalar_tensor_test 2025-09-07T08:16:28.5677638Z inflating: build/bin/scalar_test 2025-09-07T08:16:28.5678061Z inflating: build/bin/StorageUtils_test 2025-09-07T08:16:28.5678415Z inflating: build/bin/stride_properties_test 2025-09-07T08:16:28.5679035Z inflating: build/bin/tensor_iterator_test 2025-09-07T08:16:28.5679586Z inflating: build/bin/test_parallel 2025-09-07T08:16:28.5680067Z inflating: build/bin/thread_init_test 2025-09-07T08:16:28.5680883Z inflating: build/bin/type_ptr_test 2025-09-07T08:16:28.5696311Z inflating: build/bin/type_test 2025-09-07T08:16:28.5747840Z inflating: build/bin/undefined_tensor_test 2025-09-07T08:16:28.5795042Z inflating: build/bin/verify_api_visibility 2025-09-07T08:16:28.5860864Z inflating: build/bin/legacy_vmap_test 2025-09-07T08:16:28.5909615Z inflating: build/bin/weakref_test 2025-09-07T08:16:28.5958350Z inflating: build/bin/xla_tensor_test 2025-09-07T08:16:28.6007373Z inflating: build/bin/wrapdim_test 2025-09-07T08:16:28.6063464Z inflating: build/bin/IListRef_test 2025-09-07T08:16:28.6176991Z inflating: build/bin/kernel_function_legacy_test 2025-09-07T08:16:28.6959903Z inflating: build/bin/List_test 2025-09-07T08:16:28.8399684Z inflating: build/bin/KernelFunction_test 2025-09-07T08:16:28.8489578Z inflating: build/bin/kernel_function_test 2025-09-07T08:16:28.8607454Z inflating: build/bin/kernel_lambda_legacy_test 2025-09-07T08:16:28.8703464Z inflating: build/bin/kernel_lambda_test 2025-09-07T08:16:28.8763184Z inflating: build/bin/kernel_stackbased_test 2025-09-07T08:16:28.8852995Z inflating: build/bin/make_boxed_from_unboxed_functor_test 2025-09-07T08:16:28.8901890Z inflating: build/bin/CppSignature_test 2025-09-07T08:16:28.8954430Z inflating: build/bin/backend_fallback_test 2025-09-07T08:16:28.9001346Z inflating: build/bin/op_allowlist_test 2025-09-07T08:16:28.9277329Z inflating: build/bin/op_registration_test 2025-09-07T08:16:28.9339748Z inflating: build/bin/inline_container_test 2025-09-07T08:16:28.9389509Z inflating: build/bin/cuda_allocator_test 2025-09-07T08:16:28.9439432Z inflating: build/bin/cuda_apply_test 2025-09-07T08:16:28.9495509Z inflating: build/bin/cuda_atomic_ops_test 2025-09-07T08:16:28.9549652Z inflating: build/bin/cuda_caching_host_allocator_test 2025-09-07T08:16:29.0144734Z inflating: build/bin/cuda_complex_math_test 2025-09-07T08:16:29.0202160Z inflating: build/bin/cuda_complex_test 2025-09-07T08:16:29.0261223Z inflating: build/bin/cuda_cub_test 2025-09-07T08:16:29.0308382Z inflating: build/bin/cuda_device_test 2025-09-07T08:16:29.0369849Z inflating: build/bin/cuda_distributions_test 2025-09-07T08:16:29.0420018Z inflating: build/bin/cuda_dlconvertor_test 2025-09-07T08:16:29.0467933Z inflating: build/bin/cuda_exchange_device_test 2025-09-07T08:16:29.0515299Z inflating: build/bin/cuda_half_test 2025-09-07T08:16:29.0569296Z inflating: build/bin/cuda_generator_test 2025-09-07T08:16:29.0618021Z inflating: build/bin/cuda_integer_divider_test 2025-09-07T08:16:29.0665135Z inflating: build/bin/cuda_optional_test 2025-09-07T08:16:29.0714170Z inflating: build/bin/cuda_packedtensoraccessor_test 2025-09-07T08:16:29.0764184Z inflating: build/bin/cuda_reportMemoryUsage_test 2025-09-07T08:16:29.0811140Z inflating: build/bin/cuda_allocatorTraceTracker_test 2025-09-07T08:16:29.0868407Z inflating: build/bin/cuda_stream_test 2025-09-07T08:16:29.0915440Z inflating: build/bin/cuda_cudnn_test 2025-09-07T08:16:29.0965113Z inflating: build/bin/cuda_vectorized_test 2025-09-07T08:16:29.1309712Z inflating: build/bin/test_nativert 2025-09-07T08:16:29.1362126Z inflating: build/bin/test_dist_autograd 2025-09-07T08:16:29.1426781Z inflating: build/bin/test_cpp_rpc 2025-09-07T08:16:29.3666264Z inflating: build/bin/test_api 2025-09-07T08:16:29.4673719Z inflating: build/bin/parallel_benchmark 2025-09-07T08:16:29.4738325Z inflating: build/bin/ProcessGroupGlooTest 2025-09-07T08:16:29.4797892Z inflating: build/bin/ProcessGroupNCCLTest 2025-09-07T08:16:29.4853465Z inflating: build/bin/ProcessGroupGlooAsyncTest 2025-09-07T08:16:29.4911476Z inflating: build/bin/ProcessGroupNCCLErrorsTest 2025-09-07T08:16:29.6388256Z inflating: build/bin/test_jit 2025-09-07T08:16:29.8315647Z inflating: build/bin/test_lazy 2025-09-07T08:16:29.8319360Z inflating: build/bin/torch_shm_manager 2025-09-07T08:16:29.8319940Z creating: .additional_ci_files/ 2025-09-07T08:16:29.8399867Z inflating: .additional_ci_files/test-times.json 2025-09-07T08:16:29.8703366Z inflating: .additional_ci_files/test-class-times.json 2025-09-07T08:16:30.0329007Z ##[group]Run rm artifacts.zip 2025-09-07T08:16:30.0329266Z rm artifacts.zip 2025-09-07T08:16:30.0343919Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:30.0344214Z env: 2025-09-07T08:16:30.0344375Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:30.0344622Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:30.0344985Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:30.0345269Z ##[endgroup] 2025-09-07T08:16:30.6862387Z ##[group]Run df -H 2025-09-07T08:16:30.6862672Z df -H 2025-09-07T08:16:30.6877181Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:30.6877494Z env: 2025-09-07T08:16:30.6877670Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:30.6877945Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:30.6878309Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:30.6878845Z ##[endgroup] 2025-09-07T08:16:30.7276258Z Filesystem Size Used Avail Use% Mounted on 2025-09-07T08:16:30.7276671Z overlay 7.3T 696G 6.6T 10% / 2025-09-07T08:16:30.7277018Z tmpfs 68M 0 68M 0% /dev 2025-09-07T08:16:30.7277381Z shm 68M 0 68M 0% /dev/shm 2025-09-07T08:16:30.7277754Z /dev/root 7.3T 696G 6.6T 10% /home/charlie/_work 2025-09-07T08:16:30.7278204Z tmpfs 215G 111k 215G 1% /run/docker.sock 2025-09-07T08:16:30.7278619Z tmpfs 1.1T 13k 1.1T 1% /proc/driver/nvidia 2025-09-07T08:16:30.7279222Z tmpfs 430G 2.9M 430G 1% /run/.ro3175502231/nvidia-persistenced/socket 2025-09-07T08:16:30.7279786Z tmpfs 1.1T 0 1.1T 0% /proc/acpi 2025-09-07T08:16:30.7280148Z tmpfs 1.1T 0 1.1T 0% /proc/scsi 2025-09-07T08:16:30.7280684Z tmpfs 1.1T 0 1.1T 0% /sys/firmware 2025-09-07T08:16:30.7310688Z Prepare all required actions 2025-09-07T08:16:30.7311483Z Getting action download info 2025-09-07T08:16:31.0429627Z ##[group]Run ./.github/actions/download-td-artifacts 2025-09-07T08:16:31.0429950Z with: 2025-09-07T08:16:31.0430135Z env: 2025-09-07T08:16:31.0430525Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:31.0430845Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:31.0431270Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:31.0431628Z ##[endgroup] 2025-09-07T08:16:31.3546237Z ##[group]Run seemethere/download-artifact-s3@v4 2025-09-07T08:16:31.3546513Z with: 2025-09-07T08:16:31.3546671Z name: td_results 2025-09-07T08:16:31.3546858Z s3-bucket: gha-artifacts 2025-09-07T08:16:31.3547059Z region: us-east-1 2025-09-07T08:16:31.3547235Z env: 2025-09-07T08:16:31.3547397Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:31.3547651Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:31.3548025Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:31.3548315Z ##[endgroup] 2025-09-07T08:16:31.8073899Z (node:8522) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-09-07T08:16:31.8074359Z 2025-09-07T08:16:31.8074552Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-09-07T08:16:31.8075052Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-09-07T08:16:31.8075569Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-09-07T08:16:31.9303429Z Found 0 objects with prefix pytorch/pytorch/17525296438/td_results/ 2025-09-07T08:16:31.9308783Z Artifact download has finished successfully 2025-09-07T08:16:32.0353580Z ##[group]Run mkdir -p .additional_ci_files 2025-09-07T08:16:32.0353935Z mkdir -p .additional_ci_files 2025-09-07T08:16:32.0354342Z mv td_results.json .additional_ci_files/td_results.json || true 2025-09-07T08:16:32.0368875Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:32.0369188Z env: 2025-09-07T08:16:32.0369370Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:32.0369642Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:32.0369991Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:32.0370467Z ##[endgroup] 2025-09-07T08:16:32.0822141Z mv: cannot stat 'td_results.json': No such file or directory 2025-09-07T08:16:32.4426945Z ##[group]Run .github/scripts/parse_ref.py 2025-09-07T08:16:32.4427342Z .github/scripts/parse_ref.py 2025-09-07T08:16:32.4441952Z shell: /usr/bin/bash -e {0} 2025-09-07T08:16:32.4442201Z env: 2025-09-07T08:16:32.4442361Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:32.4442614Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:32.4442959Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:32.4443233Z ##[endgroup] 2025-09-07T08:16:32.5333164Z Setting output branch=main 2025-09-07T08:16:32.5431633Z Prepare all required actions 2025-09-07T08:16:32.5431972Z Getting action download info 2025-09-07T08:16:32.7520040Z ##[group]Run ./.github/actions/filter-test-configs 2025-09-07T08:16:32.7520595Z with: 2025-09-07T08:16:32.7521022Z github-token: *** 2025-09-07T08:16:32.7526926Z test-matrix: {"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T08:16:32.7532714Z job-name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:16:32.7533061Z env: 2025-09-07T08:16:32.7533221Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:32.7533473Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:32.7533800Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:32.7534076Z ##[endgroup] 2025-09-07T08:16:33.0853448Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T08:16:33.0853722Z with: 2025-09-07T08:16:33.0853883Z shell: bash 2025-09-07T08:16:33.0854062Z timeout_minutes: 10 2025-09-07T08:16:33.0854264Z max_attempts: 5 2025-09-07T08:16:33.0854464Z retry_wait_seconds: 30 2025-09-07T08:16:33.0855100Z command: set -eux # PyYAML 6.0 doesn't work with MacOS x86 anymore # This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2 python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:16:33.0855765Z polling_interval_seconds: 1 2025-09-07T08:16:33.0855985Z warning_on_retry: true 2025-09-07T08:16:33.0856192Z continue_on_error: false 2025-09-07T08:16:33.0856388Z env: 2025-09-07T08:16:33.0856553Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:33.0856810Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:33.0857175Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:33.0857624Z GITHUB_TOKEN: *** 2025-09-07T08:16:33.0857811Z ##[endgroup] 2025-09-07T08:16:33.5396760Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-09-07T08:16:33.7945657Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T08:16:34.5363767Z Collecting requests==2.27.1 2025-09-07T08:16:34.5965251Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-09-07T08:16:35.0975746Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 63.1/63.1 KB 106.1 kB/s eta 0:00:00 2025-09-07T08:16:35.7956695Z Collecting pyyaml==6.0.2 2025-09-07T08:16:35.8074443Z Downloading PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (751 kB) 2025-09-07T08:16:36.3382561Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 751.2/751.2 KB 1.4 MB/s eta 0:00:00 2025-09-07T08:16:37.2604602Z Collecting charset-normalizer~=2.0.0 2025-09-07T08:16:37.2722355Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-09-07T08:16:38.0781655Z Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.27.1) (2020.6.20) 2025-09-07T08:16:38.0792183Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.27.1) (3.3) 2025-09-07T08:16:38.0796794Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.27.1) (1.26.5) 2025-09-07T08:16:38.1464037Z Installing collected packages: pyyaml, charset-normalizer, requests 2025-09-07T08:16:39.5577499Z WARNING: The script normalizer is installed in '/home/charlie/.local/bin' which is not on PATH. 2025-09-07T08:16:39.5578750Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T08:16:42.1796934Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-09-07T08:16:42.3408899Z Command completed after 1 attempt(s). 2025-09-07T08:16:42.3880807Z ##[group]Run set -x 2025-09-07T08:16:42.3881047Z set -x 2025-09-07T08:16:42.3881238Z  2025-09-07T08:16:42.3881579Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:16:42.3882002Z # in runner workspace 2025-09-07T08:16:42.3882345Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-09-07T08:16:42.3896702Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:42.3896998Z env: 2025-09-07T08:16:42.3897154Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:42.3897415Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:42.3897750Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:42.3898032Z ##[endgroup] 2025-09-07T08:16:42.4378172Z + python3 /home/charlie/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-09-07T08:16:42.4525939Z Setting output branch=main 2025-09-07T08:16:42.5037576Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:16:42.5037970Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-09-07T08:16:42.5038259Z echo "Job name: ${JOB_NAME}" 2025-09-07T08:16:42.5038532Z  2025-09-07T08:16:42.5038862Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-09-07T08:16:42.5039287Z # in runner workspace 2025-09-07T08:16:42.5039654Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-09-07T08:16:42.5040069Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-09-07T08:16:42.5040528Z  --job-name "${JOB_NAME}" \ 2025-09-07T08:16:42.5046032Z  --test-matrix "{"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]}" \ 2025-09-07T08:16:42.5051294Z  --selected-test-configs "" \ 2025-09-07T08:16:42.5051545Z  --pr-number "${PR_NUMBER}" \ 2025-09-07T08:16:42.5051776Z  --tag "${TAG}" \ 2025-09-07T08:16:42.5052004Z  --event-name "${EVENT_NAME}" \ 2025-09-07T08:16:42.5052248Z  --schedule "${SCHEDULE}" \ 2025-09-07T08:16:42.5052474Z  --branch "${HEAD_BRANCH}" 2025-09-07T08:16:42.5067110Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:42.5067415Z env: 2025-09-07T08:16:42.5067580Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:42.5067834Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:42.5068176Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:42.5068651Z GITHUB_TOKEN: *** 2025-09-07T08:16:42.5068977Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:16:42.5069335Z PR_NUMBER: 2025-09-07T08:16:42.5069497Z TAG: 2025-09-07T08:16:42.5069645Z EVENT_NAME: schedule 2025-09-07T08:16:42.5069824Z SCHEDULE: 0 7 * * 0 2025-09-07T08:16:42.5069997Z HEAD_BRANCH: main 2025-09-07T08:16:42.5070155Z ##[endgroup] 2025-09-07T08:16:42.5517424Z Workflow: inductor-perf-nightly-h100 2025-09-07T08:16:42.5528532Z Job name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:16:43.4029489Z Setting output keep-going=True 2025-09-07T08:16:43.4029855Z Setting output ci-verbose-test-logs=False 2025-09-07T08:16:43.4030566Z Setting output ci-test-showlocals=False 2025-09-07T08:16:43.4030919Z Setting output ci-no-test-timeout=False 2025-09-07T08:16:43.4031237Z Setting output ci-no-td=False 2025-09-07T08:16:43.4031560Z Setting output ci-td-distributed=False 2025-09-07T08:16:43.4031884Z Setting output is-unstable=False 2025-09-07T08:16:43.4032156Z Setting output reenabled-issues= 2025-09-07T08:16:43.4038748Z Setting output test-matrix={"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]} 2025-09-07T08:16:43.4044996Z Setting output is-test-matrix-empty=False 2025-09-07T08:16:43.4287617Z ##[group]Run echo "Filtered matrix:" 2025-09-07T08:16:43.4287914Z echo "Filtered matrix:" 2025-09-07T08:16:43.4293762Z echo "{"include": [{"config": "inductor_huggingface_perf_cuda_h100", "shard": 1, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 2, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 3, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 4, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_huggingface_perf_cuda_h100", "shard": 5, "num_shards": 5, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 1, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 2, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 3, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 4, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 5, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 6, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_timm_perf_cuda_h100", "shard": 7, "num_shards": 7, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 1, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 2, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 3, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 4, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 5, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 6, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 7, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 8, "num_shards": 9, "runner": "linux.aws.h100"}, {"config": "inductor_torchbench_perf_cuda_h100", "shard": 9, "num_shards": 9, "runner": "linux.aws.h100"}]}" 2025-09-07T08:16:43.4298775Z  2025-09-07T08:16:43.4298942Z echo 2025-09-07T08:16:43.4299147Z echo "Is the current job unstable? False" 2025-09-07T08:16:43.4299390Z  2025-09-07T08:16:43.4299533Z echo 2025-09-07T08:16:43.4299725Z echo "Is keep-going label set? True" 2025-09-07T08:16:43.4299952Z  2025-09-07T08:16:43.4300093Z echo 2025-09-07T08:16:43.4300373Z echo "Reenabled issues? " 2025-09-07T08:16:43.4314836Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:43.4315132Z env: 2025-09-07T08:16:43.4315295Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:43.4315546Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:43.4315889Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:43.4316180Z ##[endgroup] 2025-09-07T08:16:43.4655601Z Filtered matrix: 2025-09-07T08:16:43.4661842Z {include: [{config: inductor_huggingface_perf_cuda_h100, shard: 1, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 2, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 3, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 4, num_shards: 5, runner: linux.aws.h100}, {config: inductor_huggingface_perf_cuda_h100, shard: 5, num_shards: 5, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 1, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 2, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 3, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 4, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 5, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 6, num_shards: 7, runner: linux.aws.h100}, {config: inductor_timm_perf_cuda_h100, shard: 7, num_shards: 7, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 1, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 2, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 3, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 4, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 5, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 6, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 7, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 8, num_shards: 9, runner: linux.aws.h100}, {config: inductor_torchbench_perf_cuda_h100, shard: 9, num_shards: 9, runner: linux.aws.h100}]} 2025-09-07T08:16:43.4667443Z 2025-09-07T08:16:43.4667534Z Is the current job unstable? False 2025-09-07T08:16:43.4667710Z 2025-09-07T08:16:43.4667796Z Is keep-going label set? True 2025-09-07T08:16:43.4667951Z 2025-09-07T08:16:43.4668030Z Reenabled issues? 2025-09-07T08:16:43.5981492Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:16:43.5981966Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-09-07T08:16:43.5996190Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:43.5996484Z env: 2025-09-07T08:16:43.5996647Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:43.5996901Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:43.5997244Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:43.5997518Z JOB_TIMEOUT: 1440 2025-09-07T08:16:43.5997688Z ##[endgroup] 2025-09-07T08:16:43.8280744Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:16:43.8281412Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:16:43.8282146Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-09-07T08:16:43.8296047Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T08:16:43.8296442Z env: 2025-09-07T08:16:43.8296783Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:43.8297102Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:43.8297547Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:43.8297994Z ##[endgroup] 2025-09-07T08:16:43.8973116Z ##[group]Run set -x 2025-09-07T08:16:43.8973567Z set -x 2025-09-07T08:16:43.8973817Z  2025-09-07T08:16:43.8974182Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-09-07T08:16:43.8974588Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-09-07T08:16:43.8975013Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-09-07T08:16:43.8975360Z  TEST_COMMAND=.ci/onnx/test.sh 2025-09-07T08:16:43.8975685Z else 2025-09-07T08:16:43.8976007Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:16:43.8976383Z fi 2025-09-07T08:16:43.8976583Z  2025-09-07T08:16:43.8976895Z # Leaving 1GB for the runner and other things 2025-09-07T08:16:43.8977459Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-09-07T08:16:43.8978301Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-09-07T08:16:43.8978920Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-09-07T08:16:43.8979414Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-09-07T08:16:43.8979841Z  2025-09-07T08:16:43.8980174Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:16:43.8980745Z  SHM_OPTS= 2025-09-07T08:16:43.8981019Z  JENKINS_USER= 2025-09-07T08:16:43.8981417Z  # ensure that docker container cleanly exits in 12 hours 2025-09-07T08:16:43.8981873Z  # if for some reason cleanup action doesn't stop container 2025-09-07T08:16:43.8982309Z  # when job is cancelled 2025-09-07T08:16:43.8982596Z  DOCKER_SHELL_CMD="sleep 12h" 2025-09-07T08:16:43.8983029Z else 2025-09-07T08:16:43.8983366Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-09-07T08:16:43.8983693Z  JENKINS_USER="--user jenkins" 2025-09-07T08:16:43.8983999Z  DOCKER_SHELL_CMD= 2025-09-07T08:16:43.8984314Z fi 2025-09-07T08:16:43.8984545Z  2025-09-07T08:16:43.8984890Z # detached container should get cleaned up by teardown_ec2_linux 2025-09-07T08:16:43.8985419Z # TODO: Stop building test binaries as part of the build phase 2025-09-07T08:16:43.8985906Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-09-07T08:16:43.8986366Z # shellcheck disable=SC2086,SC2090 2025-09-07T08:16:43.8986750Z container_name=$(docker run \ 2025-09-07T08:16:43.8987060Z  ${GPU_FLAG:-} \ 2025-09-07T08:16:43.8987407Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-09-07T08:16:43.8987726Z  -e BUILD_ENVIRONMENT \ 2025-09-07T08:16:43.8988043Z  -e PR_NUMBER \ 2025-09-07T08:16:43.8988349Z  -e GITHUB_ACTIONS \ 2025-09-07T08:16:43.8988652Z  -e GITHUB_REPOSITORY \ 2025-09-07T08:16:43.8988937Z  -e GITHUB_WORKFLOW \ 2025-09-07T08:16:43.8989249Z  -e GITHUB_JOB \ 2025-09-07T08:16:43.8989538Z  -e GITHUB_RUN_ID \ 2025-09-07T08:16:43.8989837Z  -e GITHUB_RUN_NUMBER \ 2025-09-07T08:16:43.8990116Z  -e GITHUB_RUN_ATTEMPT \ 2025-09-07T08:16:43.8990571Z  -e JOB_ID \ 2025-09-07T08:16:43.8990854Z  -e JOB_NAME \ 2025-09-07T08:16:43.8991047Z  -e BASE_SHA \ 2025-09-07T08:16:43.8991226Z  -e BRANCH \ 2025-09-07T08:16:43.8991401Z  -e SHA1 \ 2025-09-07T08:16:43.8991807Z  -e AWS_DEFAULT_REGION \ 2025-09-07T08:16:43.8992010Z  -e IN_WHEEL_TEST \ 2025-09-07T08:16:43.8992205Z  -e SHARD_NUMBER \ 2025-09-07T08:16:43.8992405Z  -e TEST_CONFIG \ 2025-09-07T08:16:43.8992605Z  -e NUM_TEST_SHARDS \ 2025-09-07T08:16:43.8992805Z  -e REENABLED_ISSUES \ 2025-09-07T08:16:43.8993030Z  -e CONTINUE_THROUGH_ERROR \ 2025-09-07T08:16:43.8993463Z  -e VERBOSE_TEST_LOGS \ 2025-09-07T08:16:43.8993682Z  -e TEST_SHOWLOCALS \ 2025-09-07T08:16:43.8993879Z  -e NO_TEST_TIMEOUT \ 2025-09-07T08:16:43.8994071Z  -e NO_TD \ 2025-09-07T08:16:43.8994250Z  -e TD_DISTRIBUTED \ 2025-09-07T08:16:43.8994445Z  -e PR_LABELS \ 2025-09-07T08:16:43.8994664Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-09-07T08:16:43.8994908Z  -e SCCACHE_BUCKET \ 2025-09-07T08:16:43.8995106Z  -e SCCACHE_REGION \ 2025-09-07T08:16:43.8995317Z  -e XLA_CUDA \ 2025-09-07T08:16:43.8995518Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-09-07T08:16:43.8995776Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-09-07T08:16:43.8996048Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-09-07T08:16:43.8996315Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-09-07T08:16:43.8996563Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-09-07T08:16:43.8996804Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-09-07T08:16:43.8997047Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-09-07T08:16:43.8997283Z  -e DASHBOARD_TAG \ 2025-09-07T08:16:43.8997492Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-09-07T08:16:43.8997746Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-09-07T08:16:43.8998046Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-09-07T08:16:43.8998347Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-09-07T08:16:43.8998625Z  --security-opt seccomp=unconfined \ 2025-09-07T08:16:43.8998871Z  --cap-add=SYS_PTRACE \ 2025-09-07T08:16:43.8999079Z  --ipc=host \ 2025-09-07T08:16:43.8999272Z  ${SHM_OPTS} \ 2025-09-07T08:16:43.8999451Z  --tty \ 2025-09-07T08:16:43.8999614Z  --detach \ 2025-09-07T08:16:43.8999804Z  --name="${container_name}" \ 2025-09-07T08:16:43.9000028Z  ${JENKINS_USER} \ 2025-09-07T08:16:43.9000415Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-09-07T08:16:43.9000708Z  -w /var/lib/jenkins/workspace \ 2025-09-07T08:16:43.9000929Z  "${DOCKER_IMAGE}" \ 2025-09-07T08:16:43.9001127Z  ${DOCKER_SHELL_CMD} 2025-09-07T08:16:43.9001314Z ) 2025-09-07T08:16:43.9001522Z # Propagate download.pytorch.org IP to container 2025-09-07T08:16:43.9001996Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-09-07T08:16:43.9002509Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-09-07T08:16:43.9002810Z  2025-09-07T08:16:43.9003003Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-09-07T08:16:43.9003416Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-09-07T08:16:43.9003776Z fi 2025-09-07T08:16:43.9003939Z  2025-09-07T08:16:43.9004290Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-09-07T08:16:43.9017689Z shell: /usr/bin/bash -e {0} 2025-09-07T08:16:43.9017906Z env: 2025-09-07T08:16:43.9018065Z GIT_DEFAULT_BRANCH: main 2025-09-07T08:16:43.9018336Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:16:43.9018669Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T08:16:43.9019010Z BUILD_ENVIRONMENT: linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:16:43.9019464Z PR_NUMBER: 2025-09-07T08:16:43.9019645Z GITHUB_REPOSITORY: pytorch/pytorch 2025-09-07T08:16:43.9019899Z GITHUB_WORKFLOW: inductor-perf-nightly-h100 2025-09-07T08:16:43.9020154Z GITHUB_JOB: test 2025-09-07T08:16:43.9020668Z GITHUB_RUN_ID: 17525296438 2025-09-07T08:16:43.9020865Z GITHUB_RUN_NUMBER: 662 2025-09-07T08:16:43.9021061Z GITHUB_RUN_ATTEMPT: 1 2025-09-07T08:16:43.9021244Z JOB_ID: 49775781854 2025-09-07T08:16:43.9021731Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:16:43.9022086Z BRANCH: main 2025-09-07T08:16:43.9022276Z SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:16:43.9022545Z BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:16:43.9022810Z TEST_CONFIG: inductor_torchbench_perf_cuda_h100 2025-09-07T08:16:43.9023134Z SHARD_NUMBER: 9 2025-09-07T08:16:43.9023295Z NUM_TEST_SHARDS: 9 2025-09-07T08:16:43.9023462Z REENABLED_ISSUES: 2025-09-07T08:16:43.9023639Z CONTINUE_THROUGH_ERROR: True 2025-09-07T08:16:43.9023843Z VERBOSE_TEST_LOGS: False 2025-09-07T08:16:43.9024030Z TEST_SHOWLOCALS: False 2025-09-07T08:16:43.9024212Z NO_TEST_TIMEOUT: False 2025-09-07T08:16:43.9024378Z NO_TD: False 2025-09-07T08:16:43.9024537Z TD_DISTRIBUTED: False 2025-09-07T08:16:43.9024758Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-09-07T08:16:43.9025016Z SCCACHE_REGION: us-east-1 2025-09-07T08:16:43.9025200Z SHM_SIZE: 2g 2025-09-07T08:16:43.9025837Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:16:43.9026532Z XLA_CUDA: 2025-09-07T08:16:43.9026793Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:16:43.9027124Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-09-07T08:16:43.9027349Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-09-07T08:16:43.9028256Z DASHBOARD_TAG: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T08:16:43.9029320Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-09-07T08:16:43.9029640Z HUGGING_FACE_HUB_TOKEN: *** 2025-09-07T08:16:43.9029945Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-09-07T08:16:43.9030461Z ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T08:16:43.9030838Z ##[endgroup] 2025-09-07T08:16:43.9279535Z + [[ inductor_torchbench_perf_cuda_h100 == \m\u\l\t\i\g\p\u ]] 2025-09-07T08:16:43.9279936Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *onnx* ]] 2025-09-07T08:16:43.9280617Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-09-07T08:16:43.9284849Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-09-07T08:16:43.9298145Z + TOTAL_AVAILABLE_MEMORY_IN_GB='1998.949 ' 2025-09-07T08:16:43.9298447Z + TOTAL_MEMORY_WITH_SWAP=2001 2025-09-07T08:16:43.9298761Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *\s\3\9\0\x* ]] 2025-09-07T08:16:43.9299074Z + SHM_OPTS=--shm-size=2g 2025-09-07T08:16:43.9299295Z + JENKINS_USER='--user jenkins' 2025-09-07T08:16:43.9300570Z + DOCKER_SHELL_CMD= 2025-09-07T08:16:43.9308887Z +++ nproc --ignore=2 2025-09-07T08:16:43.9324798Z ++ docker run --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all -e SCCACHE_SERVER_PORT=5229 -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=22 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e VLLM_TEST_HUGGING_FACE_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=1998g --memory-swap=2001g --env-file=/tmp/github_env_17525296438 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=2g --tty --detach --name= --user jenkins -v /home/charlie/_work/pytorch/pytorch:/var/lib/jenkins/workspace -w /var/lib/jenkins/workspace 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77 2025-09-07T08:35:46.5489925Z + container_name=541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T08:35:46.5493568Z + grep download.pytorch.org /etc/hosts 2025-09-07T08:35:46.5494812Z + docker exec -i 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f sudo bash -c '/bin/cat >> /etc/hosts' 2025-09-07T08:35:46.6103395Z + echo DOCKER_CONTAINER_ID=541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T08:35:46.6105631Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *\s\3\9\0\x* ]] 2025-09-07T08:35:46.6108816Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl 2025-09-07T08:35:46.6111841Z + docker exec -t 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-09-07T08:35:47.0213352Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp310-cp310-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d) 2025-09-07T08:35:47.3262405Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.19.1) 2025-09-07T08:35:47.3265808Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (4.15.0) 2025-09-07T08:35:47.3268946Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.13.3) 2025-09-07T08:35:47.3272949Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (2.8.8) 2025-09-07T08:35:47.3275764Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.1.6) 2025-09-07T08:35:47.3279568Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (2025.3.0) 2025-09-07T08:35:47.3292039Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.3.0) 2025-09-07T08:35:47.3617343Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from opt-einsum>=3.3->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.22.4) 2025-09-07T08:35:47.3634469Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from sympy>=1.13.3->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.3.0) 2025-09-07T08:35:47.3666993Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from jinja2->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.0.2) 2025-09-07T08:35:48.1609220Z Installing collected packages: torch 2025-09-07T08:35:57.7807638Z ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. 2025-09-07T08:35:57.7808575Z dall-e 0.1 requires torchvision, which is not installed. 2025-09-07T08:35:57.7808980Z effdet 0.4.1 requires torchvision, which is not installed. 2025-09-07T08:35:57.7809982Z python-doctr 1.0.0 requires torchvision>=0.15.0, which is not installed. 2025-09-07T08:35:57.7810953Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed. 2025-09-07T08:35:57.7811651Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed. 2025-09-07T08:35:57.7812341Z timm 1.0.14 requires torchvision, which is not installed. 2025-09-07T08:35:57.7813109Z Successfully installed torch-2.9.0a0+git93fb23d 2025-09-07T08:35:57.8488429Z + export TERM=vt100 2025-09-07T08:35:57.8488646Z + TERM=vt100 2025-09-07T08:35:57.8491969Z ++ dirname .ci/pytorch/test.sh 2025-09-07T08:35:57.8501811Z + source .ci/pytorch/common.sh 2025-09-07T08:35:57.8505826Z +++ dirname .ci/pytorch/common.sh 2025-09-07T08:35:57.8515930Z ++ source .ci/pytorch/common_utils.sh 2025-09-07T08:35:57.8517156Z +++ declare -f -t trap_add 2025-09-07T08:35:57.8521401Z ++ set -ex -o pipefail 2025-09-07T08:35:57.8521716Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:35:57.8522033Z ++ BUILD_TEST_LIBTORCH=0 2025-09-07T08:35:57.8526178Z ++ dirname .ci/pytorch/test.sh 2025-09-07T08:35:57.8534229Z + source .ci/pytorch/common-build.sh 2025-09-07T08:35:57.8535612Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *win-* ]] 2025-09-07T08:35:57.8543275Z ++++ dirname .ci/pytorch/common-build.sh 2025-09-07T08:35:57.8551203Z +++ cd .ci/pytorch 2025-09-07T08:35:57.8551426Z +++ pwd -P 2025-09-07T08:35:57.8553828Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-09-07T08:35:57.8554219Z ++ [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-pch* ]] 2025-09-07T08:35:57.8554535Z ++ which sccache 2025-09-07T08:35:57.8568386Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-09-07T08:35:57.8568667Z ++ sccache --stop-server 2025-09-07T08:35:57.8595552Z ++ true 2025-09-07T08:35:57.8595767Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-09-07T08:35:57.8607276Z ++ trap_add sccache_epilogue EXIT 2025-09-07T08:35:57.8607550Z ++ trap_add_cmd=sccache_epilogue 2025-09-07T08:35:57.8607779Z ++ shift 2025-09-07T08:35:57.8607949Z ++ for trap_add_name in "$@" 2025-09-07T08:35:57.8614447Z ++++ trap -p EXIT 2025-09-07T08:35:57.8617274Z +++ eval 'extract_trap_cmd ' 2025-09-07T08:35:57.8617489Z ++++ extract_trap_cmd 2025-09-07T08:35:57.8617676Z ++++ printf '%s\n' '' 2025-09-07T08:35:57.8617883Z +++ printf '%s\n' sccache_epilogue 2025-09-07T08:35:57.8619996Z ++ trap -- ' 2025-09-07T08:35:57.8620193Z sccache_epilogue' EXIT 2025-09-07T08:35:57.8620514Z ++ [[ -n 1 ]] 2025-09-07T08:35:57.8620824Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-09-07T08:35:57.8621314Z Skipping sccache server initialization, setting environment variables 2025-09-07T08:35:57.8621666Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:35:57.8621894Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:35:57.8622163Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:35:57.8622528Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:35:57.8622936Z ++ export RUST_LOG=sccache::server=error 2025-09-07T08:35:57.8623195Z ++ RUST_LOG=sccache::server=error 2025-09-07T08:35:57.8623417Z ++ sccache --zero-stats 2025-09-07T08:35:58.0154811Z Statistics zeroed. 2025-09-07T08:35:58.0161468Z ++ which ccache 2025-09-07T08:35:58.0175779Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *rocm* ]] 2025-09-07T08:35:58.0176183Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *s390x* ]] 2025-09-07T08:35:58.0176535Z + [[ -d /var/lib/jenkins/workspace ]] 2025-09-07T08:35:58.0179044Z ++ stat -c %u /var/lib/jenkins/workspace 2025-09-07T08:35:58.0190966Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-09-07T08:35:58.0191243Z + trap_add cleanup_workspace EXIT 2025-09-07T08:35:58.0191497Z + trap_add_cmd=cleanup_workspace 2025-09-07T08:35:58.0191715Z + shift 2025-09-07T08:35:58.0191873Z + for trap_add_name in "$@" 2025-09-07T08:35:58.0198211Z +++ trap -p EXIT 2025-09-07T08:35:58.0200729Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-09-07T08:35:58.0201531Z sccache_epilogue'\'' EXIT' 2025-09-07T08:35:58.0201899Z +++ extract_trap_cmd trap -- ' 2025-09-07T08:35:58.0202189Z sccache_epilogue' EXIT 2025-09-07T08:35:58.0202423Z +++ printf '%s\n' ' 2025-09-07T08:35:58.0202649Z sccache_epilogue' 2025-09-07T08:35:58.0202919Z ++ printf '%s\n' cleanup_workspace 2025-09-07T08:35:58.0203172Z + trap -- ' 2025-09-07T08:35:58.0203357Z sccache_epilogue 2025-09-07T08:35:58.0203560Z cleanup_workspace' EXIT 2025-09-07T08:35:58.0204063Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-09-07T08:36:07.8683162Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-09-07T08:36:08.1785707Z + echo 'Environment variables:' 2025-09-07T08:36:08.1786201Z Environment variables: 2025-09-07T08:36:08.1786576Z + env 2025-09-07T08:36:08.1797667Z GITHUB_WORKSPACE=/home/charlie/_work/pytorch/pytorch 2025-09-07T08:36:08.1798192Z CONTINUE_THROUGH_ERROR=True 2025-09-07T08:36:08.1798611Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:36:08.1804796Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T08:36:08.1805176Z HOSTNAME=541a5a68225e 2025-09-07T08:36:08.1805796Z GITHUB_PATH=/home/charlie/_work/_temp/_runner_file_commands/add_path_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.1806437Z GITHUB_ACTION=__run_2 2025-09-07T08:36:08.1806745Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T08:36:08.1807091Z GITHUB_RUN_NUMBER=662 2025-09-07T08:36:08.1807433Z TEST_CONFIG=inductor_torchbench_perf_cuda_h100 2025-09-07T08:36:08.1807870Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T08:36:08.1808250Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T08:36:08.1808606Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:36:08.1809065Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T08:36:08.1809432Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-09-07T08:36:08.1809794Z GITHUB_REF_TYPE=branch 2025-09-07T08:36:08.1810124Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.1810730Z XLA_CUDA= 2025-09-07T08:36:08.1811004Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T08:36:08.1811500Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T08:36:08.1811973Z *** 2025-09-07T08:36:08.1812225Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T08:36:08.1812562Z GITHUB_ACTIONS=true 2025-09-07T08:36:08.1812852Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:36:08.1813252Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:36:08.1813697Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.1814151Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.1814908Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-h100.yml@refs/heads/main 2025-09-07T08:36:08.1815593Z UCC_HOME=/usr 2025-09-07T08:36:08.1815860Z VERBOSE_TEST_LOGS=False 2025-09-07T08:36:08.1816171Z GITHUB_REF=refs/heads/main 2025-09-07T08:36:08.1816475Z SHARD_NUMBER=9 2025-09-07T08:36:08.1816756Z GITHUB_REF_PROTECTED=true 2025-09-07T08:36:08.1817057Z HOME=/var/lib/jenkins 2025-09-07T08:36:08.1817358Z SCCACHE_SERVER_PORT=5229 2025-09-07T08:36:08.1817700Z GITHUB_API_URL=https://api.github.com 2025-09-07T08:36:08.1818108Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T08:36:08.1818508Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T08:36:08.1818904Z USE_SYSTEM_NCCL=1 2025-09-07T08:36:08.1819173Z NUM_TEST_SHARDS=9 2025-09-07T08:36:08.1819430Z UCX_HOME=/usr 2025-09-07T08:36:08.1820013Z GITHUB_STATE=/home/charlie/_work/_temp/_runner_file_commands/save_state_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.1821096Z JOB_NAME=test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:36:08.1821932Z GITHUB_ENV=/home/charlie/_work/_temp/_runner_file_commands/set_env_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.1822718Z GITHUB_EVENT_PATH=/home/charlie/_work/_temp/_github_workflow/event.json 2025-09-07T08:36:08.1823333Z GITHUB_EVENT_NAME=schedule 2025-09-07T08:36:08.1824808Z DASHBOARD_TAG=training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T08:36:08.1826716Z GITHUB_RUN_ID=17525296438 2025-09-07T08:36:08.1827025Z INSTALLED_OPENBLAS= 2025-09-07T08:36:08.1827685Z GITHUB_STEP_SUMMARY=/home/charlie/_work/_temp/_runner_file_commands/step_summary_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.1828401Z GITHUB_ACTOR=pytorchmergebot 2025-09-07T08:36:08.1828719Z PR_NUMBER= 2025-09-07T08:36:08.1828970Z DESIRED_CUDA=12.8.1 2025-09-07T08:36:08.1829625Z GITHUB_RUN_ATTEMPT=1 2025-09-07T08:36:08.1829933Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T08:36:08.1830512Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T08:36:08.1830939Z TERM=vt100 2025-09-07T08:36:08.1831199Z INSTALLED_VISION=yes 2025-09-07T08:36:08.1831467Z BRANCH=main 2025-09-07T08:36:08.1831714Z SCCACHE_REGION=us-east-1 2025-09-07T08:36:08.1832026Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T08:36:08.1832339Z CUDA_PATH=/usr/local/cuda 2025-09-07T08:36:08.1832848Z GITHUB_ACTION_PATH=/home/charlie/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T08:36:08.1833443Z GITHUB_SERVER_URL=https://github.com 2025-09-07T08:36:08.1833849Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T08:36:08.1834239Z REENABLED_ISSUES= 2025-09-07T08:36:08.1834492Z DOCS= 2025-09-07T08:36:08.1834717Z SHLVL=1 2025-09-07T08:36:08.1834945Z MAX_JOBS=22 2025-09-07T08:36:08.1835186Z GITHUB_ACTOR_ID=97764156 2025-09-07T08:36:08.1835593Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.1836050Z GITHUB_REF_NAME=main 2025-09-07T08:36:08.1836507Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:36:08.1836992Z GITHUB_JOB=test 2025-09-07T08:36:08.1837246Z NO_TEST_TIMEOUT=False 2025-09-07T08:36:08.1837526Z TD_DISTRIBUTED=False 2025-09-07T08:36:08.1837830Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T08:36:08.1838170Z GITHUB_RETENTION_DAYS=90 2025-09-07T08:36:08.1838464Z OPENSSL_DIR=/opt/openssl 2025-09-07T08:36:08.1838766Z GITHUB_ACTION_REPOSITORY= 2025-09-07T08:36:08.1839655Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-09-07T08:36:08.1840719Z GITHUB_BASE_REF= 2025-09-07T08:36:08.1840980Z INSTALLED_ACL= 2025-09-07T08:36:08.1841490Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T08:36:08.1842082Z CI=true 2025-09-07T08:36:08.1842336Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T08:36:08.1842710Z RUST_LOG=sccache::server=error 2025-09-07T08:36:08.1843022Z JOB_ID=49775781854 2025-09-07T08:36:08.1843285Z GITHUB_HEAD_REF= 2025-09-07T08:36:08.1843548Z GITHUB_ACTION_REF= 2025-09-07T08:36:08.1843897Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T08:36:08.1844324Z TEST_SHOWLOCALS=False 2025-09-07T08:36:08.1844660Z GITHUB_WORKFLOW=inductor-perf-nightly-h100 2025-09-07T08:36:08.1845036Z DEBIAN_FRONTEND=noninteractive 2025-09-07T08:36:08.1845668Z GITHUB_OUTPUT=/home/charlie/_work/_temp/_runner_file_commands/set_output_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.1846310Z NO_TD=False 2025-09-07T08:36:08.1846576Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T08:36:08.1846921Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T08:36:08.1847276Z _=/usr/bin/env 2025-09-07T08:36:08.1847633Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-09-07T08:36:08.2075395Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch 2025-09-07T08:36:08.2076170Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/bin 2025-09-07T08:36:08.2076853Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/lib 2025-09-07T08:36:08.2077534Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/test 2025-09-07T08:36:08.2078062Z + BUILD_DIR=build 2025-09-07T08:36:08.2078357Z + BUILD_RENAMED_DIR=build_renamed 2025-09-07T08:36:08.2078697Z + BUILD_BIN_DIR=build/bin 2025-09-07T08:36:08.2079331Z + SHARD_NUMBER=9 2025-09-07T08:36:08.2079603Z + NUM_TEST_SHARDS=9 2025-09-07T08:36:08.2079903Z + export TORCH_SERIALIZATION_DEBUG=1 2025-09-07T08:36:08.2080443Z + TORCH_SERIALIZATION_DEBUG=1 2025-09-07T08:36:08.2080783Z + export VALGRIND=ON 2025-09-07T08:36:08.2081059Z + VALGRIND=ON 2025-09-07T08:36:08.2081419Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *clang9* ]] 2025-09-07T08:36:08.2081914Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *xpu* ]] 2025-09-07T08:36:08.2082590Z + detect_cuda_arch 2025-09-07T08:36:08.2082948Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T08:36:08.2083365Z + command -v nvidia-smi 2025-09-07T08:36:08.2083649Z /usr/bin/nvidia-smi 2025-09-07T08:36:08.2086745Z ++ nvidia-smi --query-gpu=compute_cap --format=csv 2025-09-07T08:36:08.2087409Z ++ tail -n 1 2025-09-07T08:36:08.2302124Z + TORCH_CUDA_ARCH_LIST=9.0 2025-09-07T08:36:08.2302434Z + export TORCH_CUDA_ARCH_LIST 2025-09-07T08:36:08.2302796Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *s390x* ]] 2025-09-07T08:36:08.2303242Z + [[ 0 == \1 ]] 2025-09-07T08:36:08.2303467Z + [[ True == \1 ]] 2025-09-07T08:36:08.2303761Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *bazel* ]] 2025-09-07T08:36:08.2307087Z ++ realpath build/custom_test_artifacts 2025-09-07T08:36:08.2317173Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-09-07T08:36:08.2317686Z + [[ -n '' ]] 2025-09-07T08:36:08.2317925Z + echo 'Environment variables' 2025-09-07T08:36:08.2318225Z Environment variables 2025-09-07T08:36:08.2318492Z + env 2025-09-07T08:36:08.2326474Z GITHUB_WORKSPACE=/home/charlie/_work/pytorch/pytorch 2025-09-07T08:36:08.2326894Z CONTINUE_THROUGH_ERROR=True 2025-09-07T08:36:08.2327252Z BUILD_ENVIRONMENT=linux-jammy-cuda12.8-py3.10-gcc9-sm90 2025-09-07T08:36:08.2327817Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-09-07T08:36:08.2328111Z HOSTNAME=541a5a68225e 2025-09-07T08:36:08.2328636Z GITHUB_PATH=/home/charlie/_work/_temp/_runner_file_commands/add_path_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.2329216Z GITHUB_ACTION=__run_2 2025-09-07T08:36:08.2329487Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-09-07T08:36:08.2329783Z GITHUB_RUN_NUMBER=662 2025-09-07T08:36:08.2330076Z TEST_CONFIG=inductor_torchbench_perf_cuda_h100 2025-09-07T08:36:08.2330604Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-09-07T08:36:08.2330933Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-09-07T08:36:08.2331243Z SCCACHE_IDLE_TIMEOUT=0 2025-09-07T08:36:08.2331635Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-09-07T08:36:08.2331959Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-09-07T08:36:08.2332280Z GITHUB_REF_TYPE=branch 2025-09-07T08:36:08.2332532Z TORCH_CUDA_ARCH_LIST=9.0 2025-09-07T08:36:08.2332832Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.2333163Z XLA_CUDA= 2025-09-07T08:36:08.2333388Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-09-07T08:36:08.2333810Z HUGGING_FACE_HUB_TOKEN=*** 2025-09-07T08:36:08.2334242Z *** 2025-09-07T08:36:08.2334458Z GITHUB_REPOSITORY_ID=65600975 2025-09-07T08:36:08.2334749Z GITHUB_ACTIONS=true 2025-09-07T08:36:08.2335012Z NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T08:36:08.2335359Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-09-07T08:36:08.2335761Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.2336140Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.2336812Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-h100.yml@refs/heads/main 2025-09-07T08:36:08.2337431Z UCC_HOME=/usr 2025-09-07T08:36:08.2337661Z TORCH_SERIALIZATION_DEBUG=1 2025-09-07T08:36:08.2337944Z VERBOSE_TEST_LOGS=False 2025-09-07T08:36:08.2338202Z GITHUB_REF=refs/heads/main 2025-09-07T08:36:08.2338459Z SHARD_NUMBER=9 2025-09-07T08:36:08.2338685Z GITHUB_REF_PROTECTED=true 2025-09-07T08:36:08.2338946Z HOME=/var/lib/jenkins 2025-09-07T08:36:08.2339229Z SCCACHE_SERVER_PORT=5229 2025-09-07T08:36:08.2339521Z GITHUB_API_URL=https://api.github.com 2025-09-07T08:36:08.2339853Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-09-07T08:36:08.2340191Z UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152 2025-09-07T08:36:08.2740665Z USE_SYSTEM_NCCL=1 2025-09-07T08:36:08.2740944Z NUM_TEST_SHARDS=9 2025-09-07T08:36:08.2741196Z UCX_HOME=/usr 2025-09-07T08:36:08.2741745Z GITHUB_STATE=/home/charlie/_work/_temp/_runner_file_commands/save_state_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.2742590Z JOB_NAME=test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T08:36:08.2743786Z GITHUB_ENV=/home/charlie/_work/_temp/_runner_file_commands/set_env_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.2744551Z GITHUB_EVENT_PATH=/home/charlie/_work/_temp/_github_workflow/event.json 2025-09-07T08:36:08.2745045Z GITHUB_EVENT_NAME=schedule 2025-09-07T08:36:08.2746497Z DASHBOARD_TAG=training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true 2025-09-07T08:36:08.2748056Z GITHUB_RUN_ID=17525296438 2025-09-07T08:36:08.2748367Z INSTALLED_OPENBLAS= 2025-09-07T08:36:08.2749078Z GITHUB_STEP_SUMMARY=/home/charlie/_work/_temp/_runner_file_commands/step_summary_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.2749850Z GITHUB_ACTOR=pytorchmergebot 2025-09-07T08:36:08.2750176Z PR_NUMBER= 2025-09-07T08:36:08.2750606Z DESIRED_CUDA=12.8.1 2025-09-07T08:36:08.2750892Z GITHUB_RUN_ATTEMPT=1 2025-09-07T08:36:08.2751173Z VALGRIND=ON 2025-09-07T08:36:08.2751467Z ANACONDA_PYTHON_VERSION=3.10 2025-09-07T08:36:08.2751859Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-09-07T08:36:08.2752275Z TERM=vt100 2025-09-07T08:36:08.2752522Z INSTALLED_VISION=yes 2025-09-07T08:36:08.2752799Z BRANCH=main 2025-09-07T08:36:08.2753059Z SCCACHE_REGION=us-east-1 2025-09-07T08:36:08.2753381Z OPENSSL_ROOT_DIR=/opt/openssl 2025-09-07T08:36:08.2753704Z CUDA_PATH=/usr/local/cuda 2025-09-07T08:36:08.2754288Z GITHUB_ACTION_PATH=/home/charlie/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-09-07T08:36:08.2754901Z GITHUB_SERVER_URL=https://github.com 2025-09-07T08:36:08.2755356Z UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96 2025-09-07T08:36:08.2755746Z REENABLED_ISSUES= 2025-09-07T08:36:08.2756008Z DOCS= 2025-09-07T08:36:08.2756239Z SHLVL=1 2025-09-07T08:36:08.2756470Z MAX_JOBS=22 2025-09-07T08:36:08.2756727Z GITHUB_ACTOR_ID=97764156 2025-09-07T08:36:08.2757122Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T08:36:08.2757557Z GITHUB_REF_NAME=main 2025-09-07T08:36:08.2758000Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-09-07T08:36:08.2758481Z GITHUB_JOB=test 2025-09-07T08:36:08.2758740Z NO_TEST_TIMEOUT=False 2025-09-07T08:36:08.2759029Z TD_DISTRIBUTED=False 2025-09-07T08:36:08.2759323Z GITHUB_REPOSITORY=pytorch/pytorch 2025-09-07T08:36:08.2759657Z GITHUB_RETENTION_DAYS=90 2025-09-07T08:36:08.2759954Z OPENSSL_DIR=/opt/openssl 2025-09-07T08:36:08.2760421Z GITHUB_ACTION_REPOSITORY= 2025-09-07T08:36:08.2761299Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-09-07T08:36:08.2762205Z GITHUB_BASE_REF= 2025-09-07T08:36:08.2762474Z INSTALLED_ACL= 2025-09-07T08:36:08.2762985Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T08:36:08.2763565Z CI=true 2025-09-07T08:36:08.2763807Z GITHUB_REPOSITORY_OWNER=pytorch 2025-09-07T08:36:08.2764160Z RUST_LOG=sccache::server=error 2025-09-07T08:36:08.2764476Z JOB_ID=49775781854 2025-09-07T08:36:08.2764728Z GITHUB_HEAD_REF= 2025-09-07T08:36:08.2764977Z GITHUB_ACTION_REF= 2025-09-07T08:36:08.2765306Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-09-07T08:36:08.2765698Z TEST_SHOWLOCALS=False 2025-09-07T08:36:08.2766018Z GITHUB_WORKFLOW=inductor-perf-nightly-h100 2025-09-07T08:36:08.2766398Z DEBIAN_FRONTEND=noninteractive 2025-09-07T08:36:08.2767038Z GITHUB_OUTPUT=/home/charlie/_work/_temp/_runner_file_commands/set_output_de7dd193-7aca-4227-9ca0-4003cc2430c6 2025-09-07T08:36:08.2767979Z NO_TD=False 2025-09-07T08:36:08.2768244Z SKIP_SCCACHE_INITIALIZATION=1 2025-09-07T08:36:08.2768592Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-09-07T08:36:08.2768945Z _=/usr/bin/env 2025-09-07T08:36:08.2769203Z + echo 'Testing pytorch' 2025-09-07T08:36:08.2769489Z Testing pytorch 2025-09-07T08:36:08.2769739Z + export LANG=C.UTF-8 2025-09-07T08:36:08.2770002Z + LANG=C.UTF-8 2025-09-07T08:36:08.2770404Z + PR_NUMBER= 2025-09-07T08:36:08.2770962Z + [[ inductor_torchbench_perf_cuda_h100 == \d\e\f\a\u\l\t ]] 2025-09-07T08:36:08.2771505Z + [[ inductor_torchbench_perf_cuda_h100 == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-09-07T08:36:08.2772020Z + [[ inductor_torchbench_perf_cuda_h100 == \s\l\o\w ]] 2025-09-07T08:36:08.2772534Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *slow-gradcheck* ]] 2025-09-07T08:36:08.2773050Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T08:36:08.2773482Z + export PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T08:36:08.2773875Z + PYTORCH_TESTING_DEVICE_ONLY_FOR=cuda 2025-09-07T08:36:08.2774300Z + [[ inductor_torchbench_perf_cuda_h100 == *crossref* ]] 2025-09-07T08:36:08.2774765Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:36:08.2775213Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *xpu* ]] 2025-09-07T08:36:08.2775691Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *-bazel-* ]] 2025-09-07T08:36:08.2776118Z + pip_install ninja==1.10.2 2025-09-07T08:36:08.2776546Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T08:36:08.2777078Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-09-07T08:36:08.7384624Z Collecting ninja==1.10.2 2025-09-07T08:36:08.7776824Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-09-07T08:36:09.1502553Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-09-07T08:36:10.4873681Z Installing collected packages: ninja 2025-09-07T08:36:10.4874037Z Attempting uninstall: ninja 2025-09-07T08:36:10.4882101Z Found existing installation: ninja 1.11.1.3 2025-09-07T08:36:10.4909156Z Uninstalling ninja-1.11.1.3: 2025-09-07T08:36:11.4032895Z Successfully uninstalled ninja-1.11.1.3 2025-09-07T08:36:12.7900551Z Successfully installed ninja-1.10.2 2025-09-07T08:36:12.8670880Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-09-07T08:36:12.8672770Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-09-07T08:36:12.8673956Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *aarch64* ]] 2025-09-07T08:36:12.8674482Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *asan* ]] 2025-09-07T08:36:12.8674964Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-debug* ]] 2025-09-07T08:36:12.8675455Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 != *-bazel-* ]] 2025-09-07T08:36:12.8676134Z + echo 'We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm90. Expect the assertion to pass' 2025-09-07T08:36:12.8676990Z We are not in debug mode: linux-jammy-cuda12.8-py3.10-gcc9-sm90. Expect the assertion to pass 2025-09-07T08:36:12.8677563Z + cd test 2025-09-07T08:36:12.8677978Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-09-07T08:36:13.3453126Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:13.3454523Z import pynvml # type: ignore[import] 2025-09-07T08:36:14.9424397Z + [[ inductor_torchbench_perf_cuda_h100 == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-09-07T08:36:14.9424929Z + [[ inductor_torchbench_perf_cuda_h100 == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-09-07T08:36:14.9425889Z + [[ inductor_torchbench_perf_cuda_h100 == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-09-07T08:36:14.9427323Z + DYNAMO_BENCHMARK_FLAGS=() 2025-09-07T08:36:14.9427835Z + [[ inductor_torchbench_perf_cuda_h100 == *pr_time_benchmarks* ]] 2025-09-07T08:36:14.9428245Z + [[ inductor_torchbench_perf_cuda_h100 == *dynamo_eager* ]] 2025-09-07T08:36:14.9428632Z + [[ inductor_torchbench_perf_cuda_h100 == *aot_eager* ]] 2025-09-07T08:36:14.9429245Z + [[ inductor_torchbench_perf_cuda_h100 == *aot_inductor* ]] 2025-09-07T08:36:14.9429654Z + [[ inductor_torchbench_perf_cuda_h100 == *max_autotune_inductor* ]] 2025-09-07T08:36:14.9430041Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor* ]] 2025-09-07T08:36:14.9430724Z + [[ inductor_torchbench_perf_cuda_h100 != *perf* ]] 2025-09-07T08:36:14.9431063Z + [[ inductor_torchbench_perf_cuda_h100 == *dynamic* ]] 2025-09-07T08:36:14.9431386Z + [[ inductor_torchbench_perf_cuda_h100 == *cpu* ]] 2025-09-07T08:36:14.9431717Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-09-07T08:36:14.9446961Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *libtorch* ]] 2025-09-07T08:36:14.9447303Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *-bazel-* ]] 2025-09-07T08:36:14.9450990Z + cd test 2025-09-07T08:36:14.9451600Z + python -c 'import torch; print(torch.__config__.show())' 2025-09-07T08:36:15.4256580Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:15.4258494Z import pynvml # type: ignore[import] 2025-09-07T08:36:16.9021479Z PyTorch built with: 2025-09-07T08:36:16.9021753Z - GCC 9.5 2025-09-07T08:36:16.9021973Z - C++ Version: 201703 2025-09-07T08:36:16.9022497Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T08:36:16.9023295Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T08:36:16.9023700Z - OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T08:36:16.9024006Z - LAPACK is enabled (usually provided by MKL) 2025-09-07T08:36:16.9024299Z - NNPACK is enabled 2025-09-07T08:36:16.9024534Z - CPU capability usage: AVX2 2025-09-07T08:36:16.9024781Z - CUDA Runtime 12.8 2025-09-07T08:36:16.9025109Z - NVCC architecture flags: -gencode;arch=compute_90,code=sm_90 2025-09-07T08:36:16.9025458Z - CuDNN 90.8 2025-09-07T08:36:16.9029675Z - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=93fb23d6fae7c4e82c4239a1033e522088742634, CUDA_VERSION=12.8, CUDNN_VERSION=9.8.0, CXX_COMPILER=/opt/cache/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wno-stringop-overflow -Wsuggest-override -Wno-psabi -Wno-error=old-style-cast -faligned-new -Werror -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, FORCE_FALLBACK_CUDA_MPI=1, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.9.0, USE_CUDA=ON, USE_CUDNN=ON, USE_CUSPARSELT=ON, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=ON, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 2025-09-07T08:36:16.9034029Z 2025-09-07T08:36:19.5549931Z + cd test 2025-09-07T08:36:19.5550625Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-09-07T08:36:20.0543870Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:20.0546457Z import pynvml # type: ignore[import] 2025-09-07T08:36:20.8474809Z ATen/Parallel: 2025-09-07T08:36:20.8475102Z at::get_num_threads() : 24 2025-09-07T08:36:20.8475391Z at::get_num_interop_threads() : 96 2025-09-07T08:36:20.8476061Z OpenMP 201511 (a.k.a. OpenMP 4.5) 2025-09-07T08:36:20.8476327Z omp_get_max_threads() : 24 2025-09-07T08:36:20.8476830Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-09-07T08:36:20.8477361Z mkl_get_max_threads() : 24 2025-09-07T08:36:20.8477696Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-09-07T08:36:20.8478082Z std::thread::hardware_concurrency() : 192 2025-09-07T08:36:20.8478358Z Environment variables: 2025-09-07T08:36:20.8478583Z OMP_NUM_THREADS : [not set] 2025-09-07T08:36:20.8478830Z MKL_NUM_THREADS : [not set] 2025-09-07T08:36:20.8479073Z ATen parallel backend: OpenMP 2025-09-07T08:36:20.8479236Z 2025-09-07T08:36:21.1472965Z + [[ inductor_torchbench_perf_cuda_h100 == *numpy_2* ]] 2025-09-07T08:36:21.1473480Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *aarch64* ]] 2025-09-07T08:36:21.1473875Z + [[ inductor_torchbench_perf_cuda_h100 == *backward* ]] 2025-09-07T08:36:21.1474242Z + [[ inductor_torchbench_perf_cuda_h100 == *xla* ]] 2025-09-07T08:36:21.1474581Z + [[ inductor_torchbench_perf_cuda_h100 == *vllm* ]] 2025-09-07T08:36:21.1474918Z + [[ inductor_torchbench_perf_cuda_h100 == *executorch* ]] 2025-09-07T08:36:21.1475322Z + [[ inductor_torchbench_perf_cuda_h100 == \j\i\t\_\l\e\g\a\c\y ]] 2025-09-07T08:36:21.1475721Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *libtorch* ]] 2025-09-07T08:36:21.1476092Z + [[ inductor_torchbench_perf_cuda_h100 == distributed ]] 2025-09-07T08:36:21.1476470Z + [[ inductor_torchbench_perf_cuda_h100 == *operator_benchmark* ]] 2025-09-07T08:36:21.1476899Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_distributed* ]] 2025-09-07T08:36:21.1477317Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-halide* ]] 2025-09-07T08:36:21.1477749Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-triton-cpu* ]] 2025-09-07T08:36:21.1478202Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor-micro-benchmark* ]] 2025-09-07T08:36:21.1478623Z + [[ inductor_torchbench_perf_cuda_h100 == *huggingface* ]] 2025-09-07T08:36:21.1478967Z + [[ inductor_torchbench_perf_cuda_h100 == *timm* ]] 2025-09-07T08:36:21.1479302Z + [[ inductor_torchbench_perf_cuda_h100 == cachebench ]] 2025-09-07T08:36:21.1479679Z + [[ inductor_torchbench_perf_cuda_h100 == verify_cachebench ]] 2025-09-07T08:36:21.1480056Z + [[ inductor_torchbench_perf_cuda_h100 == *torchbench* ]] 2025-09-07T08:36:21.1480598Z + install_torchaudio 2025-09-07T08:36:21.1480804Z + local commit 2025-09-07T08:36:21.1481018Z ++ get_pinned_commit audio 2025-09-07T08:36:21.1481260Z ++ cat .github/ci_commit_pins/audio.txt 2025-09-07T08:36:21.1496304Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T08:36:21.1497576Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio 2025-09-07T08:36:21.1498337Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 2025-09-07T08:36:21.1498798Z + local wheel_dir=dist/audio 2025-09-07T08:36:21.1499049Z + local found_whl=0 2025-09-07T08:36:21.1499279Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:21.1499648Z + [[ -f dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T08:36:21.1500003Z + found_whl=1 2025-09-07T08:36:21.1500168Z + break 2025-09-07T08:36:21.1500494Z + '[' 1 == 0 ']' 2025-09-07T08:36:21.1500687Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:21.1501065Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.1501575Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl') 2025-09-07T08:36:21.1502441Z + local args 2025-09-07T08:36:21.1502747Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T08:36:21.1503255Z + for path in "${args[@]}" 2025-09-07T08:36:21.1503610Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl' 2025-09-07T08:36:21.1504386Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.1504994Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.4932466Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:21.4992505Z Installing collected packages: torchaudio 2025-09-07T08:36:23.7983816Z Successfully installed torchaudio-2.8.0a0+2e30055 2025-09-07T08:36:23.8284359Z + install_torchvision 2025-09-07T08:36:23.8284788Z + local orig_preload 2025-09-07T08:36:23.8285186Z + local commit 2025-09-07T08:36:23.8289390Z ++ get_pinned_commit vision 2025-09-07T08:36:23.8289831Z ++ cat .github/ci_commit_pins/vision.txt 2025-09-07T08:36:23.8303666Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T08:36:23.8303949Z + orig_preload= 2025-09-07T08:36:23.8304139Z + '[' -n '' ']' 2025-09-07T08:36:23.8304395Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *cuda* ]] 2025-09-07T08:36:23.8304684Z + export FORCE_CUDA=1 2025-09-07T08:36:23.8304890Z + FORCE_CUDA=1 2025-09-07T08:36:23.8305067Z + export WITH_CUDA=1 2025-09-07T08:36:23.8305245Z + WITH_CUDA=1 2025-09-07T08:36:23.8305710Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-09-07T08:36:23.8306437Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-09-07T08:36:23.8306921Z + local wheel_dir=dist/vision 2025-09-07T08:36:23.8307136Z + local found_whl=0 2025-09-07T08:36:23.8307336Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:23.8307712Z + [[ -f dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T08:36:23.8308075Z + found_whl=1 2025-09-07T08:36:23.8308251Z + break 2025-09-07T08:36:23.8308398Z + '[' 1 == 0 ']' 2025-09-07T08:36:23.8308586Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:23.8308986Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:23.8309518Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl') 2025-09-07T08:36:23.8309872Z + local args 2025-09-07T08:36:23.8310190Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T08:36:23.8310824Z + for path in "${args[@]}" 2025-09-07T08:36:23.8311236Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl' 2025-09-07T08:36:23.8311815Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:23.8312486Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:24.1739856Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:24.1826698Z Installing collected packages: torchvision 2025-09-07T08:36:25.4926409Z Successfully installed torchvision-0.22.0a0+966da7e 2025-09-07T08:36:25.5300044Z + '[' -n '' ']' 2025-09-07T08:36:25.5300674Z + id=8 2025-09-07T08:36:25.5300932Z + pip_install opencv-python==4.8.0.74 2025-09-07T08:36:25.5301339Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T08:36:25.5301797Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74 2025-09-07T08:36:26.6735727Z Collecting opencv-python==4.8.0.74 2025-09-07T08:36:26.7154051Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB) 2025-09-07T08:36:27.9145113Z Requirement already satisfied: numpy>=1.21.2 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from opencv-python==4.8.0.74) (1.22.4) 2025-09-07T08:36:27.9279238Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB) 2025-09-07T08:36:31.8529008Z Installing collected packages: opencv-python 2025-09-07T08:36:31.8529447Z Attempting uninstall: opencv-python 2025-09-07T08:36:31.8539025Z Found existing installation: opencv-python 4.11.0.86 2025-09-07T08:36:31.8624632Z Uninstalling opencv-python-4.11.0.86: 2025-09-07T08:36:32.0260970Z Successfully uninstalled opencv-python-4.11.0.86 2025-09-07T08:36:33.8747807Z Successfully installed opencv-python-4.8.0.74 2025-09-07T08:36:33.9628990Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_torchbench_smoketest_perf* ]] 2025-09-07T08:36:33.9629854Z + [[ inductor_torchbench_perf_cuda_h100 == *inductor_torchbench_cpu_smoketest_perf* ]] 2025-09-07T08:36:33.9631342Z + [[ inductor_torchbench_perf_cuda_h100 == *torchbench_gcp_smoketest* ]] 2025-09-07T08:36:33.9631959Z + [[ inductor_torchbench_perf_cuda_h100 != *cpu* ]] 2025-09-07T08:36:33.9632483Z + install_torchrec_and_fbgemm 2025-09-07T08:36:33.9632856Z + local torchrec_commit 2025-09-07T08:36:33.9634174Z ++ get_pinned_commit torchrec 2025-09-07T08:36:33.9634644Z ++ cat .github/ci_commit_pins/torchrec.txt 2025-09-07T08:36:33.9648031Z + torchrec_commit=6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T08:36:33.9648351Z + local fbgemm_commit 2025-09-07T08:36:33.9651983Z ++ get_pinned_commit fbgemm 2025-09-07T08:36:33.9652260Z ++ cat .github/ci_commit_pins/fbgemm.txt 2025-09-07T08:36:33.9663554Z + fbgemm_commit=de731af65b4f04696e85c729e3282450b51b95fd 2025-09-07T08:36:33.9663896Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:36:33.9664199Z + pip_uninstall torchrec-nightly 2025-09-07T08:36:33.9664456Z + pip3 uninstall -y torchrec-nightly 2025-09-07T08:36:34.3181928Z WARNING: Skipping torchrec-nightly as it is not installed. 2025-09-07T08:36:34.3481054Z + pip_uninstall fbgemm-gpu-nightly 2025-09-07T08:36:34.3481384Z + pip3 uninstall -y fbgemm-gpu-nightly 2025-09-07T08:36:34.7016189Z WARNING: Skipping fbgemm-gpu-nightly as it is not installed. 2025-09-07T08:36:34.7343531Z + pip_install setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T08:36:34.7344089Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-09-07T08:36:34.7344658Z + python3 -m pip install --progress-bar off setuptools-git-versioning scikit-build pyre-extensions 2025-09-07T08:36:35.0688530Z Requirement already satisfied: setuptools-git-versioning in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (2.1.0) 2025-09-07T08:36:35.0689907Z Requirement already satisfied: scikit-build in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.18.1) 2025-09-07T08:36:35.0691641Z Requirement already satisfied: pyre-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (0.0.32) 2025-09-07T08:36:35.0702545Z Requirement already satisfied: packaging in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (25.0) 2025-09-07T08:36:35.0705555Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (80.9.0) 2025-09-07T08:36:35.0711854Z Requirement already satisfied: tomli>=2.0.1 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from setuptools-git-versioning) (2.2.1) 2025-09-07T08:36:35.0752441Z Requirement already satisfied: distro in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (1.9.0) 2025-09-07T08:36:35.0760011Z Requirement already satisfied: wheel>=0.32.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from scikit-build) (0.45.1) 2025-09-07T08:36:35.0767370Z Requirement already satisfied: typing-inspect in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (0.9.0) 2025-09-07T08:36:35.0770158Z Requirement already satisfied: typing-extensions in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from pyre-extensions) (4.15.0) 2025-09-07T08:36:35.0845529Z Requirement already satisfied: mypy-extensions>=0.3.0 in /opt/conda/envs/py_3.10/lib/python3.10/site-packages (from typing-inspect->pyre-extensions) (1.1.0) 2025-09-07T08:36:35.9593583Z + [[ linux-jammy-cuda12.8-py3.10-gcc9-sm90 == *rocm* ]] 2025-09-07T08:36:35.9594952Z + pip_build_and_install git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 dist/torchrec 2025-09-07T08:36:35.9596669Z + local build_target=git+https://github.com/pytorch/torchrec.git@6cd9fd362514d14ebb9ed51314c62ac1e1e2bbf2 2025-09-07T08:36:35.9597206Z + local wheel_dir=dist/torchrec 2025-09-07T08:36:35.9597454Z + local found_whl=0 2025-09-07T08:36:35.9597667Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:35.9597980Z + [[ -f dist/torchrec/torchrec-0.3.2-py3-none-any.whl ]] 2025-09-07T08:36:35.9598278Z + found_whl=1 2025-09-07T08:36:35.9598466Z + break 2025-09-07T08:36:35.9598632Z + '[' 1 == 0 ']' 2025-09-07T08:36:35.9598853Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:35.9599194Z + pip_install_whl dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:35.9599600Z + args=('dist/torchrec/torchrec-0.3.2-py3-none-any.whl') 2025-09-07T08:36:35.9599913Z + local args 2025-09-07T08:36:35.9600176Z + [[ dist/torchrec/torchrec-0.3.2-py3-none-any.whl == *\ * ]] 2025-09-07T08:36:35.9600935Z + for path in "${args[@]}" 2025-09-07T08:36:35.9601267Z + echo 'Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl' 2025-09-07T08:36:35.9601698Z Installing dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:35.9602192Z + python3 -mpip install --no-index --no-deps dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:36.2987870Z Processing ./dist/torchrec/torchrec-0.3.2-py3-none-any.whl 2025-09-07T08:36:36.3047059Z Installing collected packages: torchrec 2025-09-07T08:36:37.5423972Z Successfully installed torchrec-0.3.2 2025-09-07T08:36:37.5756336Z + pip_build_and_install git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu dist/fbgemm_gpu 2025-09-07T08:36:37.5757399Z + local build_target=git+https://github.com/pytorch/FBGEMM.git@de731af65b4f04696e85c729e3282450b51b95fd#subdirectory=fbgemm_gpu 2025-09-07T08:36:37.5757993Z + local wheel_dir=dist/fbgemm_gpu 2025-09-07T08:36:37.5758238Z + local found_whl=0 2025-09-07T08:36:37.5758478Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:37.5758866Z + [[ -f dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl ]] 2025-09-07T08:36:37.5759272Z + found_whl=1 2025-09-07T08:36:37.5759453Z + break 2025-09-07T08:36:37.5759620Z + '[' 1 == 0 ']' 2025-09-07T08:36:37.5759834Z + for file in "${wheel_dir}"/*.whl 2025-09-07T08:36:37.5760648Z + pip_install_whl dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:37.5761221Z + args=('dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl') 2025-09-07T08:36:37.5761610Z + local args 2025-09-07T08:36:37.5761946Z + [[ dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl == *\ * ]] 2025-09-07T08:36:37.5762371Z + for path in "${args[@]}" 2025-09-07T08:36:37.5762772Z + echo 'Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl' 2025-09-07T08:36:37.5763348Z Installing dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:37.5763998Z + python3 -mpip install --no-index --no-deps dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:37.9166455Z Processing ./dist/fbgemm_gpu/fbgemm_gpu-0.4.1.post421-cp310-cp310-linux_x86_64.whl 2025-09-07T08:36:38.0097730Z Installing collected packages: fbgemm-gpu 2025-09-07T08:36:39.8926345Z Successfully installed fbgemm-gpu-0.4.1.post421 2025-09-07T08:36:39.9221041Z + PYTHONPATH=/torchbench 2025-09-07T08:36:39.9231737Z + test_dynamo_benchmark torchbench 8 2025-09-07T08:36:39.9232135Z ++ pwd 2025-09-07T08:36:39.9232460Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:39.9232852Z + local suite=torchbench 2025-09-07T08:36:39.9233608Z + shift 2025-09-07T08:36:39.9233794Z + local shard_id=8 2025-09-07T08:36:39.9234008Z + shift 2025-09-07T08:36:39.9234276Z + [[ inductor_torchbench_perf_cuda_h100 == *perf_compare* ]] 2025-09-07T08:36:39.9234674Z + [[ inductor_torchbench_perf_cuda_h100 == *perf* ]] 2025-09-07T08:36:39.9235024Z + [[ inductor_torchbench_perf_cuda_h100 == *b200* ]] 2025-09-07T08:36:39.9235391Z + test_single_dynamo_benchmark dashboard torchbench 8 2025-09-07T08:36:39.9236166Z ++ pwd 2025-09-07T08:36:39.9239218Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:39.9239899Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:39.9260194Z + local name=dashboard 2025-09-07T08:36:39.9260753Z + shift 2025-09-07T08:36:39.9261038Z + local suite=torchbench 2025-09-07T08:36:39.9261375Z + shift 2025-09-07T08:36:39.9261630Z + local shard_id=8 2025-09-07T08:36:39.9261907Z + shift 2025-09-07T08:36:39.9262156Z + partition_flags=() 2025-09-07T08:36:39.9262470Z + local partition_flags 2025-09-07T08:36:39.9262781Z + [[ -n 9 ]] 2025-09-07T08:36:39.9263114Z + [[ -n 8 ]] 2025-09-07T08:36:39.9263623Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id") 2025-09-07T08:36:39.9264378Z + [[ inductor_torchbench_perf_cuda_h100 == *perf_compare* ]] 2025-09-07T08:36:39.9264927Z + [[ inductor_torchbench_perf_cuda_h100 == *perf* ]] 2025-09-07T08:36:39.9265656Z + test_perf_for_dashboard torchbench --device cuda --total-partitions 9 --partition-id 8 2025-09-07T08:36:39.9266314Z ++ pwd 2025-09-07T08:36:39.9266726Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:39.9267327Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports 2025-09-07T08:36:39.9281693Z + local suite=torchbench 2025-09-07T08:36:39.9282067Z + shift 2025-09-07T08:36:39.9282366Z + local backend=inductor 2025-09-07T08:36:39.9282695Z + modes=() 2025-09-07T08:36:39.9282953Z + local modes 2025-09-07T08:36:39.9284574Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *training-true* ]] 2025-09-07T08:36:39.9286343Z + modes+=(training) 2025-09-07T08:36:39.9288003Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *inference-true* ]] 2025-09-07T08:36:39.9289691Z + modes+=(inference) 2025-09-07T08:36:39.9290029Z + targets=('accuracy' 'performance') 2025-09-07T08:36:39.9290616Z + local targets 2025-09-07T08:36:39.9290894Z + local device=cuda 2025-09-07T08:36:39.9291250Z + [[ inductor_torchbench_perf_cuda_h100 == *cpu* ]] 2025-09-07T08:36:39.9291780Z + [[ inductor_torchbench_perf_cuda_h100 == *cuda_a10g* ]] 2025-09-07T08:36:39.9292298Z + [[ inductor_torchbench_perf_cuda_h100 == *h100* ]] 2025-09-07T08:36:39.9292730Z + device=cuda_h100 2025-09-07T08:36:39.9293060Z + for mode in "${modes[@]}" 2025-09-07T08:36:39.9293413Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T08:36:39.9293796Z + [[ training == \t\r\a\i\n\i\n\g ]] 2025-09-07T08:36:39.9294137Z + dtype=amp 2025-09-07T08:36:39.9294423Z + for target in "${targets[@]}" 2025-09-07T08:36:39.9294784Z + target_flag=('--accuracy') 2025-09-07T08:36:39.9295136Z + local target_flag 2025-09-07T08:36:39.9295457Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T08:36:39.9295854Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T08:36:39.9296248Z + target_flag+=(--no-translation-validation) 2025-09-07T08:36:39.9297926Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing-true* ]] 2025-09-07T08:36:39.9301064Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *default-true* ]] 2025-09-07T08:36:39.9304534Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:36:40.4250862Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:40.4253291Z import pynvml # type: ignore[import] 2025-09-07T08:36:44.2673528Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:36:44.2674775Z import pynvml # type: ignore[import] 2025-09-07T08:36:46.6970949Z 2025-09-07T08:36:48.3027366Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:36:48.3027611Z 2025-09-07T08:36:48.3028083Z scheduler_config.json: 0% 0.00/345 [00:00 will be ignored 2025-09-07T08:42:13.1556251Z pass 2025-09-07T08:42:18.3787918Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:42:18.3789736Z import pynvml # type: ignore[import] 2025-09-07T08:42:20.8894688Z 2025-09-07T08:42:22.7190379Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:42:22.7190747Z 2025-09-07T08:42:22.8446259Z model.safetensors: 0% 0.00/286M [00:00 will be ignored 2025-09-07T08:44:21.1378780Z W0907 08:44:21.137000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1384694Z W0907 08:44:21.138000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1391426Z W0907 08:44:21.138000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1397208Z W0907 08:44:21.139000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1403369Z W0907 08:44:21.140000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1409554Z W0907 08:44:21.140000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1415884Z W0907 08:44:21.141000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1422109Z W0907 08:44:21.141000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1428281Z W0907 08:44:21.142000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1442345Z W0907 08:44:21.143000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1448200Z W0907 08:44:21.144000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1454651Z W0907 08:44:21.145000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1460697Z W0907 08:44:21.145000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1466834Z W0907 08:44:21.146000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1473405Z W0907 08:44:21.147000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1479216Z W0907 08:44:21.147000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1485364Z W0907 08:44:21.148000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1491744Z W0907 08:44:21.148000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1497605Z W0907 08:44:21.149000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1504034Z W0907 08:44:21.150000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1514010Z W0907 08:44:21.151000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1519761Z W0907 08:44:21.151000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1527202Z W0907 08:44:21.152000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1533006Z W0907 08:44:21.153000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1538735Z W0907 08:44:21.153000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1545323Z W0907 08:44:21.154000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1551571Z W0907 08:44:21.154000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1557440Z W0907 08:44:21.155000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1564195Z W0907 08:44:21.156000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1570114Z W0907 08:44:21.156000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1576171Z W0907 08:44:21.157000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1582611Z W0907 08:44:21.157000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1588756Z W0907 08:44:21.158000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1595037Z W0907 08:44:21.159000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1604783Z W0907 08:44:21.160000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1610721Z W0907 08:44:21.160000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.1617142Z W0907 08:44:21.161000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2036216Z W0907 08:44:21.203000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2042846Z W0907 08:44:21.203000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2049272Z W0907 08:44:21.204000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2056026Z W0907 08:44:21.205000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2062400Z W0907 08:44:21.205000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2068965Z W0907 08:44:21.206000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2075630Z W0907 08:44:21.207000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2082084Z W0907 08:44:21.207000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2088580Z W0907 08:44:21.208000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2102486Z W0907 08:44:21.209000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2108841Z W0907 08:44:21.210000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2115763Z W0907 08:44:21.211000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2122080Z W0907 08:44:21.211000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2128312Z W0907 08:44:21.212000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2135164Z W0907 08:44:21.213000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2141748Z W0907 08:44:21.213000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2148176Z W0907 08:44:21.214000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2155022Z W0907 08:44:21.215000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2161420Z W0907 08:44:21.215000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2167828Z W0907 08:44:21.216000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2178151Z W0907 08:44:21.217000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2184774Z W0907 08:44:21.218000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2191683Z W0907 08:44:21.218000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2198099Z W0907 08:44:21.219000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2204561Z W0907 08:44:21.220000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2211397Z W0907 08:44:21.220000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2217653Z W0907 08:44:21.221000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2224341Z W0907 08:44:21.222000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2231026Z W0907 08:44:21.222000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2237481Z W0907 08:44:21.223000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2243808Z W0907 08:44:21.224000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2250548Z W0907 08:44:21.224000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2256987Z W0907 08:44:21.225000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2263683Z W0907 08:44:21.226000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2273832Z W0907 08:44:21.227000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2279986Z W0907 08:44:21.227000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.2286931Z W0907 08:44:21.228000 13450 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:44:21.3630172Z pass 2025-09-07T08:44:26.7077419Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:44:26.7078489Z import pynvml # type: ignore[import] 2025-09-07T08:44:29.1957302Z 2025-09-07T08:44:30.5256862Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:44:30.5257146Z 2025-09-07T08:44:30.6475166Z model.safetensors: 0% 0.00/42.6M [00:00 will be ignored 2025-09-07T08:47:55.0077168Z pass 2025-09-07T08:48:01.0992896Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:48:01.0994098Z import pynvml # type: ignore[import] 2025-09-07T08:48:03.5766140Z 2025-09-07T08:48:04.4226428Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:48:04.4226811Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:48:04.4227114Z cuda train tts_angular 2025-09-07T08:48:07.6903523Z W0907 08:48:07.689000 21272 site-packages/torch/_logging/_internal.py:1199] [10/0] Profiler function will be ignored 2025-09-07T08:48:11.2608548Z pass 2025-09-07T08:48:14.0323046Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:48:14.0324941Z import pynvml # type: ignore[import] 2025-09-07T08:48:16.6138708Z 2025-09-07T08:48:17.5572977Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/vgg16-397923af.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/vgg16-397923af.pth 2025-09-07T08:48:17.5743892Z 2025-09-07T08:48:17.5743899Z 2025-09-07T08:48:17.7560553Z 0% 0.00/528M [00:00 2025-09-07T08:50:30.7828873Z W0907 08:50:30.780000 22856 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T08:50:30.7829801Z W0907 08:50:30.780000 22856 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T08:50:30.7830826Z W0907 08:50:30.780000 22856 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T08:50:30.7831439Z W0907 08:50:30.780000 22856 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T08:50:30.7831889Z W0907 08:50:30.780000 22856 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T08:51:08.1363336Z W0907 08:51:08.135000 22856 site-packages/torch/fx/experimental/symbolic_shapes.py:2396] [30/2] RecursionError in sympy.xreplace(Eq(Mod(2*s29, s93), 0), {s29: evaluate_static_shape_0 + 1, s93: evaluate_static_shape_1 + 1}) 2025-09-07T08:51:39.7394410Z W0907 08:51:39.738000 22856 site-packages/torch/_logging/_internal.py:1199] [51/0] Profiler function will be ignored 2025-09-07T08:52:08.0479125Z W0907 08:52:08.047000 22856 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:52:08.0733951Z W0907 08:52:08.072000 22856 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T08:52:08.2270545Z pass 2025-09-07T08:52:13.2398280Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:52:13.2442129Z import pynvml # type: ignore[import] 2025-09-07T08:52:16.0206783Z 2025-09-07T08:52:19.9708861Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:52:19.9709246Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:52:19.9709553Z cuda train yolov3 2025-09-07T08:53:23.7536988Z W0907 08:53:23.752000 28345 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T08:53:57.7480661Z pass 2025-09-07T08:54:02.8932149Z accuracy pass_rate=86.67% 2025-09-07T08:54:02.8938594Z calls_captured gmean=0.00x mean=834.133x 2025-09-07T08:54:02.8943849Z unique_graphs gmean=0.00x mean=6.000x 2025-09-07T08:54:02.8948715Z graph_breaks gmean=0.00x mean=8.600x 2025-09-07T08:54:02.8954625Z unique_graph_breaks gmean=0.00x mean=4.733x 2025-09-07T08:54:02.8959623Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T08:54:02.8964600Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T08:54:02.8969458Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T08:54:02.8972444Z compilation_latency mean=49.656 seconds 2025-09-07T08:54:03.9353496Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs-true* ]] 2025-09-07T08:54:03.9356286Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T08:54:04.4356729Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:54:04.4359093Z import pynvml # type: ignore[import] 2025-09-07T08:54:08.1644179Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:54:08.1645469Z import pynvml # type: ignore[import] 2025-09-07T08:54:10.6743629Z 2025-09-07T08:54:12.3524447Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:54:12.3524867Z 2025-09-07T08:54:13.2024568Z Loading pipeline components...: 0% 0/6 [00:00 will be ignored 2025-09-07T08:59:11.8186546Z pass 2025-09-07T08:59:17.1822118Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T08:59:17.1825248Z import pynvml # type: ignore[import] 2025-09-07T08:59:19.6773219Z 2025-09-07T08:59:23.1794217Z loading model: 0it [00:00, ?it/s] 2025-09-07T08:59:23.1794623Z loading model: 0it [00:03, ?it/s] 2025-09-07T08:59:23.1794928Z cuda train timm_nfnet 2025-09-07T09:00:00.1157908Z pass 2025-09-07T09:00:04.2458519Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:00:04.2460571Z import pynvml # type: ignore[import] 2025-09-07T09:00:06.7211620Z 2025-09-07T09:00:10.0443215Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:00:10.0443569Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:00:10.0443866Z cuda train timm_regnet 2025-09-07T09:00:41.1612079Z W0907 09:00:41.160000 32551 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:01:16.0811346Z W0907 09:01:16.080000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0818540Z W0907 09:01:16.081000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0831471Z W0907 09:01:16.082000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0837121Z W0907 09:01:16.083000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0843348Z W0907 09:01:16.084000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0852519Z W0907 09:01:16.084000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0856562Z W0907 09:01:16.085000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0862591Z W0907 09:01:16.085000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0868869Z W0907 09:01:16.086000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0882865Z W0907 09:01:16.087000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0888853Z W0907 09:01:16.088000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0895203Z W0907 09:01:16.089000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.0901402Z W0907 09:01:16.089000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1255879Z W0907 09:01:16.090000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1257194Z W0907 09:01:16.091000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1258940Z W0907 09:01:16.091000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1260469Z W0907 09:01:16.092000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1261783Z W0907 09:01:16.092000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1263120Z W0907 09:01:16.093000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1264388Z W0907 09:01:16.094000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1265669Z W0907 09:01:16.095000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1266940Z W0907 09:01:16.095000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1268226Z W0907 09:01:16.096000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1269519Z W0907 09:01:16.097000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1270973Z W0907 09:01:16.097000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1272243Z W0907 09:01:16.098000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1429498Z W0907 09:01:16.142000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1435691Z W0907 09:01:16.143000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1442685Z W0907 09:01:16.143000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1448998Z W0907 09:01:16.144000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1455699Z W0907 09:01:16.145000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1462368Z W0907 09:01:16.145000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1469056Z W0907 09:01:16.146000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1475679Z W0907 09:01:16.147000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1482258Z W0907 09:01:16.147000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1496260Z W0907 09:01:16.149000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1503072Z W0907 09:01:16.149000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1509625Z W0907 09:01:16.150000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1946495Z W0907 09:01:16.151000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1947813Z W0907 09:01:16.151000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1949439Z W0907 09:01:16.152000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1951187Z W0907 09:01:16.153000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1952474Z W0907 09:01:16.153000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1953741Z W0907 09:01:16.154000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1954990Z W0907 09:01:16.155000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1956273Z W0907 09:01:16.155000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1957540Z W0907 09:01:16.156000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1958831Z W0907 09:01:16.157000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1960102Z W0907 09:01:16.158000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1961580Z W0907 09:01:16.158000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1962824Z W0907 09:01:16.159000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1964103Z W0907 09:01:16.160000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.1965366Z W0907 09:01:16.162000 32551 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:01:16.2969581Z pass 2025-09-07T09:01:21.8332369Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:01:21.8333638Z import pynvml # type: ignore[import] 2025-09-07T09:01:24.3080588Z 2025-09-07T09:01:26.9763162Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:01:26.9763660Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:01:26.9764089Z cuda train timm_resnest 2025-09-07T09:01:53.2828032Z pass 2025-09-07T09:01:56.6639230Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:01:56.6641684Z import pynvml # type: ignore[import] 2025-09-07T09:01:59.7171519Z 2025-09-07T09:02:02.3196923Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:02:02.3197277Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:02:02.3197575Z cuda train timm_vision_transformer 2025-09-07T09:02:22.3131976Z pass 2025-09-07T09:02:25.6231805Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:02:25.6233715Z import pynvml # type: ignore[import] 2025-09-07T09:02:28.2489904Z 2025-09-07T09:02:39.9451654Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:02:39.9452033Z loading model: 0it [00:11, ?it/s] 2025-09-07T09:02:39.9452395Z cuda train timm_vision_transformer_large 2025-09-07T09:02:40.2556350Z pass_due_to_skip 2025-09-07T09:02:42.2419204Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:02:42.2421281Z import pynvml # type: ignore[import] 2025-09-07T09:02:44.8466723Z 2025-09-07T09:02:47.9459298Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:02:47.9459664Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:02:47.9459961Z cuda train timm_vovnet 2025-09-07T09:03:13.6943573Z pass 2025-09-07T09:03:17.4172197Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:03:17.4173571Z import pynvml # type: ignore[import] 2025-09-07T09:03:19.9253862Z 2025-09-07T09:03:22.7448930Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:03:22.7449333Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:03:22.7449644Z cuda train torch_multimodal_clip 2025-09-07T09:04:03.1411969Z 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 2025-09-07T09:04:03.1413589Z pred = mod(*cloned_inputs) 2025-09-07T09:04:03.1414427Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchmultimodal/models/clip/model.py", line 72, in forward 2025-09-07T09:04:03.1415362Z embeddings_b = self.encoder_b(features_b) 2025-09-07T09:04:03.1416277Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchmultimodal/models/clip/text_encoder.py", line 132, in forward 2025-09-07T09:04:03.1417348Z hidden_state[torch.arange(hidden_state.shape[0]), text.argmax(dim=-1)] 2025-09-07T09:04:03.1417802Z 2025-09-07T09:04:03.1417807Z 2025-09-07T09:04:03.5323138Z W0907 09:04:03.531000 33671 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:04:42.8146707Z pass 2025-09-07T09:04:48.6719375Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:04:48.6721386Z import pynvml # type: ignore[import] 2025-09-07T09:04:51.1693447Z 2025-09-07T09:04:51.9971560Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:04:51.9972037Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:04:51.9972451Z cuda train tts_angular 2025-09-07T09:04:54.6248063Z W0907 09:04:54.624000 33929 site-packages/torch/_logging/_internal.py:1199] [10/0] Profiler function will be ignored 2025-09-07T09:04:55.1609416Z pass 2025-09-07T09:04:58.0261474Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:04:58.0263315Z import pynvml # type: ignore[import] 2025-09-07T09:05:00.6040862Z 2025-09-07T09:05:03.4356174Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:05:03.4356506Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:05:03.4357473Z cuda train vgg16 2025-09-07T09:05:14.4803164Z pass 2025-09-07T09:05:17.4126485Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:05:17.4128478Z import pynvml # type: ignore[import] 2025-09-07T09:05:20.1713268Z 2025-09-07T09:05:34.1015938Z loading model: 0it [00:00, ?it/s]skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:05:34.1017237Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:05:34.1018043Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:05:34.1018709Z v4 = masked_index(y_high, x_high) 2025-09-07T09:05:34.1019275Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:05:34.1019812Z return input[ 2025-09-07T09:05:34.1019943Z 2025-09-07T09:05:34.1019948Z 2025-09-07T09:05:45.0990667Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:05:45.0992276Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:05:45.0993361Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:05:45.0994222Z v4 = masked_index(y_high, x_high) 2025-09-07T09:05:45.0994994Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:05:45.0995743Z return input[ 2025-09-07T09:05:45.0995934Z 2025-09-07T09:05:45.0995939Z 2025-09-07T09:05:53.8112128Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:05:53.8113666Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:05:53.8114719Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:05:53.8115534Z v4 = masked_index(y_high, x_high) 2025-09-07T09:05:53.8116287Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:05:53.8117026Z return input[ 2025-09-07T09:05:53.8117196Z 2025-09-07T09:05:53.8117201Z 2025-09-07T09:06:01.7746819Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:06:01.7747974Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:06:01.7748801Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:06:01.7749414Z v4 = masked_index(y_high, x_high) 2025-09-07T09:06:01.7749989Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:06:01.7750972Z return input[ 2025-09-07T09:06:01.7751103Z 2025-09-07T09:06:01.7751107Z 2025-09-07T09:06:12.6860641Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:06:12.6862076Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:06:12.6862758Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:06:12.6863635Z v4 = masked_index(y_high, x_high) 2025-09-07T09:06:12.6864134Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:06:12.6864592Z return input[ 2025-09-07T09:06:12.6864707Z 2025-09-07T09:06:12.6864710Z 2025-09-07T09:06:21.9110122Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:06:21.9111786Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:06:21.9112540Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:06:21.9113125Z v4 = masked_index(y_high, x_high) 2025-09-07T09:06:21.9113640Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:06:21.9114186Z return input[ 2025-09-07T09:06:21.9114315Z 2025-09-07T09:06:21.9114318Z 2025-09-07T09:06:33.5289499Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:06:33.5290937Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:06:33.5291687Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:06:33.5292303Z v4 = masked_index(y_high, x_high) 2025-09-07T09:06:33.5292816Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:06:33.5293325Z return input[ 2025-09-07T09:06:33.5293441Z 2025-09-07T09:06:33.5293445Z 2025-09-07T09:06:38.2309641Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:06:38.2311370Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:06:38.2312150Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:06:38.2312741Z v4 = masked_index(y_high, x_high) 2025-09-07T09:06:38.2313274Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:06:38.2313792Z return input[ 2025-09-07T09:06:38.2313914Z 2025-09-07T09:06:38.2313928Z 2025-09-07T09:06:39.7184378Z 2025-09-07T09:06:39.7184904Z loading model: 0it [01:19, ?it/s] 2025-09-07T09:06:39.7185488Z cuda train vision_maskrcnn 2025-09-07T09:06:39.8413065Z W0907 09:06:39.840000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T09:06:39.8414172Z W0907 09:06:39.840000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] function: '_roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:114) 2025-09-07T09:06:39.8415316Z W0907 09:06:39.840000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] last reason: 0/7: tensor 'rois' dtype mismatch. expected Float, actual Double 2025-09-07T09:06:39.8416699Z W0907 09:06:39.840000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T09:06:39.8417818Z W0907 09:06:39.840000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T09:06:56.2748728Z W0907 09:06:56.231000 34347 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T09:06:56.2749825Z W0907 09:06:56.232000 34347 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T09:06:56.2750768Z W0907 09:06:56.233000 34347 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T09:06:56.2751450Z W0907 09:06:56.234000 34347 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T09:06:56.2752165Z W0907 09:06:56.235000 34347 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T09:06:56.8072068Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T09:06:56.8072809Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T09:06:56.8073508Z anchors = self.anchor_generator(images, features) 2025-09-07T09:06:56.8074236Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T09:06:56.8074953Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T09:06:56.8075688Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T09:06:56.8076565Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8077306Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T09:06:56.8078047Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8078376Z 2025-09-07T09:06:56.8078529Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T09:06:56.8079110Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T09:06:56.8079678Z anchors = self.anchor_generator(images, features) 2025-09-07T09:06:56.8080491Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T09:06:56.8081115Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T09:06:56.8081743Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T09:06:56.8082490Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8083205Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T09:06:56.8083916Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8084239Z 2025-09-07T09:06:56.8084390Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T09:06:56.8084957Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T09:06:56.8085526Z anchors = self.anchor_generator(images, features) 2025-09-07T09:06:56.8086111Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T09:06:56.8086713Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T09:06:56.8087332Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T09:06:56.8222946Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8223777Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T09:06:56.8224594Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8224950Z 2025-09-07T09:06:56.8225427Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T09:06:56.8226084Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T09:06:56.8226721Z anchors = self.anchor_generator(images, features) 2025-09-07T09:06:56.8227261Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T09:06:56.8227823Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T09:06:56.8228405Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T09:06:56.8229079Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8229729Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T09:06:56.8230575Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8230876Z 2025-09-07T09:06:56.8231010Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T09:06:56.8231525Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T09:06:56.8232039Z anchors = self.anchor_generator(images, features) 2025-09-07T09:06:56.8232575Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T09:06:56.8233145Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T09:06:56.8233709Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T09:06:56.8234372Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8235018Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T09:06:56.8235659Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T09:06:56.8235944Z 2025-09-07T09:06:56.8266739Z cudagraph partition into 2 partitions 2025-09-07T09:06:59.2195776Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T09:06:59.2196744Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T09:06:59.2197531Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] or: 2025-09-07T09:06:59.2198243Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T09:06:59.2199061Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] to include these operations in the captured graph. 2025-09-07T09:06:59.2199734Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T09:06:59.2200776Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break: from user code at: 2025-09-07T09:06:59.2201959Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T09:06:59.2203896Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T09:06:59.2205386Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T09:06:59.2206515Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T09:06:59.2207571Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T09:06:59.2208484Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T09:06:59.2209397Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T09:06:59.2210532Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T09:06:59.2221621Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T09:06:59.2222637Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T09:06:59.2223702Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T09:06:59.2224649Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T09:06:59.2225269Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T09:06:59.2225741Z W0907 09:06:59.218000 34347 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T09:06:59.4762237Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:06:59.4763038Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T09:06:59.4763850Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T09:06:59.4764168Z 2025-09-07T09:07:00.3108116Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:07:00.3108901Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T09:07:00.3109669Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T09:07:00.3109978Z 2025-09-07T09:07:07.7875001Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:07.7876318Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:07.7877120Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:07.7877701Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:07.7878647Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:07.7879368Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:07.7880117Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:07.7881325Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:07.7881828Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:07.7882309Z return input[ 2025-09-07T09:07:07.7882424Z 2025-09-07T09:07:07.7882427Z 2025-09-07T09:07:13.0056867Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:13.0058354Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:13.0059229Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:13.0059868Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:13.0060845Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:13.0061580Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:13.0062324Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:13.0062975Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:13.0063480Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:13.0063997Z return input[ 2025-09-07T09:07:13.0064111Z 2025-09-07T09:07:13.0064115Z 2025-09-07T09:07:17.4537907Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:17.4539817Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:17.4541458Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:17.4542362Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:17.4543233Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:17.4544292Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:17.4545445Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:17.4546331Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:17.4547142Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:17.4547925Z return input[ 2025-09-07T09:07:17.4548129Z 2025-09-07T09:07:17.4548135Z 2025-09-07T09:07:33.5132399Z W0907 09:07:33.512000 34347 site-packages/torch/fx/experimental/symbolic_shapes.py:2396] [30/4] RecursionError in sympy.xreplace(Eq(Mod(2*s29, s93), 0), {s29: evaluate_static_shape_0 + 1, s93: evaluate_static_shape_1 + 1}) 2025-09-07T09:07:34.5093315Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:34.5094627Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:34.5095931Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:34.5096562Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:34.5097149Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:34.5098103Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:34.5098819Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:34.5099361Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:34.5099858Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:34.5100766Z return input[ 2025-09-07T09:07:34.5100900Z 2025-09-07T09:07:34.5100903Z 2025-09-07T09:07:40.2272672Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:40.2273964Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:40.2274833Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:40.2275421Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:40.2275932Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:40.2276645Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:40.2277389Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:40.2277984Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:40.2278520Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:40.2279043Z return input[ 2025-09-07T09:07:40.2279170Z 2025-09-07T09:07:40.2279173Z 2025-09-07T09:07:48.9364284Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:48.9365699Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:48.9366597Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:48.9367225Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:48.9367795Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:48.9368548Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:48.9369363Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:48.9370010Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:48.9371013Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:48.9371581Z return input[ 2025-09-07T09:07:48.9371711Z 2025-09-07T09:07:48.9371715Z 2025-09-07T09:07:52.2482723Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:07:52.2484585Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:07:52.2485405Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:07:52.2486004Z return fn(*args[2:], **kwargs) 2025-09-07T09:07:52.2486865Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:07:52.2487615Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:07:52.2488382Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:07:52.2488964Z v4 = masked_index(y_high, x_high) 2025-09-07T09:07:52.2489518Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:07:52.2490064Z return input[ 2025-09-07T09:07:52.2490196Z 2025-09-07T09:07:52.2490587Z 2025-09-07T09:07:57.9019659Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 418, in torch_dynamo_resume_in_paste_mask_in_image_at_410 2025-09-07T09:07:57.9021408Z mask = F.interpolate(mask, size=(h, w), mode="bilinear", align_corners=False) 2025-09-07T09:07:57.9021736Z 2025-09-07T09:07:57.9021740Z 2025-09-07T09:07:58.9064291Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 418, in torch_dynamo_resume_in_paste_mask_in_image_at_410 2025-09-07T09:07:58.9065632Z mask = F.interpolate(mask, size=(h, w), mode="bilinear", align_corners=False) 2025-09-07T09:07:58.9065961Z 2025-09-07T09:07:58.9065993Z 2025-09-07T09:08:00.6746762Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 823, in torch_dynamo_resume_in_forward_at_806 2025-09-07T09:08:00.6748641Z masks_probs = maskrcnn_inference(mask_logits, labels) 2025-09-07T09:08:00.6749814Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 79, in maskrcnn_inference 2025-09-07T09:08:00.6751462Z mask_prob = mask_prob[index, labels][:, None] 2025-09-07T09:08:00.6751825Z 2025-09-07T09:08:00.6751833Z 2025-09-07T09:08:03.8203208Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:08:03.8204461Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:08:03.8205274Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:08:03.8205847Z return fn(*args[2:], **kwargs) 2025-09-07T09:08:03.8206350Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:03.8207056Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:03.8207734Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:03.8208287Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:03.8208782Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:03.8209262Z return input[ 2025-09-07T09:08:03.8209804Z 2025-09-07T09:08:03.8209809Z 2025-09-07T09:08:07.3684006Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 114, in forward 2025-09-07T09:08:07.3685166Z features = self.backbone(images.tensors) 2025-09-07T09:08:07.3686388Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/backbone_utils.py", line 58, in forward 2025-09-07T09:08:07.3687005Z x = self.fpn(x) 2025-09-07T09:08:07.3687528Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/feature_pyramid_network.py", line 194, in forward 2025-09-07T09:08:07.3688169Z inner_top_down = F.interpolate(last_inner, size=feat_shape, mode="nearest") 2025-09-07T09:08:07.3688448Z 2025-09-07T09:08:07.3688453Z 2025-09-07T09:08:07.6645909Z W0907 09:08:07.662000 34347 site-packages/torch/_logging/_internal.py:1199] [51/0] Profiler function will be ignored 2025-09-07T09:08:18.1141333Z W0907 09:08:18.113000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T09:08:18.1143463Z W0907 09:08:18.113000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] function: 'torch_dynamo_resume_in_roi_align_at_255' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:255) 2025-09-07T09:08:18.1145480Z W0907 09:08:18.113000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] last reason: 30/7: tensor 'rois' requires_grad mismatch. expected requires_grad=1 2025-09-07T09:08:18.1147064Z W0907 09:08:18.113000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T09:08:18.1148880Z W0907 09:08:18.113000 34347 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T09:08:20.3366576Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:20.3368410Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:20.3369745Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:20.3371196Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:20.3371697Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:20.3372181Z return input[ 2025-09-07T09:08:20.3372294Z 2025-09-07T09:08:20.3372298Z 2025-09-07T09:08:23.1470075Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:23.1472302Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:23.1473066Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:23.1473666Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:23.1474197Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:23.1474718Z return input[ 2025-09-07T09:08:23.1474840Z 2025-09-07T09:08:23.1474843Z 2025-09-07T09:08:25.1219845Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:25.1221657Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:25.1222431Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:25.1223141Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:25.1223987Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:25.1224525Z return input[ 2025-09-07T09:08:25.1224662Z 2025-09-07T09:08:25.1224666Z 2025-09-07T09:08:27.0986141Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:27.0987297Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:27.0988112Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:27.0988745Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:27.0989300Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:27.0989966Z return input[ 2025-09-07T09:08:27.0990123Z 2025-09-07T09:08:27.0990128Z 2025-09-07T09:08:32.8360844Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:32.8361992Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:32.8362745Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:32.8363325Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:32.8363876Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:32.8364398Z return input[ 2025-09-07T09:08:32.8364520Z 2025-09-07T09:08:32.8364524Z 2025-09-07T09:08:36.1428833Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:36.1429991Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:36.1431185Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:36.1431796Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:36.1432350Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:36.1432894Z return input[ 2025-09-07T09:08:36.1433025Z 2025-09-07T09:08:36.1433030Z 2025-09-07T09:08:40.2763554Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:08:40.2764687Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:08:40.2765467Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:08:40.2766063Z v4 = masked_index(y_high, x_high) 2025-09-07T09:08:40.2766589Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:08:40.2767104Z return input[ 2025-09-07T09:08:40.2767221Z 2025-09-07T09:08:40.2767225Z 2025-09-07T09:08:49.9334318Z W0907 09:08:49.932000 34347 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:08:49.9575622Z W0907 09:08:49.957000 34347 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:08:50.2407430Z pass 2025-09-07T09:08:55.7944996Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:08:55.7946158Z import pynvml # type: ignore[import] 2025-09-07T09:08:58.2213218Z 2025-09-07T09:09:01.3721956Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:09:01.3722369Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:09:01.3722733Z cuda train yolov3 2025-09-07T09:09:26.9145862Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:09:26.9146648Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:09:26.9147351Z pred = mod(*cloned_inputs) 2025-09-07T09:09:26.9147800Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:09:26.9148269Z return self.forward_once(x) 2025-09-07T09:09:26.9148717Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T09:09:26.9149233Z yolo_out.append(module(x, out)) 2025-09-07T09:09:26.9149767Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T09:09:26.9150607Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T09:09:26.9151099Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T09:09:26.9151579Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T09:09:26.9151801Z 2025-09-07T09:09:26.9151947Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:09:26.9152625Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:09:26.9153255Z pred = mod(*cloned_inputs) 2025-09-07T09:09:26.9153651Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:09:26.9154082Z return self.forward_once(x) 2025-09-07T09:09:26.9154509Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T09:09:26.9154964Z yolo_out.append(module(x, out)) 2025-09-07T09:09:26.9155374Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T09:09:26.9155828Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T09:09:26.9156296Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T09:09:26.9156772Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T09:09:26.9156984Z 2025-09-07T09:09:26.9157118Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T09:09:26.9157772Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T09:09:26.9158385Z pred = mod(*cloned_inputs) 2025-09-07T09:09:26.9158775Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:09:26.9159204Z return self.forward_once(x) 2025-09-07T09:09:26.9159631Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T09:09:26.9160079Z yolo_out.append(module(x, out)) 2025-09-07T09:09:26.9160626Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T09:09:26.9161029Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T09:09:26.9161416Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T09:09:26.9639173Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T09:09:26.9639429Z 2025-09-07T09:09:27.1616622Z cudagraph partition into 2 partitions 2025-09-07T09:10:04.7424212Z 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 2025-09-07T09:10:04.7425971Z pred = mod(*cloned_inputs) 2025-09-07T09:10:04.7426463Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:10:04.7426932Z return self.forward_once(x) 2025-09-07T09:10:04.7427383Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 374, in forward_once 2025-09-07T09:10:04.7427835Z x = module(x) 2025-09-07T09:10:04.7427966Z 2025-09-07T09:10:04.7427982Z 2025-09-07T09:10:05.6863438Z W0907 09:10:05.685000 36063 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:10:37.6157586Z 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 2025-09-07T09:10:37.6158755Z pred = mod(*cloned_inputs) 2025-09-07T09:10:37.6159210Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:10:37.6159687Z return self.forward_once(x) 2025-09-07T09:10:37.6160138Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 374, in forward_once 2025-09-07T09:10:37.6160896Z x = module(x) 2025-09-07T09:10:37.6161014Z 2025-09-07T09:10:37.6161018Z 2025-09-07T09:10:38.8650182Z pass 2025-09-07T09:10:44.4101940Z accuracy pass_rate=86.67% 2025-09-07T09:10:44.4114886Z calls_captured gmean=0.00x mean=874.200x 2025-09-07T09:10:44.4118039Z unique_graphs gmean=0.00x mean=6.333x 2025-09-07T09:10:44.4121798Z graph_breaks gmean=0.00x mean=8.600x 2025-09-07T09:10:44.4125200Z unique_graph_breaks gmean=0.00x mean=4.733x 2025-09-07T09:10:44.4128534Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:10:44.4132146Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:10:44.4135414Z cudagraph_skips gmean=0.00x mean=1.200x 2025-09-07T09:10:44.4136625Z compilation_latency mean=48.740 seconds 2025-09-07T09:10:45.2726256Z + [[ 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* ]] 2025-09-07T09:10:45.2731087Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:10:45.8169185Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:10:45.8170588Z import pynvml # type: ignore[import] 2025-09-07T09:10:49.6213931Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:10:49.6215600Z import pynvml # type: ignore[import] 2025-09-07T09:10:52.3308460Z 2025-09-07T09:10:54.0392770Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:10:54.0393016Z 2025-09-07T09:10:55.1021269Z Loading pipeline components...: 0% 0/6 [00:00 will be ignored 2025-09-07T09:14:48.4581171Z pass 2025-09-07T09:14:51.6757167Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:14:51.6758407Z import pynvml # type: ignore[import] 2025-09-07T09:14:54.1476128Z 2025-09-07T09:14:57.5140725Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:14:57.5141108Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:14:57.5141934Z cuda train timm_nfnet 2025-09-07T09:15:06.9029839Z pass 2025-09-07T09:15:10.3234695Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:15:10.3235910Z import pynvml # type: ignore[import] 2025-09-07T09:15:12.8078009Z 2025-09-07T09:15:17.1364062Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:17.1364452Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:15:17.1365325Z cuda train timm_regnet 2025-09-07T09:15:28.6221691Z W0907 09:15:28.621000 38904 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:15:34.9751613Z W0907 09:15:34.974000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9757383Z W0907 09:15:34.975000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9770109Z W0907 09:15:34.976000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9776610Z W0907 09:15:34.977000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9782911Z W0907 09:15:34.977000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9789366Z W0907 09:15:34.978000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9795955Z W0907 09:15:34.979000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9802206Z W0907 09:15:34.979000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9808228Z W0907 09:15:34.980000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9822171Z W0907 09:15:34.981000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9829163Z W0907 09:15:34.982000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9835361Z W0907 09:15:34.983000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9840991Z W0907 09:15:34.983000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9846996Z W0907 09:15:34.984000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9853728Z W0907 09:15:34.985000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9859680Z W0907 09:15:34.985000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9866161Z W0907 09:15:34.986000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9872555Z W0907 09:15:34.986000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9878569Z W0907 09:15:34.987000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9884937Z W0907 09:15:34.988000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9894960Z W0907 09:15:34.989000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9901222Z W0907 09:15:34.989000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9907826Z W0907 09:15:34.990000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9914254Z W0907 09:15:34.991000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9920128Z W0907 09:15:34.991000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9926888Z W0907 09:15:34.992000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9933261Z W0907 09:15:34.993000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9939244Z W0907 09:15:34.993000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9946206Z W0907 09:15:34.994000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9952595Z W0907 09:15:34.994000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9958531Z W0907 09:15:34.995000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9965287Z W0907 09:15:34.996000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9971494Z W0907 09:15:34.996000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9977601Z W0907 09:15:34.997000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9988027Z W0907 09:15:34.998000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:34.9994387Z W0907 09:15:34.999000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0000691Z W0907 09:15:34.999000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0427487Z W0907 09:15:35.042000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0433666Z W0907 09:15:35.043000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0439972Z W0907 09:15:35.043000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0446758Z W0907 09:15:35.044000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0453378Z W0907 09:15:35.045000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0459939Z W0907 09:15:35.045000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0466906Z W0907 09:15:35.046000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0473526Z W0907 09:15:35.047000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0479818Z W0907 09:15:35.047000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0494284Z W0907 09:15:35.049000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0501376Z W0907 09:15:35.049000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0507533Z W0907 09:15:35.050000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0514069Z W0907 09:15:35.051000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0520583Z W0907 09:15:35.051000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0527423Z W0907 09:15:35.052000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0534100Z W0907 09:15:35.053000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0540458Z W0907 09:15:35.053000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0547448Z W0907 09:15:35.054000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0554147Z W0907 09:15:35.055000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0560760Z W0907 09:15:35.055000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0571017Z W0907 09:15:35.056000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0577683Z W0907 09:15:35.057000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0584810Z W0907 09:15:35.058000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0591661Z W0907 09:15:35.058000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0598281Z W0907 09:15:35.059000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0604936Z W0907 09:15:35.060000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0611514Z W0907 09:15:35.060000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0617834Z W0907 09:15:35.061000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0624901Z W0907 09:15:35.062000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0631611Z W0907 09:15:35.062000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0637881Z W0907 09:15:35.063000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0644979Z W0907 09:15:35.064000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0651469Z W0907 09:15:35.064000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0658003Z W0907 09:15:35.065000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0668606Z W0907 09:15:35.066000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0675320Z W0907 09:15:35.067000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.0682140Z W0907 09:15:35.067000 38904 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:15:35.2084540Z pass 2025-09-07T09:15:38.3994915Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:15:38.3996128Z import pynvml # type: ignore[import] 2025-09-07T09:15:40.8612343Z 2025-09-07T09:15:43.6139782Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:43.6140912Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:15:43.6141396Z cuda train timm_resnest 2025-09-07T09:15:50.5916767Z pass 2025-09-07T09:15:53.4853963Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:15:53.4855270Z import pynvml # type: ignore[import] 2025-09-07T09:15:55.9181295Z 2025-09-07T09:15:58.1496967Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:15:58.1497313Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:15:58.1497644Z cuda train timm_vision_transformer 2025-09-07T09:16:05.8527243Z pass 2025-09-07T09:16:08.6251328Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:08.6253193Z import pynvml # type: ignore[import] 2025-09-07T09:16:11.0890494Z 2025-09-07T09:16:23.0203139Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:16:23.0203509Z loading model: 0it [00:11, ?it/s] 2025-09-07T09:16:23.0203807Z cuda train timm_vision_transformer_large 2025-09-07T09:16:23.0599482Z pass_due_to_skip 2025-09-07T09:16:24.8708780Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:24.8710647Z import pynvml # type: ignore[import] 2025-09-07T09:16:27.7679399Z 2025-09-07T09:16:30.4372795Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:16:30.4373281Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:16:30.4374442Z cuda train timm_vovnet 2025-09-07T09:16:39.3198563Z pass 2025-09-07T09:16:42.4107436Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:16:42.4108759Z import pynvml # type: ignore[import] 2025-09-07T09:16:44.9411929Z 2025-09-07T09:16:47.3689572Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:16:47.3689930Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:16:47.3690843Z cuda train torch_multimodal_clip 2025-09-07T09:16:56.3089499Z 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 2025-09-07T09:16:56.3091140Z pred = mod(*cloned_inputs) 2025-09-07T09:16:56.3091760Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchmultimodal/models/clip/model.py", line 72, in forward 2025-09-07T09:16:56.3092373Z embeddings_b = self.encoder_b(features_b) 2025-09-07T09:16:56.3093000Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchmultimodal/models/clip/text_encoder.py", line 132, in forward 2025-09-07T09:16:56.3093733Z hidden_state[torch.arange(hidden_state.shape[0]), text.argmax(dim=-1)] 2025-09-07T09:16:56.3094029Z 2025-09-07T09:16:56.3094034Z 2025-09-07T09:16:57.1936269Z W0907 09:16:57.192000 40064 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:17:02.6711251Z pass 2025-09-07T09:17:05.8320756Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:17:05.8322296Z import pynvml # type: ignore[import] 2025-09-07T09:17:08.4598743Z 2025-09-07T09:17:09.3395464Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:17:09.3395795Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:17:09.3396085Z cuda train tts_angular 2025-09-07T09:17:13.8078213Z W0907 09:17:13.807000 40332 site-packages/torch/_logging/_internal.py:1199] [10/0] Profiler function will be ignored 2025-09-07T09:17:14.4831976Z pass 2025-09-07T09:17:17.5663940Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:17:17.5665446Z import pynvml # type: ignore[import] 2025-09-07T09:17:20.3449263Z 2025-09-07T09:17:23.2801742Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:17:23.2802076Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:17:23.2802363Z cuda train vgg16 2025-09-07T09:17:30.3385894Z pass 2025-09-07T09:17:33.8493323Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:17:33.8495171Z import pynvml # type: ignore[import] 2025-09-07T09:17:36.6952911Z 2025-09-07T09:17:42.1660585Z loading model: 0it [00:00, ?it/s]skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:42.1661892Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:42.1662644Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:42.1663268Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:42.1663767Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:42.1664247Z return input[ 2025-09-07T09:17:42.1664383Z 2025-09-07T09:17:42.1664387Z 2025-09-07T09:17:44.9962221Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:44.9963600Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:44.9964476Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:44.9965192Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:44.9965796Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:44.9966400Z return input[ 2025-09-07T09:17:44.9966535Z 2025-09-07T09:17:44.9966539Z 2025-09-07T09:17:46.2160850Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:46.2162028Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:46.2162812Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:46.2163379Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:46.2163877Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:46.2164393Z return input[ 2025-09-07T09:17:46.2164507Z 2025-09-07T09:17:46.2164511Z 2025-09-07T09:17:47.2452032Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:47.2453677Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:47.2454407Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:47.2454974Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:47.2455467Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:47.2455971Z return input[ 2025-09-07T09:17:47.2456096Z 2025-09-07T09:17:47.2456442Z 2025-09-07T09:17:48.1227373Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:48.1229293Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:48.1231794Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:48.1232936Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:48.1233758Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:48.1234305Z return input[ 2025-09-07T09:17:48.1234427Z 2025-09-07T09:17:48.1234430Z 2025-09-07T09:17:49.0101278Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:49.0103642Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:49.0104402Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:49.0104997Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:49.0105516Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:49.0106027Z return input[ 2025-09-07T09:17:49.0106148Z 2025-09-07T09:17:49.0106152Z 2025-09-07T09:17:50.0391891Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:50.0393174Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:50.0394106Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:50.0394724Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:50.0395276Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:50.0395827Z return input[ 2025-09-07T09:17:50.0395970Z 2025-09-07T09:17:50.0395974Z 2025-09-07T09:17:50.6428407Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:17:50.6429622Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:17:50.6430936Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:17:50.6431633Z v4 = masked_index(y_high, x_high) 2025-09-07T09:17:50.6432202Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:17:50.6432763Z return input[ 2025-09-07T09:17:50.6432896Z 2025-09-07T09:17:50.6432900Z 2025-09-07T09:17:51.7329714Z 2025-09-07T09:17:51.7330182Z loading model: 0it [00:15, ?it/s] 2025-09-07T09:17:51.7331057Z cuda train vision_maskrcnn 2025-09-07T09:17:51.8619922Z W0907 09:17:51.861000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T09:17:51.8621593Z W0907 09:17:51.861000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] function: '_roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:114) 2025-09-07T09:17:51.8633676Z W0907 09:17:51.861000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] last reason: 0/7: tensor 'rois' dtype mismatch. expected Float, actual Double 2025-09-07T09:17:51.8635093Z W0907 09:17:51.861000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T09:17:51.8636368Z W0907 09:17:51.861000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T09:17:58.1775942Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 114, in forward 2025-09-07T09:17:58.1777389Z features = self.backbone(images.tensors) 2025-09-07T09:17:58.1778086Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/backbone_utils.py", line 58, in forward 2025-09-07T09:17:58.1778725Z x = self.fpn(x) 2025-09-07T09:17:58.1779323Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/feature_pyramid_network.py", line 194, in forward 2025-09-07T09:17:58.1780056Z inner_top_down = F.interpolate(last_inner, size=feat_shape, mode="nearest") 2025-09-07T09:17:58.1780754Z 2025-09-07T09:17:58.1780759Z 2025-09-07T09:18:00.8900727Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T09:18:00.8901829Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T09:18:00.8902646Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] or: 2025-09-07T09:18:00.8903541Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T09:18:00.8904505Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] to include these operations in the captured graph. 2025-09-07T09:18:00.8905282Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T09:18:00.8906007Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break: from user code at: 2025-09-07T09:18:00.8907488Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T09:18:00.8909083Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T09:18:00.8910639Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T09:18:00.8911976Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T09:18:00.8913215Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T09:18:00.8914368Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T09:18:00.8915534Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T09:18:00.8916791Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T09:18:00.8918403Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T09:18:00.8919714Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T09:18:00.8920923Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T09:18:00.8921942Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T09:18:00.8922604Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T09:18:00.8923072Z W0907 09:18:00.889000 40868 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T09:18:02.2373841Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:02.2375127Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:02.2375942Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:02.2376556Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:02.2377155Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:02.2377806Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:02.2378515Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:02.2379058Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:02.2379551Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:02.2380035Z return input[ 2025-09-07T09:18:02.2380152Z 2025-09-07T09:18:02.2380159Z 2025-09-07T09:18:02.8013368Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:02.8014613Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:02.8015435Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:02.8016081Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:02.8016626Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:02.8017403Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:02.8018109Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:02.8018668Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:02.8019177Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:02.8019675Z return input[ 2025-09-07T09:18:02.8019789Z 2025-09-07T09:18:02.8019793Z 2025-09-07T09:18:03.2834640Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:03.2836192Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:03.2836986Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:03.2837837Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:03.2838339Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:03.2838981Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:03.2839669Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:03.2840647Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:03.2841157Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:03.2841648Z return input[ 2025-09-07T09:18:03.2841763Z 2025-09-07T09:18:03.2841766Z 2025-09-07T09:18:03.7380819Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:03.7382078Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:03.7382949Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:03.7383545Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:03.7384083Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:03.7384806Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:03.7385568Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:03.7386170Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:03.7386720Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:03.7387307Z return input[ 2025-09-07T09:18:03.7387461Z 2025-09-07T09:18:03.7387465Z 2025-09-07T09:18:06.5751824Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:06.5753183Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:06.5754033Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:06.5754616Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:06.5755128Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:06.5755831Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:06.5756576Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:06.5757169Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:06.5757699Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:06.5758220Z return input[ 2025-09-07T09:18:06.5758342Z 2025-09-07T09:18:06.5758345Z 2025-09-07T09:18:07.4108780Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:07.4111479Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:07.4113069Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:07.4113694Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:07.4114225Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:07.4114924Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:07.4115699Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:07.4116300Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:07.4116847Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:07.4117375Z return input[ 2025-09-07T09:18:07.4117499Z 2025-09-07T09:18:07.4117516Z 2025-09-07T09:18:08.3292271Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:08.3294330Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:08.3295642Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:08.3296601Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:08.3297474Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:08.3298680Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:08.3299672Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:08.3300206Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:08.3300839Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:08.3301316Z return input[ 2025-09-07T09:18:08.3301437Z 2025-09-07T09:18:08.3301440Z 2025-09-07T09:18:09.0251852Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T09:18:09.0253154Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:18:09.0253992Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T09:18:09.0254585Z return fn(*args[2:], **kwargs) 2025-09-07T09:18:09.0255112Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:09.0255838Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:09.0256614Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:09.0257216Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:09.0257760Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:09.0258283Z return input[ 2025-09-07T09:18:09.0258433Z 2025-09-07T09:18:09.0258437Z 2025-09-07T09:18:09.1845844Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 823, in torch_dynamo_resume_in_forward_at_806 2025-09-07T09:18:09.1847019Z masks_probs = maskrcnn_inference(mask_logits, labels) 2025-09-07T09:18:09.1848106Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 79, in maskrcnn_inference 2025-09-07T09:18:09.1848850Z mask_prob = mask_prob[index, labels][:, None] 2025-09-07T09:18:09.1849088Z 2025-09-07T09:18:09.1849091Z 2025-09-07T09:18:09.9182654Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 418, in torch_dynamo_resume_in_paste_mask_in_image_at_410 2025-09-07T09:18:09.9184839Z mask = F.interpolate(mask, size=(h, w), mode="bilinear", align_corners=False) 2025-09-07T09:18:09.9185384Z 2025-09-07T09:18:09.9185393Z 2025-09-07T09:18:10.3252975Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 418, in torch_dynamo_resume_in_paste_mask_in_image_at_410 2025-09-07T09:18:10.3254971Z mask = F.interpolate(mask, size=(h, w), mode="bilinear", align_corners=False) 2025-09-07T09:18:10.3255484Z 2025-09-07T09:18:10.3255490Z 2025-09-07T09:18:12.1758061Z W0907 09:18:12.175000 40868 site-packages/torch/_logging/_internal.py:1199] [51/0] Profiler function will be ignored 2025-09-07T09:18:14.1798204Z W0907 09:18:14.179000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T09:18:14.1799388Z W0907 09:18:14.179000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] function: 'torch_dynamo_resume_in_roi_align_at_255' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:255) 2025-09-07T09:18:14.1801209Z W0907 09:18:14.179000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] last reason: 30/7: tensor 'rois' requires_grad mismatch. expected requires_grad=1 2025-09-07T09:18:14.1802354Z W0907 09:18:14.179000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T09:18:14.1803625Z W0907 09:18:14.179000 40868 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T09:18:14.6439736Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:14.6441303Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:14.6442142Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:14.6442747Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:14.6443340Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:14.6443890Z return input[ 2025-09-07T09:18:14.6444025Z 2025-09-07T09:18:14.6444030Z 2025-09-07T09:18:15.8751791Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:15.8752896Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:15.8753650Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:15.8754704Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:15.8755242Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:15.8755764Z return input[ 2025-09-07T09:18:15.8755889Z 2025-09-07T09:18:15.8755892Z 2025-09-07T09:18:16.4189594Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:16.4190780Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:16.4191552Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:16.4192136Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:16.4192672Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:16.4193194Z return input[ 2025-09-07T09:18:16.4193317Z 2025-09-07T09:18:16.4193320Z 2025-09-07T09:18:17.0467110Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:17.0468469Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:17.0469428Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:17.0470161Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:17.0471114Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:17.0471853Z return input[ 2025-09-07T09:18:17.0471979Z 2025-09-07T09:18:17.0471983Z 2025-09-07T09:18:18.9041276Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:18.9042639Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:18.9043570Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:18.9044270Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:18.9044885Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:18.9045484Z return input[ 2025-09-07T09:18:18.9045635Z 2025-09-07T09:18:18.9045640Z 2025-09-07T09:18:19.4831515Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:19.4832850Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:19.4833638Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:19.4834268Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:19.4834822Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:19.4835366Z return input[ 2025-09-07T09:18:19.4835494Z 2025-09-07T09:18:19.4835498Z 2025-09-07T09:18:20.1215139Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:18:20.1216697Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:18:20.1217525Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:18:20.1218178Z v4 = masked_index(y_high, x_high) 2025-09-07T09:18:20.1219029Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:18:20.1219599Z return input[ 2025-09-07T09:18:20.1219727Z 2025-09-07T09:18:20.1219730Z 2025-09-07T09:18:22.1046728Z W0907 09:18:22.103000 40868 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:18:22.1299363Z W0907 09:18:22.129000 40868 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:18:22.3188003Z pass 2025-09-07T09:18:26.2603731Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:18:26.2604949Z import pynvml # type: ignore[import] 2025-09-07T09:18:28.8342781Z 2025-09-07T09:18:31.7726084Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:18:31.7726539Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:18:31.7726930Z cuda train yolov3 2025-09-07T09:18:43.3730980Z 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 2025-09-07T09:18:43.3732125Z pred = mod(*cloned_inputs) 2025-09-07T09:18:43.3732581Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:18:43.3733099Z return self.forward_once(x) 2025-09-07T09:18:43.3733554Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 374, in forward_once 2025-09-07T09:18:43.3733997Z x = module(x) 2025-09-07T09:18:43.3734130Z 2025-09-07T09:18:43.3734135Z 2025-09-07T09:18:45.0406082Z W0907 09:18:45.039000 41198 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:18:53.2775907Z 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 2025-09-07T09:18:53.2777587Z pred = mod(*cloned_inputs) 2025-09-07T09:18:53.2778311Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T09:18:53.2779063Z return self.forward_once(x) 2025-09-07T09:18:53.2779772Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 374, in forward_once 2025-09-07T09:18:53.2781231Z x = module(x) 2025-09-07T09:18:53.2781468Z 2025-09-07T09:18:53.2781476Z 2025-09-07T09:18:54.4303773Z pass 2025-09-07T09:18:57.2901936Z accuracy pass_rate=86.67% 2025-09-07T09:18:57.2913719Z calls_captured gmean=0.00x mean=875.867x 2025-09-07T09:18:57.2917328Z unique_graphs gmean=0.00x mean=6.333x 2025-09-07T09:18:57.2920844Z graph_breaks gmean=0.00x mean=8.600x 2025-09-07T09:18:57.2924414Z unique_graph_breaks gmean=0.00x mean=4.733x 2025-09-07T09:18:57.2927615Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:18:57.2930872Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:18:57.2934351Z cudagraph_skips gmean=0.00x mean=1.200x 2025-09-07T09:18:57.2935463Z compilation_latency mean=19.998 seconds 2025-09-07T09:18:58.1352099Z + [[ 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* ]] 2025-09-07T09:18:58.1354244Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T09:18:58.1355900Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:18:58.6836414Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:18:58.6837657Z import pynvml # type: ignore[import] 2025-09-07T09:19:02.3921939Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:19:02.3923241Z import pynvml # type: ignore[import] 2025-09-07T09:19:04.8957396Z 2025-09-07T09:19:06.5778180Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:19:06.5778596Z 2025-09-07T09:19:06.7364766Z Loading pipeline components...: 0% 0/6 [00:00 will be ignored 2025-09-07T09:29:40.3198737Z pass 2025-09-07T09:29:46.0611588Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:29:46.0612828Z import pynvml # type: ignore[import] 2025-09-07T09:29:48.5036059Z 2025-09-07T09:29:51.8919110Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:29:51.8919451Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:29:51.8919730Z cuda train timm_nfnet 2025-09-07T09:31:01.1429573Z pass 2025-09-07T09:31:05.6051758Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:31:05.6053147Z import pynvml # type: ignore[import] 2025-09-07T09:31:08.0893298Z 2025-09-07T09:31:11.3798148Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:31:11.3798483Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:31:11.3798759Z cuda train timm_regnet 2025-09-07T09:32:14.3363263Z W0907 09:32:14.335000 45545 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:33:10.4934492Z W0907 09:33:10.492000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4939334Z W0907 09:33:10.493000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4945989Z W0907 09:33:10.494000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4952237Z W0907 09:33:10.494000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4957981Z W0907 09:33:10.495000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4964262Z W0907 09:33:10.496000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4970027Z W0907 09:33:10.496000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4976095Z W0907 09:33:10.497000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4982177Z W0907 09:33:10.497000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.4995738Z W0907 09:33:10.499000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5001758Z W0907 09:33:10.499000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5008235Z W0907 09:33:10.500000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5014005Z W0907 09:33:10.501000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5019717Z W0907 09:33:10.501000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5026191Z W0907 09:33:10.502000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5032293Z W0907 09:33:10.502000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5038141Z W0907 09:33:10.503000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5044319Z W0907 09:33:10.504000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5050057Z W0907 09:33:10.504000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5056608Z W0907 09:33:10.505000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5066466Z W0907 09:33:10.506000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5072374Z W0907 09:33:10.506000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5078556Z W0907 09:33:10.507000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5084529Z W0907 09:33:10.508000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5090320Z W0907 09:33:10.508000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5096584Z W0907 09:33:10.509000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5528033Z W0907 09:33:10.552000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5534485Z W0907 09:33:10.553000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5540483Z W0907 09:33:10.553000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5546950Z W0907 09:33:10.554000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5553409Z W0907 09:33:10.555000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5559825Z W0907 09:33:10.555000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5566320Z W0907 09:33:10.556000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5572734Z W0907 09:33:10.556000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5578950Z W0907 09:33:10.557000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5593009Z W0907 09:33:10.559000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5599025Z W0907 09:33:10.559000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5605986Z W0907 09:33:10.560000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5612262Z W0907 09:33:10.560000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5618350Z W0907 09:33:10.561000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5625142Z W0907 09:33:10.562000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5631669Z W0907 09:33:10.562000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5637803Z W0907 09:33:10.563000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5644382Z W0907 09:33:10.564000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5650559Z W0907 09:33:10.564000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5657033Z W0907 09:33:10.565000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5667278Z W0907 09:33:10.566000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5673511Z W0907 09:33:10.567000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5680086Z W0907 09:33:10.567000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5686561Z W0907 09:33:10.568000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5692809Z W0907 09:33:10.569000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5699189Z W0907 09:33:10.569000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.5719001Z W0907 09:33:10.571000 45545 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:33:10.6722395Z pass 2025-09-07T09:33:16.4271368Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:33:16.4272691Z import pynvml # type: ignore[import] 2025-09-07T09:33:18.8776128Z 2025-09-07T09:33:21.5234994Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:33:21.5235338Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:33:21.5235623Z cuda train timm_resnest 2025-09-07T09:33:59.9912278Z pass 2025-09-07T09:34:03.5734252Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:34:03.5736207Z import pynvml # type: ignore[import] 2025-09-07T09:34:06.0749285Z 2025-09-07T09:34:09.0144701Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:34:09.0145065Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:34:09.0145387Z cuda train timm_vision_transformer 2025-09-07T09:34:46.6463699Z pass 2025-09-07T09:34:50.1462112Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:34:50.1463851Z import pynvml # type: ignore[import] 2025-09-07T09:34:52.6219007Z 2025-09-07T09:35:04.2396562Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:04.2396888Z loading model: 0it [00:11, ?it/s] 2025-09-07T09:35:04.2397166Z cuda train timm_vision_transformer_large 2025-09-07T09:35:04.2781417Z pass_due_to_skip 2025-09-07T09:35:06.0725623Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:06.0726949Z import pynvml # type: ignore[import] 2025-09-07T09:35:08.5155616Z 2025-09-07T09:35:11.1934275Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:35:11.1934680Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:35:11.1934988Z cuda train timm_vovnet 2025-09-07T09:35:51.7557450Z pass 2025-09-07T09:35:55.5295920Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:35:55.5297595Z import pynvml # type: ignore[import] 2025-09-07T09:35:58.0346768Z 2025-09-07T09:36:01.2848710Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:36:01.2849087Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:36:01.2849418Z cuda train torch_multimodal_clip 2025-09-07T09:37:38.2437868Z W0907 09:37:38.243000 47793 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:38:45.2653616Z pass 2025-09-07T09:38:52.4645617Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:38:52.4646793Z import pynvml # type: ignore[import] 2025-09-07T09:38:55.3317575Z 2025-09-07T09:38:56.2085904Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:56.2086461Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:38:56.2086946Z cuda train tts_angular 2025-09-07T09:39:03.4401349Z W0907 09:39:03.439000 48413 site-packages/torch/_logging/_internal.py:1199] [10/0] Profiler function will be ignored 2025-09-07T09:39:08.2723854Z pass 2025-09-07T09:39:11.6897245Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:39:11.6898506Z import pynvml # type: ignore[import] 2025-09-07T09:39:14.1835249Z 2025-09-07T09:39:17.0390540Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:17.0391049Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:39:17.0391461Z cuda train vgg16 2025-09-07T09:39:35.1744547Z pass 2025-09-07T09:39:38.0984690Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:39:38.0986857Z import pynvml # type: ignore[import] 2025-09-07T09:39:40.6313602Z 2025-09-07T09:39:56.0227609Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:39:56.0227932Z loading model: 0it [00:15, ?it/s] 2025-09-07T09:39:56.0228682Z cuda train vision_maskrcnn 2025-09-07T09:39:56.0229161Z Traceback (most recent call last): 2025-09-07T09:39:56.0229619Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1997, in validate_model 2025-09-07T09:39:56.0230079Z self.model_iter_fn(model, example_inputs) 2025-09-07T09:39:56.0232308Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in forward_and_backward_pass 2025-09-07T09:39:56.0232806Z pred = mod(*cloned_inputs) 2025-09-07T09:39:56.0233331Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:39:56.0233851Z return self._call_impl(*args, **kwargs) 2025-09-07T09:39:56.0234366Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:39:56.0234900Z return forward_call(*args, **kwargs) 2025-09-07T09:39:56.0235512Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in forward 2025-09-07T09:39:56.0236304Z detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T09:39:56.0237045Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:39:56.0237605Z return self._call_impl(*args, **kwargs) 2025-09-07T09:39:56.0238135Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:39:56.0238666Z return forward_call(*args, **kwargs) 2025-09-07T09:39:56.0239235Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T09:39:56.0239894Z box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T09:39:56.0241110Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T09:39:56.0241686Z return self._call_impl(*args, **kwargs) 2025-09-07T09:39:56.0242204Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T09:39:56.0242723Z return forward_call(*args, **kwargs) 2025-09-07T09:39:56.0243225Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 314, in forward 2025-09-07T09:39:56.0243726Z return _multiscale_roi_align( 2025-09-07T09:39:56.0244272Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 204, in _multiscale_roi_align 2025-09-07T09:39:56.0244845Z result_idx_in_level = roi_align( 2025-09-07T09:39:56.0245259Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in roi_align 2025-09-07T09:39:56.0245830Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T09:39:56.0246420Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 27, in compile_hook 2025-09-07T09:39:56.0246855Z return compiled_fn(*args, **kwargs) 2025-09-07T09:39:56.0247304Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 832, in compile_wrapper 2025-09-07T09:39:56.0247735Z return fn(*args, **kwargs) 2025-09-07T09:39:56.0248132Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1875, in __call__ 2025-09-07T09:39:56.0248874Z result = self._torchdynamo_orig_backend( 2025-09-07T09:39:56.0249319Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1624, in __call__ 2025-09-07T09:39:56.0249741Z result = self._inner_convert( 2025-09-07T09:39:56.0250151Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 688, in __call__ 2025-09-07T09:39:56.0250721Z result = _compile( 2025-09-07T09:39:56.0251250Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1494, in _compile 2025-09-07T09:39:56.0251691Z raise InternalTorchDynamoError( 2025-09-07T09:39:56.0252118Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1433, in _compile 2025-09-07T09:39:56.0252604Z guarded_code, tracer_output = compile_inner(code, one_graph, hooks) 2025-09-07T09:39:56.0253106Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_utils_internal.py", line 92, in wrapper_function 2025-09-07T09:39:56.0253553Z return function(*args, **kwargs) 2025-09-07T09:39:56.0254012Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1117, in compile_inner 2025-09-07T09:39:56.0254492Z return _compile_inner(code, one_graph, hooks) 2025-09-07T09:39:56.0254958Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1151, in _compile_inner 2025-09-07T09:39:56.0255402Z dynamo_output = compile_frame( 2025-09-07T09:39:56.0255837Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1032, in compile_frame 2025-09-07T09:39:56.0256343Z bytecode, tracer_output = transform_code_object(code, transform) 2025-09-07T09:39:56.0256919Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/bytecode_transformation.py", line 1592, in transform_code_object 2025-09-07T09:39:56.0257479Z tracer_output = transformations(instructions, code_options) 2025-09-07T09:39:56.0257970Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 1004, in transform 2025-09-07T09:39:56.0258410Z tracer_output = trace_frame( 2025-09-07T09:39:56.0258801Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/convert_frame.py", line 333, in _fn 2025-09-07T09:39:56.0259226Z torch.cuda.set_rng_state(cuda_rng_state) 2025-09-07T09:39:56.0259646Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/random.py", line 79, in set_rng_state 2025-09-07T09:39:56.0260054Z _lazy_call(cb) 2025-09-07T09:39:56.0260586Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py", line 341, in _lazy_call 2025-09-07T09:39:56.0260975Z callable() 2025-09-07T09:39:56.0261301Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/random.py", line 77, in cb 2025-09-07T09:39:56.0261684Z default_generator.set_state(new_state) 2025-09-07T09:39:56.0262110Z torch._dynamo.exc.InternalTorchDynamoError: AcceleratorError: CUDA error: device-side assert triggered 2025-09-07T09:39:56.0262875Z Search for `cudaErrorAssert' in https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html for more information. 2025-09-07T09:39:56.0263572Z CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. 2025-09-07T09:39:56.0264055Z For debugging consider passing CUDA_LAUNCH_BLOCKING=1 2025-09-07T09:39:56.0264408Z Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. 2025-09-07T09:39:56.0264633Z 2025-09-07T09:39:56.0264637Z 2025-09-07T09:39:56.0264640Z 2025-09-07T09:39:56.0264798Z The above exception was the direct cause of the following exception: 2025-09-07T09:39:56.0265024Z 2025-09-07T09:39:56.0265106Z Traceback (most recent call last): 2025-09-07T09:39:56.0265443Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 4172, in run 2025-09-07T09:39:56.0265967Z ) = runner.load_model( 2025-09-07T09:39:56.0266323Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 401, in load_model 2025-09-07T09:39:56.0266732Z self.validate_model(model, example_inputs) 2025-09-07T09:39:56.0267138Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1999, in validate_model 2025-09-07T09:39:56.0267544Z raise RuntimeError("Eager run failed") from e 2025-09-07T09:39:56.0267938Z RuntimeError: Eager run failed 2025-09-07T09:39:56.0268079Z 2025-09-07T09:39:56.0268149Z eager_fail_to_run 2025-09-07T09:39:57.8384745Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8386880Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8388743Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8391196Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8393439Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8395559Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8397191Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8398988Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8400873Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8402358Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8404088Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8405564Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8407150Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8408357Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8409561Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8410888Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8412957Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8414653Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8416695Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8418342Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8419692Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8421035Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8422228Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8423521Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8424722Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8425921Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8427658Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8429042Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8430372Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8431598Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8432828Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8434357Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25984,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8435560Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8437128Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8438727Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8440576Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8442369Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8444015Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8445216Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8446409Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8447599Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8449093Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8450825Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8452016Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8453212Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8454569Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8455760Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8457353Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8458886Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8460444Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8462110Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8463826Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8465393Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8467240Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8468704Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8470723Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8472289Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8473780Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8475505Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8477035Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8478227Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8479519Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8481114Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8482563Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25486,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8483768Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8484955Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8486158Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8487365Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8488551Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8489754Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8491087Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8492276Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8493639Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8494971Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8496168Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8497360Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8498556Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8499758Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8501139Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8502327Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8503591Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8504800Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8506001Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8507284Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8508477Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8509673Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8511001Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8512197Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8513383Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8514573Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8515914Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8517130Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8518426Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8519620Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8520940Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8522128Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25129,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8523314Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8524509Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8525692Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8526895Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8528097Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8529289Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8530586Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8531786Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8532977Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8534166Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8535354Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8536550Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8537739Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8539082Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8540524Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8541726Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8543001Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8544199Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8545382Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8546573Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8547771Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8548969Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8550155Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8551507Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8552689Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8553875Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8555070Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8556276Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8557463Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8558655Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8559843Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8561332Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25183,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8562517Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8563836Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8565031Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8566218Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8567405Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8568610Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8569803Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8571135Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8572320Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8573512Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8574706Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8575900Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8577095Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8578294Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8579485Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8580788Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8581979Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8583241Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8584595Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8585911Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8587104Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8588294Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8589477Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8590818Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8592011Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8593220Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8594414Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8595600Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8596791Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8597986Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8599174Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8600484Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8601684Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8602883Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8604082Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8605277Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8606466Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8607794Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8609108Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8610429Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8611630Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8612823Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8614019Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8615215Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8616401Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8617588Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8618791Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8619983Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8621276Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8622468Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8623756Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8624942Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8626128Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8627317Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8628506Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8629839Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8631297Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8632522Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8633718Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8634917Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8636113Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8637300Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8638506Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8639700Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26022,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8641062Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8642258Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8643467Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8644659Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8645844Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8647040Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8648230Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8649416Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8650723Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8651923Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8653259Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8654560Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8655751Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8656938Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8658129Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8659326Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8660655Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8661840Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8663093Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8664279Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8665473Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8666656Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8667843Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8669025Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8670336Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8671532Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8672742Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8673919Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8675286Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8676475Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8677784Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8678974Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8680176Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8681499Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8682689Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8683882Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8685074Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8686271Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8687459Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8688655Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8689846Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8691166Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8692374Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8693576Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8694772Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8695975Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8697170Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8698506Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8699802Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8701114Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8702309Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8703589Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8704776Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8705979Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8707170Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8708356Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8709558Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8710896Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8712080Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8713268Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8714459Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8715657Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8716851Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8718043Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26121,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8719228Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8720722Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8721925Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8723235Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8724446Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8725635Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8726826Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8728011Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8729199Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8730502Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8731699Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8732898Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8734105Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8735299Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8736491Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8737675Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8738864Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8740059Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8741405Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8742613Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8744035Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8745388Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8746584Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8747783Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8748975Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8750168Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8751510Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8752748Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8753948Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8755144Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8756346Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8757539Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26145,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8758737Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8759933Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8761243Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8762434Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8763626Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8764811Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8766138Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8767339Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8768824Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8770028Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8771356Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8772555Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8773744Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8774948Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8776146Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8777333Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8778527Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8779721Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8781039Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8782230Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8783496Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8784684Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8785895Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8787093Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8788285Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8789644Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8791102Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8792296Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8793487Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8794680Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8795881Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8797096Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25177,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8798301Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8799500Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8800832Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8802045Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8803248Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8804442Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8805643Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8806846Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8808039Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8809237Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8810539Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8811899Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8813092Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8814396Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8815591Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8816781Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8817985Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8819173Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8820494Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8821703Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8822995Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8824205Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8825415Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8826615Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8827810Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8828999Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8830189Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8831511Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8832705Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8833903Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8835255Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8836585Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25140,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8837792Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8838987Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8840196Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8841516Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8842730Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8843921Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8845110Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8846307Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8847512Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8848717Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8849934Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8851277Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8852475Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8853672Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8854865Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8856055Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8857262Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8858602Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8859927Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8861249Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8862447Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8863741Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8864931Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8866114Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8867303Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8868493Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8869682Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8870991Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8872188Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8873384Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8874576Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8875761Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25139,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8876952Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8878148Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8879334Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8880803Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8882121Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8883315Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8884504Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8885702Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8886900Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8888109Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8889303Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8890626Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8891824Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8893008Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8894212Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8895405Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8896595Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8897786Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8898983Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8900168Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8901469Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8902732Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8904082Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8905393Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8906594Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8907789Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8908980Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8910173Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8911497Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8912698Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8913899Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8915092Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25326,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8916285Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8917487Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8918680Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8919862Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8921193Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8922383Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8923570Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8924758Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8926149Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8927343Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8928651Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8929843Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8931188Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8932386Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8933575Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8934767Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8935968Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8937167Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8938351Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8939562Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8940878Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8942067Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8943351Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8944546Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8945738Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8946921Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8948111Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8949456Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8950886Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8952095Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8953286Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8954484Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25147,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8955691Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8956874Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8958061Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8959276Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8960596Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8961800Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8962999Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8964198Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8965399Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8966591Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8967792Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8968996Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8970187Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8971662Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8972868Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8974178Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8975392Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8976581Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8977776Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8978969Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8980174Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8981513Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8982779Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8983970Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8985154Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8986341Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8987532Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8988724Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8989914Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8991254Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8992458Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8993639Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25481,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8995000Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8996318Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8997518Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8998712Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.8999907Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9001238Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9002425Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9003617Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9004812Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9006015Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9007214Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9008406Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9009600Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9010904Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9012099Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9013307Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9014493Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9015692Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9017066Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9018262Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9019566Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9020898Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9022090Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9023345Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9024539Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9025739Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9026934Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9028122Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9029309Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9030621Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9031843Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9033046Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26115,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9034251Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9035444Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9036636Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9037820Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9039003Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9040455Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9041771Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9042974Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9044159Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9045350Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9046546Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9047748Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9048945Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9050147Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9051468Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9052661Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9053852Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9055048Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9056236Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9057433Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9058634Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9059820Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9061127Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9062473Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9063751Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9065066Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9066266Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9067456Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9068663Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9069869Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9071189Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9072388Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25566,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9073578Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9074771Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9076054Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9077247Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9078443Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9079636Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9080938Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9082149Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9083340Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9084532Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9085874Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9087202Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9088397Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9101057Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9102331Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9103622Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9104846Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9106045Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9107271Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9108472Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9109675Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9110997Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9112211Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9113425Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9114638Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9115826Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9117018Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9118221Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9119420Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9121018Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9122378Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9123590Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26295,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9124788Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9125993Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9127187Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9128390Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9129594Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9130921Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9132119Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9133314Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9134511Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9135724Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9136924Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9138122Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9139328Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9140625Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9141822Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9143256Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9144575Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9145786Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9146998Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9148206Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9149424Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9150759Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9151953Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9153156Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9154350Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9155547Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9156742Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9157941Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9159135Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9160454Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9161649Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9162949Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25755,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9164137Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9165338Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9166677Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9167986Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9169183Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9170487Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9171701Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9172904Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9174101Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9175296Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9176492Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9177690Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9178879Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9180069Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9181380Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9182576Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9183860Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9185052Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9186242Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9187440Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9188776Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9189973Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9191436Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9192640Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9193835Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9195034Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9196246Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9197435Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9198626Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9199817Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9201156Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9202354Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25191,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9203551Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9204747Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9205945Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9207130Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9208326Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9209534Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9210858Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9212220Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9213553Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9214761Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9215958Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9217171Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9218373Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9219570Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9220899Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9222103Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9223368Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9224566Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9225758Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9226947Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9228143Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9229355Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9230698Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9231916Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9233104Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9234456Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9235664Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9236983Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9238175Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9239375Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9240701Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9241904Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25410,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9243093Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9244284Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9245470Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9246666Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9247858Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9249050Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9250355Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9251558Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9252757Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9253954Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9255158Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9256354Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9257696Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9259014Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9260327Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9261528Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9262777Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9263972Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9265172Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9266363Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9267567Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9268760Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9269944Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9271248Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9272439Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9273631Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9274829Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9276037Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9277235Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9278428Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9279797Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9281200Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [25536,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9282537Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [0,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9283741Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [1,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9284948Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [2,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9286148Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [3,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9287337Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [4,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9288528Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [5,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9289717Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [6,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9291045Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [7,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9292244Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [8,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9293439Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [9,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9294629Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [10,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9295830Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [11,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9297033Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [12,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9298221Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [13,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9299417Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [14,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9300745Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [15,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9301955Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [16,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9303370Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [17,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9304689Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [18,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9305893Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [19,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9307083Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [20,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9308276Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [21,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9309463Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [22,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9310797Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [23,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9312000Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [24,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9313187Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [25,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9314381Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [26,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9315572Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [27,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9316766Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [28,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9317976Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [29,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9319159Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [30,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9320500Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26384,0,0], thread: [31,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9321719Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [32,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9322916Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [33,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9324105Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [34,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9325306Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [35,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9326641Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [36,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9327964Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [37,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9329165Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [38,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9330484Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [39,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9331681Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [40,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9332863Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [41,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9334056Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [42,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9335254Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [43,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9336441Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [44,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9337634Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [45,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9338830Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [46,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9340023Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [47,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9341330Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [48,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9342538Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [49,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9343797Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [50,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9345006Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [51,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9346192Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [52,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9347391Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [53,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9348735Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [54,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9350049Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [55,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9351399Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [56,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9352590Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [57,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9353800Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [58,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9354995Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [59,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9356193Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [60,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9357386Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [61,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9358579Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [62,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:57.9359766Z /tmp/torchinductor_jenkins/mf/cmfi6syasmte4jdrygg45jkzxjeebq4y3nrdbe5t33b6qq42xrdm.py:56: unknown: block: [26094,0,0], thread: [63,0,0] Assertion `index out of bounds: 0 <= tmp10 < 1` failed. 2025-09-07T09:39:58.9058853Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:39:58.9060735Z import pynvml # type: ignore[import] 2025-09-07T09:40:01.4476195Z 2025-09-07T09:40:04.2205129Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:40:04.2205488Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:40:04.2205777Z cuda train yolov3 2025-09-07T09:41:58.8528727Z W0907 09:41:58.851000 49763 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:42:47.4731256Z pass 2025-09-07T09:42:54.2959071Z accuracy pass_rate=80.00% 2025-09-07T09:42:54.2964296Z calls_captured gmean=0.00x mean=670.667x 2025-09-07T09:42:54.2967732Z unique_graphs gmean=0.00x mean=2.267x 2025-09-07T09:42:54.2971624Z graph_breaks gmean=0.00x mean=5.400x 2025-09-07T09:42:54.2983416Z unique_graph_breaks gmean=0.00x mean=4.133x 2025-09-07T09:42:54.2986993Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T09:42:54.2990799Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T09:42:54.2994084Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T09:42:54.2995073Z compilation_latency mean=82.307 seconds 2025-09-07T09:42:55.3322492Z + [[ 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* ]] 2025-09-07T09:42:55.3325457Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:42:55.3327256Z + [[ 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* ]] 2025-09-07T09:42:55.3328500Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:42:55.3329931Z + [[ 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* ]] 2025-09-07T09:42:55.3331410Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T09:42:55.3332542Z + [[ 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* ]] 2025-09-07T09:42:55.3333699Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T09:42:55.3334909Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --training --amp --backend inductor --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.csv 2025-09-07T09:42:55.8750437Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:42:55.8751692Z import pynvml # type: ignore[import] 2025-09-07T09:42:59.7598723Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:42:59.7599925Z import pynvml # type: ignore[import] 2025-09-07T09:43:02.2222223Z 2025-09-07T09:43:03.8656249Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:43:03.8656506Z 2025-09-07T09:43:04.4095776Z Loading pipeline components...: 0% 0/6 [00:00 will be ignored 2025-09-07T09:50:26.5929391Z pass 2025-09-07T09:50:32.5282425Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:50:32.5283788Z import pynvml # type: ignore[import] 2025-09-07T09:50:35.1846587Z 2025-09-07T09:50:38.6317213Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:50:38.6317586Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:50:38.6317865Z cuda train timm_nfnet 2025-09-07T09:50:59.2196524Z Autotune Choices Stats: 2025-09-07T09:50:59.2197827Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_15", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.02067199908196926, "best_triton_pos": 0} 2025-09-07T09:50:59.4430400Z AUTOTUNE convolution(4x32x96x96, 64x32x3x3) 2025-09-07T09:50:59.4430715Z strides: [294912, 9216, 96, 1], [288, 9, 3, 1] 2025-09-07T09:50:59.4431001Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:59.4431720Z triton_convolution2d_15 0.0207 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:59.4432905Z triton_convolution2d_14 0.0220 ms 93.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:59.4434080Z triton_convolution2d_11 0.0224 ms 92.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:59.4435210Z triton_convolution2d_16 0.0225 ms 91.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:50:59.4436347Z triton_convolution2d_12 0.0236 ms 87.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:50:59.4437486Z triton_convolution2d_17 0.0242 ms 85.4% 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 2025-09-07T09:50:59.4438174Z convolution 0.0344 ms 60.0% 2025-09-07T09:50:59.4438866Z triton_convolution2d_13 0.0697 ms 29.6% 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 2025-09-07T09:50:59.4439769Z SingleProcess AUTOTUNE benchmarking takes 0.3351 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:50:59.8845903Z Autotune Choices Stats: 2025-09-07T09:50:59.8847059Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_29", "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": 0.011296000331640244, "best_triton_pos": 0} 2025-09-07T09:50:59.9195576Z AUTOTUNE convolution(4x128x48x48, 256x128x1x1) 2025-09-07T09:50:59.9195956Z strides: [294912, 2304, 48, 1], [128, 1, 1, 1] 2025-09-07T09:50:59.9196265Z dtypes: torch.float16, torch.float16 2025-09-07T09:50:59.9197841Z triton_convolution2d_29 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 2025-09-07T09:50:59.9198699Z convolution 0.0114 ms 98.9% 2025-09-07T09:50:59.9199538Z triton_convolution2d_31 0.0130 ms 86.9% 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 2025-09-07T09:50:59.9201340Z triton_convolution2d_28 0.0130 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 2025-09-07T09:50:59.9202722Z triton_convolution2d_25 0.0141 ms 80.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:50:59.9204053Z triton_convolution2d_26 0.0148 ms 76.1% 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 2025-09-07T09:50:59.9205375Z triton_convolution2d_30 0.0165 ms 68.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:50:59.9206698Z triton_convolution2d_27 0.0170 ms 66.4% 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 2025-09-07T09:50:59.9207408Z conv1x1_via_mm 0.0484 ms 23.3% 2025-09-07T09:50:59.9207841Z SingleProcess AUTOTUNE benchmarking takes 0.1713 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:00.4259506Z Autotune Choices Stats: 2025-09-07T09:51:00.4261597Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011359999887645245, "best_triton_pos": 1, "best_triton_time": 0.014495999552309513, "best_triton_kernel": "triton_convolution2d_82", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:00.6300404Z AUTOTUNE convolution(4x256x48x48, 256x256x1x1) 2025-09-07T09:51:00.6300769Z strides: [589824, 2304, 48, 1], [256, 1, 1, 1] 2025-09-07T09:51:00.6301075Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:00.6301395Z convolution 0.0114 ms 100.0% 2025-09-07T09:51:00.6302207Z triton_convolution2d_82 0.0145 ms 78.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:00.6303649Z triton_convolution2d_81 0.0171 ms 66.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:00.6304981Z triton_convolution2d_84 0.0172 ms 66.1% 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 2025-09-07T09:51:00.6306328Z triton_convolution2d_78 0.0203 ms 56.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:00.6308026Z triton_convolution2d_79 0.0216 ms 52.5% 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 2025-09-07T09:51:00.6309306Z triton_convolution2d_83 0.0226 ms 50.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:00.6310996Z triton_convolution2d_80 0.0263 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 2025-09-07T09:51:00.6311812Z conv1x1_via_mm 0.0593 ms 19.2% 2025-09-07T09:51:00.6312287Z SingleProcess AUTOTUNE benchmarking takes 0.3399 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:01.0284302Z Autotune Choices Stats: 2025-09-07T09:51:01.0285822Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010975999757647514, "best_triton_pos": 1, "best_triton_time": 0.0191040001809597, "best_triton_kernel": "triton_convolution2d_141", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:01.1043941Z AUTOTUNE convolution(4x512x24x24, 768x512x1x1) 2025-09-07T09:51:01.1044350Z strides: [294912, 576, 24, 1], [512, 1, 1, 1] 2025-09-07T09:51:01.1044673Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:01.1044965Z convolution 0.0110 ms 100.0% 2025-09-07T09:51:01.1045730Z triton_convolution2d_141 0.0191 ms 57.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:01.1047057Z triton_convolution2d_140 0.0221 ms 49.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:01.1048251Z triton_convolution2d_143 0.0227 ms 48.4% 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 2025-09-07T09:51:01.1049423Z triton_convolution2d_142 0.0236 ms 46.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:01.1061311Z triton_convolution2d_137 0.0315 ms 34.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:01.1062430Z triton_convolution2d_138 0.0319 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 2025-09-07T09:51:01.1063601Z triton_convolution2d_139 0.0424 ms 25.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:01.1064224Z conv1x1_via_mm 0.0485 ms 22.6% 2025-09-07T09:51:01.1064641Z SingleProcess AUTOTUNE benchmarking takes 0.2169 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:01.4420704Z Autotune Choices Stats: 2025-09-07T09:51:01.4421865Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_5", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.01196799986064434, "best_triton_pos": 0} 2025-09-07T09:51:01.5484946Z AUTOTUNE convolution(4x16x96x96, 32x16x3x3) 2025-09-07T09:51:01.5485302Z strides: [147456, 9216, 96, 1], [144, 9, 3, 1] 2025-09-07T09:51:01.5485618Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:01.5486403Z triton_convolution2d_5 0.0120 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:01.5488028Z triton_convolution2d_8 0.0125 ms 95.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:01.5489277Z triton_convolution2d_9 0.0130 ms 92.3% 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=8 2025-09-07T09:51:01.5490824Z triton_convolution2d_6 0.0131 ms 91.7% 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 2025-09-07T09:51:01.5492079Z triton_convolution2d_10 0.0135 ms 88.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:01.5493307Z triton_convolution2d_7 0.0233 ms 51.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:01.5494059Z convolution 0.0248 ms 48.2% 2025-09-07T09:51:01.5494546Z SingleProcess AUTOTUNE benchmarking takes 0.1961 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:51:01.9788623Z Autotune Choices Stats: 2025-09-07T09:51:01.9789746Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_21", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.02735999971628189, "best_triton_pos": 0} 2025-09-07T09:51:02.2015660Z AUTOTUNE convolution(4x64x97x97, 128x64x3x3) 2025-09-07T09:51:02.2016033Z strides: [602176, 9409, 97, 1], [576, 9, 3, 1] 2025-09-07T09:51:02.2016344Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:02.2017146Z triton_convolution2d_21 0.0274 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:02.2018441Z triton_convolution2d_24 0.0283 ms 96.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:02.2019663Z triton_convolution2d_22 0.0299 ms 91.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:02.2021203Z triton_convolution2d_23 0.0307 ms 89.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:02.2021957Z convolution 0.0319 ms 85.8% 2025-09-07T09:51:02.2022677Z triton_convolution2d_19 0.0361 ms 75.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:02.2023983Z triton_convolution2d_18 0.0365 ms 75.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:02.2025533Z triton_convolution2d_20 0.0984 ms 27.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:02.2026520Z SingleProcess AUTOTUNE benchmarking takes 0.3327 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:02.6565739Z Autotune Choices Stats: 2025-09-07T09:51:02.6567597Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009855999611318111, "best_triton_pos": 1, "best_triton_time": 0.011071999557316303, "best_triton_kernel": "triton_convolution2d_37", "best_triton_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"} 2025-09-07T09:51:02.8779200Z AUTOTUNE convolution(4x128x48x48, 128x128x1x1) 2025-09-07T09:51:02.8779570Z strides: [294912, 2304, 48, 1], [128, 1, 1, 1] 2025-09-07T09:51:02.8779891Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:02.8780178Z convolution 0.0099 ms 100.0% 2025-09-07T09:51:02.8781315Z triton_convolution2d_37 0.0111 ms 89.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:02.8782592Z triton_convolution2d_36 0.0112 ms 88.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:02.8783933Z triton_convolution2d_35 0.0124 ms 79.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:02.8785163Z triton_convolution2d_32 0.0125 ms 79.0% 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 2025-09-07T09:51:02.8786386Z triton_convolution2d_38 0.0127 ms 77.6% 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 2025-09-07T09:51:02.8787756Z triton_convolution2d_33 0.0146 ms 67.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:02.8788984Z triton_convolution2d_34 0.0160 ms 61.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:02.8789757Z conv1x1_via_mm 0.0372 ms 26.5% 2025-09-07T09:51:02.8790350Z SingleProcess AUTOTUNE benchmarking takes 0.3596 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:03.6093415Z Autotune Choices Stats: 2025-09-07T09:51:03.6094864Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03299200162291527, "best_triton_pos": 1, "best_triton_time": 0.04255999997258186, "best_triton_kernel": "triton_convolution2d_45", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:51:03.8029090Z AUTOTUNE convolution(4x128x48x48, 128x128x3x3) 2025-09-07T09:51:03.8029468Z strides: [294912, 2304, 48, 1], [1152, 9, 3, 1] 2025-09-07T09:51:03.8029768Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:03.8030042Z convolution 0.0330 ms 100.0% 2025-09-07T09:51:03.8031100Z triton_convolution2d_45 0.0426 ms 77.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:03.8032876Z triton_convolution2d_42 0.0485 ms 68.0% 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 2025-09-07T09:51:03.8034335Z triton_convolution2d_43 0.0496 ms 66.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:03.8035561Z triton_convolution2d_44 0.0552 ms 59.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:03.8036780Z triton_convolution2d_40 0.0624 ms 52.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:03.8037995Z triton_convolution2d_39 0.0702 ms 47.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:03.8039224Z triton_convolution2d_41 0.1525 ms 21.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:03.8040193Z SingleProcess AUTOTUNE benchmarking takes 0.6176 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:04.0520999Z Autotune Choices Stats: 2025-09-07T09:51:04.0522653Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.008960000239312649, "best_triton_pos": 1, "best_triton_time": 0.012864000163972378, "best_triton_kernel": "triton_convolution2d_75", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:04.2377054Z AUTOTUNE convolution(4x256x24x24, 512x256x1x1) 2025-09-07T09:51:04.2377458Z strides: [147456, 576, 24, 1], [256, 1, 1, 1] 2025-09-07T09:51:04.2377789Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:04.2378119Z convolution 0.0090 ms 100.0% 2025-09-07T09:51:04.2378932Z triton_convolution2d_75 0.0129 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 2025-09-07T09:51:04.2380200Z triton_convolution2d_76 0.0140 ms 63.8% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:04.2381836Z triton_convolution2d_74 0.0146 ms 61.3% 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 2025-09-07T09:51:04.2383184Z triton_convolution2d_77 0.0156 ms 57.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:04.2384425Z triton_convolution2d_71 0.0180 ms 49.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:04.2385648Z triton_convolution2d_72 0.0196 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 2025-09-07T09:51:04.2386873Z triton_convolution2d_73 0.0220 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 2025-09-07T09:51:04.2388199Z conv1x1_via_mm 0.0350 ms 25.6% 2025-09-07T09:51:04.2388643Z SingleProcess AUTOTUNE benchmarking takes 0.3191 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:04.8521815Z Autotune Choices Stats: 2025-09-07T09:51:04.8523977Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010080000385642052, "best_triton_pos": 1, "best_triton_time": 0.018400000408291817, "best_triton_kernel": "triton_convolution2d_134", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:04.8681852Z AUTOTUNE convolution(4x512x12x12, 1536x512x1x1) 2025-09-07T09:51:04.8682196Z strides: [73728, 144, 12, 1], [512, 1, 1, 1] 2025-09-07T09:51:04.8682501Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:04.8682805Z convolution 0.0101 ms 100.0% 2025-09-07T09:51:04.8683593Z triton_convolution2d_134 0.0184 ms 54.8% 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 2025-09-07T09:51:04.8684903Z triton_convolution2d_133 0.0220 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 2025-09-07T09:51:04.8686181Z triton_convolution2d_135 0.0225 ms 44.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:04.8687431Z triton_convolution2d_136 0.0225 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 2025-09-07T09:51:04.8688719Z triton_convolution2d_130 0.0314 ms 32.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:04.8689846Z triton_convolution2d_131 0.0323 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 2025-09-07T09:51:04.8690869Z conv1x1_via_mm 0.0327 ms 30.9% 2025-09-07T09:51:04.8691572Z triton_convolution2d_132 0.0373 ms 27.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:04.8692478Z SingleProcess AUTOTUNE benchmarking takes 0.1524 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:05.2871166Z Autotune Choices Stats: 2025-09-07T09:51:05.2872330Z {"num_choices": 6, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_0", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.009952000342309475, "best_triton_pos": 0} 2025-09-07T09:51:05.4621916Z AUTOTUNE convolution(4x3x193x193, 16x3x3x3) 2025-09-07T09:51:05.4622337Z strides: [111747, 37249, 193, 1], [27, 9, 3, 1] 2025-09-07T09:51:05.4622666Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:05.4623560Z triton_convolution2d_0 0.0100 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:05.4624785Z triton_convolution2d_3 0.0109 ms 91.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:05.4626479Z triton_convolution2d_1 0.0116 ms 85.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:51:05.4627924Z triton_convolution2d_4 0.0116 ms 85.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:51:05.4628784Z convolution 0.0122 ms 81.4% 2025-09-07T09:51:05.4629502Z triton_convolution2d_2 0.0148 ms 67.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:51:05.4631007Z SingleProcess AUTOTUNE benchmarking takes 0.2511 seconds and 0.0002 seconds precompiling for 6 choices 2025-09-07T09:51:05.9182233Z Autotune Choices Stats: 2025-09-07T09:51:05.9183850Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009631999768316746, "best_triton_pos": 1, "best_triton_time": 0.01775999926030636, "best_triton_kernel": "triton_convolution2d_108", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:06.1252290Z AUTOTUNE convolution(4x512x24x24, 256x512x1x1) 2025-09-07T09:51:06.1252691Z strides: [294912, 576, 24, 1], [512, 1, 1, 1] 2025-09-07T09:51:06.1253021Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:06.1253313Z convolution 0.0096 ms 100.0% 2025-09-07T09:51:06.1254079Z triton_convolution2d_108 0.0178 ms 54.2% 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 2025-09-07T09:51:06.1255387Z triton_convolution2d_107 0.0218 ms 44.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:06.1256637Z triton_convolution2d_110 0.0223 ms 43.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:06.1257897Z triton_convolution2d_109 0.0232 ms 41.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:06.1259174Z triton_convolution2d_104 0.0314 ms 30.7% 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 2025-09-07T09:51:06.1260741Z triton_convolution2d_105 0.0320 ms 30.1% 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 2025-09-07T09:51:06.1261444Z conv1x1_via_mm 0.0339 ms 28.4% 2025-09-07T09:51:06.1262131Z triton_convolution2d_106 0.0374 ms 25.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:06.1263092Z SingleProcess AUTOTUNE benchmarking takes 0.3420 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:06.8442592Z Autotune Choices Stats: 2025-09-07T09:51:06.8444898Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012671999633312225, "best_triton_pos": 2, "best_triton_time": 0.0414079986512661, "best_triton_kernel": "triton_convolution2d_167", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:07.0190941Z AUTOTUNE convolution(4x1536x12x12, 768x1536x1x1) 2025-09-07T09:51:07.0191271Z strides: [221184, 144, 12, 1], [1536, 1, 1, 1] 2025-09-07T09:51:07.0191562Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:07.0191829Z convolution 0.0127 ms 100.0% 2025-09-07T09:51:07.0192403Z conv1x1_via_mm 0.0364 ms 34.8% 2025-09-07T09:51:07.0193158Z triton_convolution2d_167 0.0414 ms 30.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:07.0194405Z triton_convolution2d_166 0.0500 ms 25.3% 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 2025-09-07T09:51:07.0195629Z triton_convolution2d_168 0.0512 ms 24.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:07.0196850Z triton_convolution2d_169 0.0529 ms 24.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:07.0198067Z triton_convolution2d_163 0.0764 ms 16.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:07.0199279Z triton_convolution2d_164 0.0814 ms 15.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:07.0200803Z triton_convolution2d_165 0.0998 ms 12.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:07.0201738Z SingleProcess AUTOTUNE benchmarking takes 0.5980 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:07.7728112Z Autotune Choices Stats: 2025-09-07T09:51:07.7730983Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021056000143289566, "best_triton_pos": 2, "best_triton_time": 0.042367998510599136, "best_triton_kernel": "triton_convolution2d_297", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:07.7843634Z AUTOTUNE convolution(4x1536x6x6, 1536x1536x1x1) 2025-09-07T09:51:07.7844236Z strides: [55296, 36, 6, 1], [1536, 1, 1, 1] 2025-09-07T09:51:07.7844745Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:07.7845203Z convolution 0.0211 ms 100.0% 2025-09-07T09:51:07.7845598Z conv1x1_via_mm 0.0397 ms 53.1% 2025-09-07T09:51:07.7846804Z triton_convolution2d_297 0.0424 ms 49.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:07.7848887Z triton_convolution2d_296 0.0544 ms 38.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:07.7850480Z triton_convolution2d_298 0.0547 ms 38.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:07.7851619Z triton_convolution2d_299 0.0559 ms 37.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:07.7853197Z triton_convolution2d_295 0.0651 ms 32.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:07.7854540Z triton_convolution2d_294 0.0699 ms 30.1% 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 2025-09-07T09:51:07.7855663Z triton_convolution2d_293 0.0783 ms 26.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:07.7856557Z SingleProcess AUTOTUNE benchmarking takes 0.1697 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:08.6313023Z Autotune Choices Stats: 2025-09-07T09:51:08.6314489Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.022431999444961548, "best_triton_pos": 2, "best_triton_time": 0.042688000947237015, "best_triton_kernel": "triton_convolution2d_330", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:08.8055887Z AUTOTUNE convolution(4x1536x6x6, 768x1536x1x1) 2025-09-07T09:51:08.8056213Z strides: [55296, 36, 6, 1], [1536, 1, 1, 1] 2025-09-07T09:51:08.8056474Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:08.8056713Z convolution 0.0224 ms 100.0% 2025-09-07T09:51:08.8056931Z conv1x1_via_mm 0.0313 ms 71.8% 2025-09-07T09:51:08.8057584Z triton_convolution2d_330 0.0427 ms 52.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:08.8058695Z triton_convolution2d_329 0.0532 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 2025-09-07T09:51:08.8059795Z triton_convolution2d_331 0.0539 ms 41.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:08.8061216Z triton_convolution2d_332 0.0558 ms 40.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:08.8062277Z triton_convolution2d_328 0.0649 ms 34.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:08.8063428Z triton_convolution2d_327 0.0718 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 2025-09-07T09:51:08.8064492Z triton_convolution2d_326 0.0798 ms 28.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:08.8065329Z SingleProcess AUTOTUNE benchmarking takes 0.3298 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:09.2391357Z Autotune Choices Stats: 2025-09-07T09:51:09.2392810Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.011136000044643879, "best_triton_pos": 2, "best_triton_time": 0.021503999829292297, "best_triton_kernel": "triton_convolution2d_161", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:09.3596985Z AUTOTUNE convolution(4x768x1x1, 1536x768x1x1) 2025-09-07T09:51:09.3597326Z strides: [768, 1, 1, 1], [768, 1, 1, 1] 2025-09-07T09:51:09.3597605Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:09.3597883Z convolution 0.0111 ms 100.0% 2025-09-07T09:51:09.3598510Z conv1x1_via_mm 0.0122 ms 91.6% 2025-09-07T09:51:09.3599327Z triton_convolution2d_161 0.0215 ms 51.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:09.3601112Z triton_convolution2d_160 0.0235 ms 47.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:09.3602394Z triton_convolution2d_162 0.0274 ms 40.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:09.3603679Z triton_convolution2d_159 0.0275 ms 40.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:51:09.3604928Z triton_convolution2d_158 0.0304 ms 36.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:09.3606167Z triton_convolution2d_157 0.0383 ms 29.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:09.3607164Z SingleProcess AUTOTUNE benchmarking takes 0.2425 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:09.8052665Z Autotune Choices Stats: 2025-09-07T09:51:09.8054075Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.0098879998549819, "best_triton_pos": 2, "best_triton_time": 0.03702399879693985, "best_triton_kernel": "triton_convolution2d_155", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:09.9983070Z AUTOTUNE convolution(4x1536x1x1, 768x1536x1x1) 2025-09-07T09:51:09.9983425Z strides: [1536, 1, 1, 1], [1536, 1, 1, 1] 2025-09-07T09:51:09.9983720Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:09.9984005Z convolution 0.0099 ms 100.0% 2025-09-07T09:51:09.9984274Z conv1x1_via_mm 0.0121 ms 82.0% 2025-09-07T09:51:09.9985049Z triton_convolution2d_155 0.0370 ms 26.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:09.9986326Z triton_convolution2d_154 0.0407 ms 24.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:09.9987568Z triton_convolution2d_156 0.0480 ms 20.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:09.9988806Z triton_convolution2d_153 0.0536 ms 18.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:51:09.9990198Z triton_convolution2d_152 0.0585 ms 16.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:09.9991993Z triton_convolution2d_151 0.0716 ms 13.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:09.9993150Z SingleProcess AUTOTUNE benchmarking takes 0.3265 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:10.4350889Z Autotune Choices Stats: 2025-09-07T09:51:10.4352358Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.008671999908983707, "best_triton_pos": 1, "best_triton_time": 0.010816000401973724, "best_triton_kernel": "triton_convolution2d_102", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:10.6072983Z AUTOTUNE convolution(4x256x1x1, 512x256x1x1) 2025-09-07T09:51:10.6073308Z strides: [256, 1, 1, 1], [256, 1, 1, 1] 2025-09-07T09:51:10.6073585Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:10.6073861Z convolution 0.0087 ms 100.0% 2025-09-07T09:51:10.6074596Z triton_convolution2d_102 0.0108 ms 80.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:10.6075820Z triton_convolution2d_101 0.0115 ms 75.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:10.6076565Z conv1x1_via_mm 0.0116 ms 74.5% 2025-09-07T09:51:10.6077283Z triton_convolution2d_100 0.0124 ms 69.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:51:10.6078502Z triton_convolution2d_103 0.0127 ms 68.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:10.6079714Z triton_convolution2d_99 0.0134 ms 64.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:10.6081414Z triton_convolution2d_98 0.0163 ms 53.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:10.6082380Z SingleProcess AUTOTUNE benchmarking takes 0.2935 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:11.3027690Z Autotune Choices Stats: 2025-09-07T09:51:11.3028919Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_69", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.007935999892652035, "best_triton_pos": 0} 2025-09-07T09:51:11.5092933Z AUTOTUNE convolution(4x128x1x1, 256x128x1x1) 2025-09-07T09:51:11.5093338Z strides: [128, 1, 1, 1], [128, 1, 1, 1] 2025-09-07T09:51:11.5093639Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:11.5094447Z triton_convolution2d_69 0.0079 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:11.5095716Z triton_convolution2d_67 0.0082 ms 97.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:51:11.5097495Z triton_convolution2d_68 0.0082 ms 96.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:11.5098938Z triton_convolution2d_66 0.0088 ms 90.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:11.5100510Z triton_convolution2d_70 0.0089 ms 88.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:11.5101211Z convolution 0.0091 ms 87.0% 2025-09-07T09:51:11.5101440Z conv1x1_via_mm 0.0099 ms 80.3% 2025-09-07T09:51:11.5102113Z triton_convolution2d_65 0.0109 ms 72.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:11.5103110Z SingleProcess AUTOTUNE benchmarking takes 0.3263 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:11.9882847Z Autotune Choices Stats: 2025-09-07T09:51:11.9884380Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.009535999968647957, "best_triton_pos": 2, "best_triton_time": 0.015519999898970127, "best_triton_kernel": "triton_convolution2d_96", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:12.0428565Z AUTOTUNE convolution(4x512x1x1, 256x512x1x1) 2025-09-07T09:51:12.0428928Z strides: [512, 1, 1, 1], [512, 1, 1, 1] 2025-09-07T09:51:12.0429223Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:12.0429537Z convolution 0.0095 ms 100.0% 2025-09-07T09:51:12.0429841Z conv1x1_via_mm 0.0105 ms 91.1% 2025-09-07T09:51:12.0430973Z triton_convolution2d_96 0.0155 ms 61.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:12.0432229Z triton_convolution2d_95 0.0174 ms 54.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:12.0433455Z triton_convolution2d_94 0.0193 ms 49.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:51:12.0434652Z triton_convolution2d_97 0.0205 ms 46.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:12.0435856Z triton_convolution2d_93 0.0208 ms 45.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:12.0437066Z triton_convolution2d_92 0.0277 ms 34.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:12.0438025Z SingleProcess AUTOTUNE benchmarking takes 0.1779 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:51:12.4135730Z Autotune Choices Stats: 2025-09-07T09:51:12.4138023Z {"num_choices": 7, "num_triton_choices": 5, "best_kernel": "convolution", "best_time": 0.008415999822318554, "best_triton_pos": 2, "best_triton_time": 0.010400000028312206, "best_triton_kernel": "triton_convolution2d_64", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:12.4453323Z AUTOTUNE convolution(4x256x1x1, 128x256x1x1) 2025-09-07T09:51:12.4453860Z strides: [256, 1, 1, 1], [256, 1, 1, 1] 2025-09-07T09:51:12.4454332Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:12.4454783Z convolution 0.0084 ms 100.0% 2025-09-07T09:51:12.4455717Z conv1x1_via_mm 0.0101 ms 83.0% 2025-09-07T09:51:12.4456962Z triton_convolution2d_64 0.0104 ms 80.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:12.4458962Z triton_convolution2d_62 0.0107 ms 79.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:51:12.4461112Z triton_convolution2d_63 0.0109 ms 77.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:12.4462199Z triton_convolution2d_61 0.0122 ms 69.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:12.4463326Z triton_convolution2d_60 0.0135 ms 62.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:12.4464166Z SingleProcess AUTOTUNE benchmarking takes 0.1401 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:51:13.4675349Z Autotune Choices Stats: 2025-09-07T09:51:13.4676782Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010944000445306301, "best_triton_pos": 1, "best_triton_time": 0.024032000452280045, "best_triton_kernel": "triton_convolution2d_148", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:13.5070119Z AUTOTUNE convolution(4x768x12x12, 1536x768x1x1) 2025-09-07T09:51:13.5071049Z strides: [110592, 144, 12, 1], [768, 1, 1, 1] 2025-09-07T09:51:13.5071432Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:13.5071713Z convolution 0.0109 ms 100.0% 2025-09-07T09:51:13.5072444Z triton_convolution2d_148 0.0240 ms 45.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:13.5073687Z triton_convolution2d_147 0.0294 ms 37.2% 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 2025-09-07T09:51:13.5074931Z triton_convolution2d_149 0.0300 ms 36.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:13.5076161Z triton_convolution2d_150 0.0302 ms 36.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:13.5076909Z conv1x1_via_mm 0.0367 ms 29.8% 2025-09-07T09:51:13.5077633Z triton_convolution2d_144 0.0420 ms 26.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:13.5078847Z triton_convolution2d_145 0.0450 ms 24.3% 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 2025-09-07T09:51:13.5080737Z triton_convolution2d_146 0.0530 ms 20.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:51:13.5081982Z SingleProcess AUTOTUNE benchmarking takes 0.1760 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:13.6591711Z Autotune Choices Stats: 2025-09-07T09:51:13.6593067Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014783999882638454, "best_triton_pos": 1, "best_triton_time": 0.02454400062561035, "best_triton_kernel": "triton_convolution2d_311", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:13.8324527Z AUTOTUNE convolution(4x768x6x6, 1536x768x1x1) 2025-09-07T09:51:13.8324859Z strides: [27648, 36, 6, 1], [768, 1, 1, 1] 2025-09-07T09:51:13.8325158Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:13.8325441Z convolution 0.0148 ms 100.0% 2025-09-07T09:51:13.8326229Z triton_convolution2d_311 0.0245 ms 60.2% 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 2025-09-07T09:51:13.8326999Z conv1x1_via_mm 0.0297 ms 49.7% 2025-09-07T09:51:13.8327759Z triton_convolution2d_310 0.0311 ms 47.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:13.8329021Z triton_convolution2d_312 0.0311 ms 47.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:13.8330480Z triton_convolution2d_313 0.0320 ms 46.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:13.8331659Z triton_convolution2d_309 0.0358 ms 41.3% 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 2025-09-07T09:51:13.8332790Z triton_convolution2d_308 0.0379 ms 39.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:13.8333915Z triton_convolution2d_307 0.0420 ms 35.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:13.8334812Z SingleProcess AUTOTUNE benchmarking takes 0.3052 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:13.9993610Z Autotune Choices Stats: 2025-09-07T09:51:13.9994962Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02412799932062626, "best_triton_pos": 1, "best_triton_time": 0.044863998889923096, "best_triton_kernel": "triton_convolution2d_382", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:51:14.1678993Z AUTOTUNE convolution(4x1536x6x6, 3072x1536x1x1) 2025-09-07T09:51:14.1679307Z strides: [55296, 36, 6, 1], [1536, 1, 1, 1] 2025-09-07T09:51:14.1679588Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:14.1679847Z convolution 0.0241 ms 100.0% 2025-09-07T09:51:14.1681182Z triton_convolution2d_382 0.0449 ms 53.8% 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 2025-09-07T09:51:14.1682897Z conv1x1_via_mm 0.0515 ms 46.9% 2025-09-07T09:51:14.1684362Z triton_convolution2d_381 0.0549 ms 43.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:14.1686402Z triton_convolution2d_384 0.0564 ms 42.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:14.1688374Z triton_convolution2d_383 0.0566 ms 42.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:51:14.1690587Z triton_convolution2d_380 0.0676 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 2025-09-07T09:51:14.1692121Z triton_convolution2d_379 0.0739 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 2025-09-07T09:51:14.1693270Z triton_convolution2d_378 0.0797 ms 30.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:51:14.1694175Z SingleProcess AUTOTUNE benchmarking takes 0.3253 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:51:14.4374881Z Autotune Choices Stats: 2025-09-07T09:51:14.4376894Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "bias_addmm", "best_time": 0.014720000326633453, "best_triton_pos": 1, "best_triton_time": 0.01500799972563982, "best_triton_kernel": "triton_mm_389", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T09:51:14.4527803Z AUTOTUNE addmm(4x1000, 4x3072, 3072x1000) 2025-09-07T09:51:14.4528303Z strides: [0, 1], [3072, 1], [1, 3072] 2025-09-07T09:51:14.4528806Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:51:14.4529324Z bias_addmm 0.0147 ms 100.0% 2025-09-07T09:51:14.4530825Z triton_mm_389 0.0150 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:51:14.4532002Z triton_mm_393 0.0160 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:51:14.4532903Z triton_mm_397 0.0173 ms 85.0% 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 2025-09-07T09:51:14.4533806Z triton_mm_401 0.0206 ms 71.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:51:14.4534371Z addmm 0.0209 ms 70.3% 2025-09-07T09:51:14.4534901Z triton_mm_388 0.0236 ms 62.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:51:14.4535795Z triton_mm_386 0.0249 ms 59.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:51:14.4536678Z triton_mm_387 0.0251 ms 58.6% 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 2025-09-07T09:51:14.4537839Z triton_mm_392 0.0256 ms 57.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:51:14.4538609Z SingleProcess AUTOTUNE benchmarking takes 0.2836 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:51:30.2204668Z Autotune Choices Stats: 2025-09-07T09:51:30.2206559Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_424", "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": 0.007840000092983246, "best_triton_pos": 0} 2025-09-07T09:51:30.3281417Z AUTOTUNE mm(1000x4, 4x3072) 2025-09-07T09:51:30.3281709Z strides: [1, 1000], [3072, 1] 2025-09-07T09:51:30.3282013Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:30.3282810Z triton_mm_424 0.0078 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 2025-09-07T09:51:30.3283997Z triton_mm_426 0.0079 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:51:30.3285153Z triton_mm_428 0.0080 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:51:30.3286301Z triton_mm_431 0.0080 ms 97.6% 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 2025-09-07T09:51:30.3287476Z triton_mm_429 0.0082 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:51:30.3288622Z triton_mm_425 0.0082 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:51:30.3289773Z triton_mm_432 0.0082 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:51:30.3291286Z triton_mm_434 0.0082 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:51:30.3292453Z triton_mm_427 0.0083 ms 95.0% 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 2025-09-07T09:51:30.3293605Z triton_mm_433 0.0084 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:51:30.3294615Z SingleProcess AUTOTUNE benchmarking takes 0.2774 seconds and 0.0004 seconds precompiling for 17 choices 2025-09-07T09:51:31.0050113Z Autotune Choices Stats: 2025-09-07T09:51:31.0052207Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.01033599954098463, "best_triton_pos": 1, "best_triton_time": 0.011008000001311302, "best_triton_kernel": "triton_mm_414", "best_triton_kernel_desc": "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"} 2025-09-07T09:51:31.1216430Z AUTOTUNE mm(4x1000, 1000x3072) 2025-09-07T09:51:31.1216703Z strides: [1000, 1], [3072, 1] 2025-09-07T09:51:31.1216962Z dtypes: torch.float16, torch.float16 2025-09-07T09:51:31.1217237Z mm 0.0103 ms 100.0% 2025-09-07T09:51:31.1217866Z triton_mm_414 0.0110 ms 93.9% 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 2025-09-07T09:51:31.1219463Z triton_mm_410 0.0114 ms 91.0% 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 2025-09-07T09:51:31.1221127Z triton_mm_418 0.0121 ms 85.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:51:31.1222129Z triton_mm_404 0.0127 ms 81.6% 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 2025-09-07T09:51:31.1223176Z triton_mm_409 0.0132 ms 78.2% 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 2025-09-07T09:51:31.1224146Z triton_mm_406 0.0133 ms 77.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:51:31.1225110Z triton_mm_416 0.0139 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:51:31.1226197Z triton_mm_413 0.0140 ms 74.1% 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 2025-09-07T09:51:31.1227165Z triton_mm_412 0.0144 ms 71.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:51:31.1228008Z SingleProcess AUTOTUNE benchmarking takes 0.3031 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:51:39.0151542Z E0907 09:51:39.014000 83116 site-packages/torch/_dynamo/utils.py:3115] RMSE (res-fp64): 0.00152, (ref-fp64): 0.00034 and shape=torch.Size([]). res.dtype: torch.float32, multiplier: 3.000000, tol: 0.001000, use_larger_multiplier_for_smaller_tensor: 0 2025-09-07T09:51:39.0153279Z E0907 09:51:39.014000 83116 site-packages/torch/_dynamo/utils.py:2976] Accuracy failed for key name stages.0.0.skipinit_gain.grad 2025-09-07T09:51:39.0920172Z fail_accuracy 2025-09-07T09:51:43.8039858Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:51:43.8042538Z import pynvml # type: ignore[import] 2025-09-07T09:51:46.2973384Z 2025-09-07T09:51:49.6769665Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:51:49.6770058Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:51:49.6770771Z cuda train timm_regnet 2025-09-07T09:52:10.7420843Z Autotune Choices Stats: 2025-09-07T09:52:10.7422132Z {"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": 0.014879999682307243, "best_triton_pos": 0} 2025-09-07T09:52:10.7573650Z AUTOTUNE convolution(4x32x112x112, 224x32x1x1) 2025-09-07T09:52:10.7574017Z strides: [401408, 12544, 112, 1], [32, 1, 1, 1] 2025-09-07T09:52:10.7574302Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:10.7575015Z triton_convolution2d_10 0.0149 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 2025-09-07T09:52:10.7576164Z triton_convolution2d_12 0.0167 ms 89.3% 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 2025-09-07T09:52:10.7577474Z convolution 0.0172 ms 86.4% 2025-09-07T09:52:10.7578164Z triton_convolution2d_11 0.0172 ms 86.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:10.7579621Z triton_convolution2d_9 0.0173 ms 86.1% 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 2025-09-07T09:52:10.7580976Z triton_convolution2d_7 0.0176 ms 84.7% 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 2025-09-07T09:52:10.7582114Z triton_convolution2d_6 0.0193 ms 77.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:10.7583327Z triton_convolution2d_8 0.0213 ms 69.9% 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 2025-09-07T09:52:10.7584016Z conv1x1_via_mm 0.1228 ms 12.1% 2025-09-07T09:52:10.7584460Z SingleProcess AUTOTUNE benchmarking takes 0.1536 seconds and 0.0003 seconds precompiling for 9 choices 2025-09-07T09:52:11.2048989Z Autotune Choices Stats: 2025-09-07T09:52:11.2050855Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01532800029963255, "best_triton_pos": 1, "best_triton_time": 0.020640000700950623, "best_triton_kernel": "triton_convolution2d_62", "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"} 2025-09-07T09:52:11.2641202Z AUTOTUNE convolution(4x224x56x56, 448x224x1x1) 2025-09-07T09:52:11.2641570Z strides: [702464, 3136, 56, 1], [224, 1, 1, 1] 2025-09-07T09:52:11.2641887Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:11.2642193Z convolution 0.0153 ms 100.0% 2025-09-07T09:52:11.2643020Z triton_convolution2d_62 0.0206 ms 74.3% 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 2025-09-07T09:52:11.2644388Z triton_convolution2d_59 0.0220 ms 69.5% 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 2025-09-07T09:52:11.2645734Z triton_convolution2d_61 0.0232 ms 66.2% 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 2025-09-07T09:52:11.2647113Z triton_convolution2d_64 0.0248 ms 61.7% 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 2025-09-07T09:52:11.2648257Z triton_convolution2d_58 0.0249 ms 61.5% 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 2025-09-07T09:52:11.2649384Z triton_convolution2d_63 0.0266 ms 57.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:11.2650696Z triton_convolution2d_60 0.0413 ms 37.1% 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 2025-09-07T09:52:11.2651763Z conv1x1_via_mm 0.0904 ms 16.9% 2025-09-07T09:52:11.2652227Z SingleProcess AUTOTUNE benchmarking takes 0.1975 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:52:11.6421490Z Autotune Choices Stats: 2025-09-07T09:52:11.6423157Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_32", "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": 0.009088000282645226, "best_triton_pos": 0} 2025-09-07T09:52:11.6790031Z AUTOTUNE convolution(4x32x112x112, 224x32x1x1) 2025-09-07T09:52:11.6790553Z strides: [401408, 12544, 112, 1], [32, 1, 1, 1] 2025-09-07T09:52:11.6790849Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:11.6791620Z triton_convolution2d_32 0.0091 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 2025-09-07T09:52:11.6792918Z triton_convolution2d_33 0.0094 ms 96.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:11.6794166Z triton_convolution2d_31 0.0095 ms 95.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:11.6795392Z triton_convolution2d_34 0.0100 ms 91.0% 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 2025-09-07T09:52:11.6796603Z triton_convolution2d_29 0.0105 ms 86.3% 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 2025-09-07T09:52:11.6797832Z triton_convolution2d_28 0.0109 ms 83.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:11.6799056Z triton_convolution2d_30 0.0224 ms 40.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:52:11.6799811Z convolution 0.0271 ms 33.5% 2025-09-07T09:52:11.6800420Z SingleProcess AUTOTUNE benchmarking takes 0.1381 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:12.1820719Z Autotune Choices Stats: 2025-09-07T09:52:12.1822136Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011455999687314034, "best_triton_pos": 1, "best_triton_time": 0.014399999752640724, "best_triton_kernel": "triton_convolution2d_39", "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"} 2025-09-07T09:52:12.1966906Z AUTOTUNE convolution(4x224x56x56, 224x224x1x1) 2025-09-07T09:52:12.1967262Z strides: [702464, 3136, 56, 1], [224, 1, 1, 1] 2025-09-07T09:52:12.1967602Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:12.1967894Z convolution 0.0115 ms 100.0% 2025-09-07T09:52:12.1968653Z triton_convolution2d_39 0.0144 ms 79.6% 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 2025-09-07T09:52:12.1969907Z triton_convolution2d_38 0.0162 ms 70.8% 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 2025-09-07T09:52:12.1971302Z triton_convolution2d_41 0.0167 ms 68.6% 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 2025-09-07T09:52:12.1972931Z triton_convolution2d_35 0.0178 ms 64.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:12.1974348Z triton_convolution2d_36 0.0204 ms 56.3% 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 2025-09-07T09:52:12.1975574Z triton_convolution2d_40 0.0217 ms 52.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:12.1976810Z triton_convolution2d_37 0.0240 ms 47.7% 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 2025-09-07T09:52:12.1977682Z conv1x1_via_mm 0.0654 ms 17.5% 2025-09-07T09:52:12.1978150Z SingleProcess AUTOTUNE benchmarking takes 0.1499 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:52:12.8707757Z Autotune Choices Stats: 2025-09-07T09:52:12.8709349Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.012543999589979649, "best_triton_pos": 1, "best_triton_time": 0.019680000841617584, "best_triton_kernel": "triton_convolution2d_192", "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"} 2025-09-07T09:52:12.9046647Z AUTOTUNE convolution(4x448x28x28, 896x448x1x1) 2025-09-07T09:52:12.9047014Z strides: [351232, 784, 28, 1], [448, 1, 1, 1] 2025-09-07T09:52:12.9047353Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:12.9047645Z convolution 0.0125 ms 100.0% 2025-09-07T09:52:12.9048422Z triton_convolution2d_192 0.0197 ms 63.7% 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 2025-09-07T09:52:12.9049708Z triton_convolution2d_191 0.0219 ms 57.2% 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 2025-09-07T09:52:12.9051104Z triton_convolution2d_193 0.0222 ms 56.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:12.9052339Z triton_convolution2d_194 0.0229 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 2025-09-07T09:52:12.9053560Z triton_convolution2d_188 0.0278 ms 45.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:12.9054778Z triton_convolution2d_189 0.0308 ms 40.7% 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 2025-09-07T09:52:12.9056008Z triton_convolution2d_190 0.0421 ms 29.8% 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 2025-09-07T09:52:12.9056753Z conv1x1_via_mm 0.0595 ms 21.1% 2025-09-07T09:52:12.9057255Z SingleProcess AUTOTUNE benchmarking takes 0.1739 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:52:13.3738268Z Autotune Choices Stats: 2025-09-07T09:52:13.3739466Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_484", "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": 0.03049599938094616, "best_triton_pos": 0} 2025-09-07T09:52:13.4266854Z AUTOTUNE convolution(4x896x14x14, 2240x896x1x1) 2025-09-07T09:52:13.4267254Z strides: [175616, 196, 14, 1], [896, 1, 1, 1] 2025-09-07T09:52:13.4267601Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:13.4268300Z triton_convolution2d_484 0.0305 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:13.4269375Z triton_convolution2d_483 0.0350 ms 87.0% 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 2025-09-07T09:52:13.4270631Z triton_convolution2d_485 0.0357 ms 85.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:13.4271700Z triton_convolution2d_486 0.0401 ms 76.1% 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 2025-09-07T09:52:13.4272751Z triton_convolution2d_481 0.0468 ms 65.1% 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 2025-09-07T09:52:13.4273828Z triton_convolution2d_480 0.0492 ms 62.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:13.4274483Z conv1x1_via_mm 0.0612 ms 49.9% 2025-09-07T09:52:13.4275120Z triton_convolution2d_482 0.0787 ms 38.8% 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 2025-09-07T09:52:13.4275779Z convolution 0.0828 ms 36.8% 2025-09-07T09:52:13.4276190Z SingleProcess AUTOTUNE benchmarking takes 0.2024 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:52:13.7992158Z Autotune Choices Stats: 2025-09-07T09:52:13.7993275Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_3", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.01027199998497963, "best_triton_pos": 0} 2025-09-07T09:52:13.8432649Z AUTOTUNE convolution(4x3x224x224, 32x3x3x3) 2025-09-07T09:52:13.8432958Z strides: [150528, 50176, 224, 1], [27, 9, 3, 1] 2025-09-07T09:52:13.8433257Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:13.8434036Z triton_convolution2d_3 0.0103 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:52:13.8435300Z triton_convolution2d_5 0.0107 ms 95.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:52:13.8436511Z triton_convolution2d_0 0.0108 ms 95.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:52:13.8438021Z triton_convolution2d_1 0.0114 ms 90.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:52:13.8439243Z triton_convolution2d_4 0.0119 ms 86.5% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:52:13.8440962Z triton_convolution2d_2 0.0167 ms 61.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:52:13.8441727Z convolution 0.0177 ms 58.0% 2025-09-07T09:52:13.8442192Z SingleProcess AUTOTUNE benchmarking takes 0.1322 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:52:14.3549784Z Autotune Choices Stats: 2025-09-07T09:52:14.3551094Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_85", "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": 0.01369599997997284, "best_triton_pos": 0} 2025-09-07T09:52:14.3663338Z AUTOTUNE convolution(4x224x56x56, 448x224x1x1) 2025-09-07T09:52:14.3663661Z strides: [702464, 3136, 56, 1], [224, 1, 1, 1] 2025-09-07T09:52:14.3663959Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:14.3664673Z triton_convolution2d_85 0.0137 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 2025-09-07T09:52:14.3665828Z triton_convolution2d_86 0.0152 ms 89.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:14.3666969Z triton_convolution2d_87 0.0198 ms 69.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:14.3668138Z triton_convolution2d_81 0.0201 ms 68.3% 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 2025-09-07T09:52:14.3669349Z triton_convolution2d_82 0.0208 ms 65.7% 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 2025-09-07T09:52:14.3670092Z convolution 0.0254 ms 54.0% 2025-09-07T09:52:14.3671202Z triton_convolution2d_83 0.0430 ms 31.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:52:14.3672454Z triton_convolution2d_84 0.0462 ms 29.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:14.3673421Z SingleProcess AUTOTUNE benchmarking takes 0.1117 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:14.8675943Z Autotune Choices Stats: 2025-09-07T09:52:14.8677354Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010751999914646149, "best_triton_pos": 1, "best_triton_time": 0.017632000148296356, "best_triton_kernel": "triton_convolution2d_92", "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"} 2025-09-07T09:52:14.8887154Z AUTOTUNE convolution(4x448x28x28, 448x448x1x1) 2025-09-07T09:52:14.8887854Z strides: [351232, 784, 28, 1], [448, 1, 1, 1] 2025-09-07T09:52:14.8888182Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:14.8888469Z convolution 0.0108 ms 100.0% 2025-09-07T09:52:14.8889216Z triton_convolution2d_92 0.0176 ms 61.0% 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 2025-09-07T09:52:14.8891143Z triton_convolution2d_91 0.0204 ms 52.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:14.8892407Z triton_convolution2d_94 0.0210 ms 51.1% 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 2025-09-07T09:52:14.8893634Z triton_convolution2d_93 0.0211 ms 51.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:14.8894858Z triton_convolution2d_88 0.0276 ms 38.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:14.8896086Z triton_convolution2d_89 0.0298 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 2025-09-07T09:52:14.8897295Z triton_convolution2d_90 0.0347 ms 31.0% 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 2025-09-07T09:52:14.8898112Z conv1x1_via_mm 0.0450 ms 23.9% 2025-09-07T09:52:14.8898554Z SingleProcess AUTOTUNE benchmarking takes 0.1562 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:52:15.6702644Z Autotune Choices Stats: 2025-09-07T09:52:15.6703956Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_217", "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": 0.018624000251293182, "best_triton_pos": 0} 2025-09-07T09:52:15.7085042Z AUTOTUNE convolution(4x448x28x28, 896x448x1x1) 2025-09-07T09:52:15.7085438Z strides: [351232, 784, 28, 1], [448, 1, 1, 1] 2025-09-07T09:52:15.7085765Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:15.7086704Z triton_convolution2d_217 0.0186 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 2025-09-07T09:52:15.7088197Z triton_convolution2d_218 0.0219 ms 85.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:15.7088967Z convolution 0.0220 ms 84.6% 2025-09-07T09:52:15.7089719Z triton_convolution2d_216 0.0229 ms 81.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:15.7091370Z triton_convolution2d_213 0.0306 ms 60.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:15.7092608Z triton_convolution2d_219 0.0310 ms 60.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:15.7094269Z triton_convolution2d_214 0.0338 ms 55.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:15.7095511Z triton_convolution2d_215 0.0568 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=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:52:15.7096704Z SingleProcess AUTOTUNE benchmarking takes 0.1399 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:16.2454913Z Autotune Choices Stats: 2025-09-07T09:52:16.2456341Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.0226879995316267, "best_triton_pos": 1, "best_triton_time": 0.02848000079393387, "best_triton_kernel": "triton_convolution2d_224", "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"} 2025-09-07T09:52:16.2870528Z AUTOTUNE convolution(4x896x14x14, 896x896x1x1) 2025-09-07T09:52:16.2870893Z strides: [175616, 196, 14, 1], [896, 1, 1, 1] 2025-09-07T09:52:16.2871180Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:16.2871457Z convolution 0.0227 ms 100.0% 2025-09-07T09:52:16.2872209Z triton_convolution2d_224 0.0285 ms 79.7% 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 2025-09-07T09:52:16.2873448Z triton_convolution2d_223 0.0336 ms 67.5% 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 2025-09-07T09:52:16.2874699Z triton_convolution2d_225 0.0336 ms 67.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:16.2875963Z triton_convolution2d_226 0.0351 ms 64.6% 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 2025-09-07T09:52:16.2876714Z conv1x1_via_mm 0.0365 ms 62.1% 2025-09-07T09:52:16.2877450Z triton_convolution2d_221 0.0441 ms 51.5% 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 2025-09-07T09:52:16.2878691Z triton_convolution2d_220 0.0464 ms 48.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:16.2879919Z triton_convolution2d_222 0.0686 ms 33.1% 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 2025-09-07T09:52:16.2881021Z SingleProcess AUTOTUNE benchmarking takes 0.1848 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:52:17.3737789Z Autotune Choices Stats: 2025-09-07T09:52:17.3739261Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.008832000195980072, "best_triton_pos": 1, "best_triton_time": 0.010463999584317207, "best_triton_kernel": "triton_convolution2d_497", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:17.3994496Z AUTOTUNE convolution(4x224x1x1, 2240x224x1x1) 2025-09-07T09:52:17.3994808Z strides: [224, 1, 1, 1], [224, 1, 1, 1] 2025-09-07T09:52:17.3995078Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:17.3995786Z convolution 0.0088 ms 100.0% 2025-09-07T09:52:17.3996525Z triton_convolution2d_497 0.0105 ms 84.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:17.3997275Z conv1x1_via_mm 0.0106 ms 83.1% 2025-09-07T09:52:17.3998204Z triton_convolution2d_496 0.0110 ms 80.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:17.3999398Z triton_convolution2d_495 0.0118 ms 74.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:17.4000680Z triton_convolution2d_498 0.0120 ms 73.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:17.4001803Z triton_convolution2d_494 0.0125 ms 70.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:17.4002921Z triton_convolution2d_493 0.0150 ms 58.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:17.4003816Z SingleProcess AUTOTUNE benchmarking takes 0.1460 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:17.7821202Z Autotune Choices Stats: 2025-09-07T09:52:17.7822331Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_204", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.008031999692320824, "best_triton_pos": 0} 2025-09-07T09:52:17.8287529Z AUTOTUNE convolution(4x112x1x1, 896x112x1x1) 2025-09-07T09:52:17.8287878Z strides: [112, 1, 1, 1], [112, 1, 1, 1] 2025-09-07T09:52:17.8288176Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:17.8289026Z triton_convolution2d_204 0.0080 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:17.8289821Z convolution 0.0083 ms 97.3% 2025-09-07T09:52:17.8290741Z triton_convolution2d_203 0.0084 ms 96.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:17.8291987Z triton_convolution2d_205 0.0088 ms 91.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:17.8293220Z triton_convolution2d_202 0.0092 ms 87.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:17.8294452Z triton_convolution2d_201 0.0095 ms 84.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:17.8295194Z conv1x1_via_mm 0.0102 ms 78.7% 2025-09-07T09:52:17.8295932Z triton_convolution2d_200 0.0109 ms 73.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:17.8296918Z SingleProcess AUTOTUNE benchmarking takes 0.1678 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:18.2112231Z Autotune Choices Stats: 2025-09-07T09:52:18.2113869Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.008576000109314919, "best_triton_pos": 2, "best_triton_time": 0.01027199998497963, "best_triton_kernel": "triton_convolution2d_237", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:18.2367278Z AUTOTUNE convolution(4x224x1x1, 896x224x1x1) 2025-09-07T09:52:18.2367625Z strides: [224, 1, 1, 1], [224, 1, 1, 1] 2025-09-07T09:52:18.2367916Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:18.2368222Z convolution 0.0086 ms 100.0% 2025-09-07T09:52:18.2368484Z conv1x1_via_mm 0.0102 ms 84.0% 2025-09-07T09:52:18.2369278Z triton_convolution2d_237 0.0103 ms 83.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:18.2370882Z triton_convolution2d_236 0.0108 ms 79.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:18.2372106Z triton_convolution2d_238 0.0116 ms 73.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:18.2373317Z triton_convolution2d_235 0.0119 ms 72.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:18.2374520Z triton_convolution2d_234 0.0124 ms 69.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:18.2375725Z triton_convolution2d_233 0.0155 ms 55.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:18.2376693Z SingleProcess AUTOTUNE benchmarking takes 0.1463 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:18.9964842Z Autotune Choices Stats: 2025-09-07T09:52:18.9966039Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_72", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.0063680000603199005, "best_triton_pos": 0} 2025-09-07T09:52:19.0056013Z AUTOTUNE convolution(4x56x1x1, 448x56x1x1) 2025-09-07T09:52:19.0056321Z strides: [56, 1, 1, 1], [56, 1, 1, 1] 2025-09-07T09:52:19.0056610Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:19.0057406Z triton_convolution2d_72 0.0064 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:19.0058675Z triton_convolution2d_70 0.0065 ms 98.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:19.0059903Z triton_convolution2d_71 0.0065 ms 98.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:19.0061305Z triton_convolution2d_73 0.0069 ms 92.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:19.0062878Z triton_convolution2d_69 0.0070 ms 90.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:19.0063644Z convolution 0.0075 ms 84.7% 2025-09-07T09:52:19.0064595Z triton_convolution2d_68 0.0081 ms 79.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:19.0065347Z conv1x1_via_mm 0.0106 ms 60.3% 2025-09-07T09:52:19.0065833Z SingleProcess AUTOTUNE benchmarking takes 0.1291 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:19.3841423Z Autotune Choices Stats: 2025-09-07T09:52:19.3842637Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_104", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.007648000027984381, "best_triton_pos": 0} 2025-09-07T09:52:19.3891044Z AUTOTUNE convolution(4x112x1x1, 448x112x1x1) 2025-09-07T09:52:19.3891372Z strides: [112, 1, 1, 1], [112, 1, 1, 1] 2025-09-07T09:52:19.3891673Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:19.3892449Z triton_convolution2d_104 0.0076 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:19.3893211Z convolution 0.0081 ms 94.1% 2025-09-07T09:52:19.3893941Z triton_convolution2d_103 0.0081 ms 94.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:19.3895161Z triton_convolution2d_102 0.0087 ms 88.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:19.3896380Z triton_convolution2d_105 0.0087 ms 88.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:19.3897597Z triton_convolution2d_101 0.0090 ms 84.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:19.3898350Z conv1x1_via_mm 0.0096 ms 79.4% 2025-09-07T09:52:19.3899111Z triton_convolution2d_100 0.0103 ms 74.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:19.3900065Z SingleProcess AUTOTUNE benchmarking takes 0.1250 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:19.6456175Z Autotune Choices Stats: 2025-09-07T09:52:19.6457281Z {"num_choices": 7, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_20", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8", "best_time": 0.0055680000223219395, "best_triton_pos": 0} 2025-09-07T09:52:19.6727815Z AUTOTUNE convolution(4x8x1x1, 224x8x1x1) 2025-09-07T09:52:19.6728133Z strides: [8, 1, 1, 1], [8, 1, 1, 1] 2025-09-07T09:52:19.6728430Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:19.6729269Z triton_convolution2d_20 0.0056 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:19.6730829Z triton_convolution2d_17 0.0057 ms 98.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:19.6732290Z triton_convolution2d_18 0.0057 ms 98.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:19.6733575Z triton_convolution2d_19 0.0057 ms 97.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:19.6734703Z triton_convolution2d_16 0.0063 ms 88.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:19.6735402Z convolution 0.0074 ms 75.7% 2025-09-07T09:52:19.6735638Z conv1x1_via_mm 0.0092 ms 60.4% 2025-09-07T09:52:19.6736077Z SingleProcess AUTOTUNE benchmarking takes 0.1341 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:52:20.0465436Z Autotune Choices Stats: 2025-09-07T09:52:20.0466557Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_49", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.006271999794989824, "best_triton_pos": 0} 2025-09-07T09:52:20.1044268Z AUTOTUNE convolution(4x56x1x1, 224x56x1x1) 2025-09-07T09:52:20.1044625Z strides: [56, 1, 1, 1], [56, 1, 1, 1] 2025-09-07T09:52:20.1044943Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:20.1045823Z triton_convolution2d_49 0.0063 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:20.1047245Z triton_convolution2d_47 0.0064 ms 97.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:20.1048643Z triton_convolution2d_48 0.0064 ms 97.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:20.1050013Z triton_convolution2d_50 0.0069 ms 91.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:20.1051518Z triton_convolution2d_46 0.0069 ms 90.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:20.1052262Z convolution 0.0075 ms 83.8% 2025-09-07T09:52:20.1052972Z triton_convolution2d_45 0.0079 ms 79.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:20.1053712Z conv1x1_via_mm 0.0094 ms 66.9% 2025-09-07T09:52:20.1054178Z SingleProcess AUTOTUNE benchmarking takes 0.1764 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:20.3331430Z Autotune Choices Stats: 2025-09-07T09:52:20.3332819Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "conv1x1_via_mm", "best_time": 0.010591999627649784, "best_triton_pos": 2, "best_triton_time": 0.022975999861955643, "best_triton_kernel": "triton_convolution2d_231", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:20.3875481Z AUTOTUNE convolution(4x896x1x1, 224x896x1x1) 2025-09-07T09:52:20.3875779Z strides: [896, 1, 1, 1], [896, 1, 1, 1] 2025-09-07T09:52:20.3876055Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:20.3876328Z conv1x1_via_mm 0.0106 ms 100.0% 2025-09-07T09:52:20.3876587Z convolution 0.0108 ms 97.6% 2025-09-07T09:52:20.3877494Z triton_convolution2d_231 0.0230 ms 46.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:20.3878758Z triton_convolution2d_230 0.0256 ms 41.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:20.3880031Z triton_convolution2d_232 0.0291 ms 36.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:20.3881401Z triton_convolution2d_229 0.0316 ms 33.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:20.3882564Z triton_convolution2d_228 0.0326 ms 32.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:20.3883714Z triton_convolution2d_227 0.0406 ms 26.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:20.3884613Z SingleProcess AUTOTUNE benchmarking takes 0.1749 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:20.8449347Z Autotune Choices Stats: 2025-09-07T09:52:20.8451234Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.010400000028312206, "best_triton_pos": 2, "best_triton_time": 0.050335999578237534, "best_triton_kernel": "triton_convolution2d_491", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:20.8907728Z AUTOTUNE convolution(4x2240x1x1, 224x2240x1x1) 2025-09-07T09:52:20.8908097Z strides: [2240, 1, 1, 1], [2240, 1, 1, 1] 2025-09-07T09:52:20.8908401Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:20.8908684Z convolution 0.0104 ms 100.0% 2025-09-07T09:52:20.8918245Z conv1x1_via_mm 0.0129 ms 80.8% 2025-09-07T09:52:20.8919121Z triton_convolution2d_491 0.0503 ms 20.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:20.8920649Z triton_convolution2d_490 0.0582 ms 17.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:20.8921898Z triton_convolution2d_492 0.0668 ms 15.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:52:20.8923123Z triton_convolution2d_489 0.0723 ms 14.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:20.8924354Z triton_convolution2d_488 0.0827 ms 12.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:20.8925561Z triton_convolution2d_487 0.0950 ms 11.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:52:20.8926742Z SingleProcess AUTOTUNE benchmarking takes 0.1914 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:21.0032130Z Autotune Choices Stats: 2025-09-07T09:52:21.0033706Z {"num_choices": 7, "num_triton_choices": 5, "best_kernel": "convolution", "best_time": 0.008895999751985073, "best_triton_pos": 2, "best_triton_time": 0.01408000010997057, "best_triton_kernel": "triton_convolution2d_99", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:21.0673653Z AUTOTUNE convolution(4x448x1x1, 112x448x1x1) 2025-09-07T09:52:21.0673943Z strides: [448, 1, 1, 1], [448, 1, 1, 1] 2025-09-07T09:52:21.0674215Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:21.0674488Z convolution 0.0089 ms 100.0% 2025-09-07T09:52:21.0674731Z conv1x1_via_mm 0.0113 ms 78.8% 2025-09-07T09:52:21.0675461Z triton_convolution2d_99 0.0141 ms 63.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:21.0676681Z triton_convolution2d_98 0.0149 ms 59.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:21.0677888Z triton_convolution2d_97 0.0170 ms 52.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:21.0679078Z triton_convolution2d_96 0.0171 ms 52.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:21.0680578Z triton_convolution2d_95 0.0189 ms 47.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:21.0681504Z SingleProcess AUTOTUNE benchmarking takes 0.1705 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:52:21.6128848Z Autotune Choices Stats: 2025-09-07T09:52:21.6130601Z {"num_choices": 7, "num_triton_choices": 5, "best_kernel": "conv1x1_via_mm", "best_time": 0.010495999827980995, "best_triton_pos": 2, "best_triton_time": 0.02300800010561943, "best_triton_kernel": "triton_convolution2d_199", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:21.6635173Z AUTOTUNE convolution(4x896x1x1, 112x896x1x1) 2025-09-07T09:52:21.6635484Z strides: [896, 1, 1, 1], [896, 1, 1, 1] 2025-09-07T09:52:21.6635763Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:21.6636035Z conv1x1_via_mm 0.0105 ms 100.0% 2025-09-07T09:52:21.6636302Z convolution 0.0106 ms 98.8% 2025-09-07T09:52:21.6637047Z triton_convolution2d_199 0.0230 ms 45.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:21.6638270Z triton_convolution2d_198 0.0245 ms 42.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:21.6639489Z triton_convolution2d_196 0.0286 ms 36.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:21.6641025Z triton_convolution2d_197 0.0294 ms 35.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:21.6642329Z triton_convolution2d_195 0.0336 ms 31.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:21.6643244Z SingleProcess AUTOTUNE benchmarking takes 0.1614 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:52:21.7547444Z Autotune Choices Stats: 2025-09-07T09:52:21.7548800Z {"num_choices": 5, "num_triton_choices": 3, "best_kernel": "convolution", "best_time": 0.008287999778985977, "best_triton_pos": 1, "best_triton_time": 0.009344000369310379, "best_triton_kernel": "triton_convolution2d_44", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:22.0186049Z AUTOTUNE convolution(4x224x1x1, 56x224x1x1) 2025-09-07T09:52:22.0186379Z strides: [224, 1, 1, 1], [224, 1, 1, 1] 2025-09-07T09:52:22.0186675Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:22.0186961Z convolution 0.0083 ms 100.0% 2025-09-07T09:52:22.0187752Z triton_convolution2d_44 0.0093 ms 88.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:22.0188553Z conv1x1_via_mm 0.0094 ms 88.4% 2025-09-07T09:52:22.0189322Z triton_convolution2d_43 0.0098 ms 84.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:22.0191136Z triton_convolution2d_42 0.0106 ms 78.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:22.0192180Z SingleProcess AUTOTUNE benchmarking takes 0.3489 seconds and 0.0002 seconds precompiling for 5 choices 2025-09-07T09:52:22.3740092Z Autotune Choices Stats: 2025-09-07T09:52:22.3741654Z {"num_choices": 5, "num_triton_choices": 3, "best_kernel": "convolution", "best_time": 0.008927999995648861, "best_triton_pos": 2, "best_triton_time": 0.013791999779641628, "best_triton_kernel": "triton_convolution2d_67", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:52:22.3785440Z AUTOTUNE convolution(4x448x1x1, 56x448x1x1) 2025-09-07T09:52:22.3785773Z strides: [448, 1, 1, 1], [448, 1, 1, 1] 2025-09-07T09:52:22.3786073Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:22.3786357Z convolution 0.0089 ms 100.0% 2025-09-07T09:52:22.3786605Z conv1x1_via_mm 0.0100 ms 89.1% 2025-09-07T09:52:22.3787354Z triton_convolution2d_67 0.0138 ms 64.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:22.3788575Z triton_convolution2d_66 0.0158 ms 56.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:22.3789811Z triton_convolution2d_65 0.0167 ms 53.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:22.3791008Z SingleProcess AUTOTUNE benchmarking takes 0.0922 seconds and 0.0002 seconds precompiling for 5 choices 2025-09-07T09:52:22.4702235Z Autotune Choices Stats: 2025-09-07T09:52:22.4703966Z {"num_choices": 5, "num_triton_choices": 3, "best_kernel": "convolution", "best_time": 0.007935999892652035, "best_triton_pos": 1, "best_triton_time": 0.00863999966531992, "best_triton_kernel": "triton_convolution2d_15", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=1"} 2025-09-07T09:52:22.5219043Z AUTOTUNE convolution(4x224x1x1, 8x224x1x1) 2025-09-07T09:52:22.5219343Z strides: [224, 1, 1, 1], [224, 1, 1, 1] 2025-09-07T09:52:22.5219630Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:22.5219938Z convolution 0.0079 ms 100.0% 2025-09-07T09:52:22.5221002Z triton_convolution2d_15 0.0086 ms 91.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=1 2025-09-07T09:52:22.5221761Z conv1x1_via_mm 0.0094 ms 84.1% 2025-09-07T09:52:22.5222489Z triton_convolution2d_14 0.0097 ms 82.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:52:22.5223789Z triton_convolution2d_13 0.0097 ms 81.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=1 2025-09-07T09:52:22.5224745Z SingleProcess AUTOTUNE benchmarking takes 0.1363 seconds and 0.0002 seconds precompiling for 5 choices 2025-09-07T09:52:24.3828481Z Autotune Choices Stats: 2025-09-07T09:52:24.3829890Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02409599907696247, "best_triton_pos": 2, "best_triton_time": 0.07548800110816956, "best_triton_kernel": "triton_convolution2d_502", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:52:24.4234675Z AUTOTUNE convolution(4x2240x7x7, 2240x2240x1x1) 2025-09-07T09:52:24.4235009Z strides: [109760, 49, 7, 1], [2240, 1, 1, 1] 2025-09-07T09:52:24.4235311Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:24.4235575Z convolution 0.0241 ms 100.0% 2025-09-07T09:52:24.4235832Z conv1x1_via_mm 0.0708 ms 34.0% 2025-09-07T09:52:24.4236581Z triton_convolution2d_502 0.0755 ms 31.9% 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 2025-09-07T09:52:24.4237814Z triton_convolution2d_504 0.0767 ms 31.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:24.4239032Z triton_convolution2d_503 0.1015 ms 23.7% 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 2025-09-07T09:52:24.4240396Z triton_convolution2d_505 0.1136 ms 21.2% 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 2025-09-07T09:52:24.4241583Z triton_convolution2d_499 0.1157 ms 20.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:24.4242716Z triton_convolution2d_501 0.1270 ms 19.0% 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 2025-09-07T09:52:24.4244188Z triton_convolution2d_500 0.1380 ms 17.5% 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 2025-09-07T09:52:24.4245087Z SingleProcess AUTOTUNE benchmarking takes 0.3610 seconds and 0.0007 seconds precompiling for 9 choices 2025-09-07T09:52:24.5463347Z Autotune Choices Stats: 2025-09-07T09:52:24.5464977Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.022655999287962914, "best_triton_pos": 1, "best_triton_time": 0.03590400144457817, "best_triton_kernel": "triton_convolution2d_511", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:52:24.5894384Z AUTOTUNE convolution(4x896x14x14, 2240x896x1x1) 2025-09-07T09:52:24.5894729Z strides: [175616, 196, 14, 1], [896, 1, 1, 1] 2025-09-07T09:52:24.5895043Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:24.5895325Z convolution 0.0227 ms 100.0% 2025-09-07T09:52:24.5896069Z triton_convolution2d_511 0.0359 ms 63.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:24.5897312Z triton_convolution2d_509 0.0364 ms 62.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:24.5898542Z triton_convolution2d_510 0.0517 ms 43.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:24.5899753Z triton_convolution2d_506 0.0532 ms 42.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:24.5901319Z triton_convolution2d_512 0.0598 ms 37.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:52:24.5902460Z triton_convolution2d_507 0.0632 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:52:24.5903657Z triton_convolution2d_508 0.1419 ms 16.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T09:52:24.5904555Z SingleProcess AUTOTUNE benchmarking takes 0.1649 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:52:25.0293031Z Autotune Choices Stats: 2025-09-07T09:52:25.0294303Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "bias_addmm", "best_time": 0.012128000147640705, "best_triton_pos": 1, "best_triton_time": 0.013183999806642532, "best_triton_kernel": "triton_mm_517", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T09:52:25.0473432Z AUTOTUNE addmm(4x1000, 4x2240, 2240x1000) 2025-09-07T09:52:25.0473730Z strides: [0, 1], [2240, 1], [1, 2240] 2025-09-07T09:52:25.0474036Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:52:25.0474344Z bias_addmm 0.0121 ms 100.0% 2025-09-07T09:52:25.0474956Z triton_mm_517 0.0132 ms 92.0% 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 2025-09-07T09:52:25.0475933Z triton_mm_521 0.0134 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:25.0476764Z addmm 0.0147 ms 82.8% 2025-09-07T09:52:25.0477336Z triton_mm_525 0.0150 ms 80.6% 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 2025-09-07T09:52:25.0478489Z triton_mm_529 0.0163 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:52:25.0479447Z triton_mm_516 0.0185 ms 65.6% 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 2025-09-07T09:52:25.0480669Z triton_mm_515 0.0195 ms 62.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:25.0481634Z triton_mm_520 0.0198 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:25.0482529Z triton_mm_514 0.0220 ms 55.0% 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 2025-09-07T09:52:25.0483319Z SingleProcess AUTOTUNE benchmarking takes 0.4569 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:52:37.2492498Z Autotune Choices Stats: 2025-09-07T09:52:37.2493710Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_552", "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": 0.00687999976798892, "best_triton_pos": 0} 2025-09-07T09:52:37.3158606Z AUTOTUNE mm(1000x4, 4x2240) 2025-09-07T09:52:37.3158902Z strides: [1, 1000], [2240, 1] 2025-09-07T09:52:37.3159192Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:37.3159891Z triton_mm_552 0.0069 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 2025-09-07T09:52:37.3161356Z triton_mm_553 0.0069 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:52:37.3162439Z triton_mm_554 0.0070 ms 98.6% 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 2025-09-07T09:52:37.3163509Z triton_mm_559 0.0071 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:52:37.3164560Z triton_mm_551 0.0071 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:52:37.3165570Z triton_mm_555 0.0071 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:37.3166547Z triton_mm_557 0.0072 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:52:37.3167514Z triton_mm_558 0.0072 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:37.3168484Z triton_mm_556 0.0073 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:52:37.3169457Z triton_mm_560 0.0075 ms 91.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:52:37.3170909Z SingleProcess AUTOTUNE benchmarking takes 0.2262 seconds and 0.0004 seconds precompiling for 17 choices 2025-09-07T09:52:37.9203060Z Autotune Choices Stats: 2025-09-07T09:52:37.9205693Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009503999724984169, "best_triton_pos": 1, "best_triton_time": 0.01033599954098463, "best_triton_kernel": "triton_mm_538", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:52:37.9705355Z AUTOTUNE mm(4x1000, 1000x2240) 2025-09-07T09:52:37.9705773Z strides: [1000, 1], [2240, 1] 2025-09-07T09:52:37.9706148Z dtypes: torch.float16, torch.float16 2025-09-07T09:52:37.9706525Z mm 0.0095 ms 100.0% 2025-09-07T09:52:37.9707476Z triton_mm_538 0.0103 ms 92.0% 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 2025-09-07T09:52:37.9708959Z triton_mm_534 0.0108 ms 88.1% 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 2025-09-07T09:52:37.9710691Z triton_mm_546 0.0115 ms 83.0% 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 2025-09-07T09:52:37.9712142Z triton_mm_532 0.0119 ms 79.6% 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 2025-09-07T09:52:37.9713605Z triton_mm_542 0.0124 ms 76.9% 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 2025-09-07T09:52:37.9715140Z triton_mm_537 0.0124 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:37.9716445Z triton_mm_533 0.0127 ms 74.8% 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 2025-09-07T09:52:37.9717744Z triton_mm_541 0.0133 ms 71.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:52:37.9719034Z triton_mm_544 0.0135 ms 70.4% 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 2025-09-07T09:52:37.9720179Z SingleProcess AUTOTUNE benchmarking takes 0.2343 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:52:44.1936692Z W0907 09:52:44.192000 87713 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:53:18.6695714Z W0907 09:53:18.668000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6702847Z W0907 09:53:18.669000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6714931Z W0907 09:53:18.671000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6721749Z W0907 09:53:18.671000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6727428Z W0907 09:53:18.672000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6734008Z W0907 09:53:18.673000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6739891Z W0907 09:53:18.673000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6746429Z W0907 09:53:18.674000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6753115Z W0907 09:53:18.674000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6766599Z W0907 09:53:18.676000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6772674Z W0907 09:53:18.676000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6778920Z W0907 09:53:18.677000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6785268Z W0907 09:53:18.678000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6791357Z W0907 09:53:18.678000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6797821Z W0907 09:53:18.679000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6804322Z W0907 09:53:18.680000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6809929Z W0907 09:53:18.680000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6816442Z W0907 09:53:18.681000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6822652Z W0907 09:53:18.681000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6828810Z W0907 09:53:18.682000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6838894Z W0907 09:53:18.683000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6845060Z W0907 09:53:18.684000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6851490Z W0907 09:53:18.684000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6857473Z W0907 09:53:18.685000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6863880Z W0907 09:53:18.686000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6870458Z W0907 09:53:18.686000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6876716Z W0907 09:53:18.687000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6882864Z W0907 09:53:18.687000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6888973Z W0907 09:53:18.688000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6895586Z W0907 09:53:18.689000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.6901731Z W0907 09:53:18.689000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.7169018Z W0907 09:53:18.690000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.7169844Z W0907 09:53:18.691000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8945749Z W0907 09:53:18.691000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8946813Z W0907 09:53:18.692000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8947649Z W0907 09:53:18.693000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8948470Z W0907 09:53:18.694000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8949286Z W0907 09:53:18.694000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8950096Z W0907 09:53:18.695000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8951237Z W0907 09:53:18.736000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8952061Z W0907 09:53:18.737000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8952868Z W0907 09:53:18.738000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8953675Z W0907 09:53:18.738000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8954486Z W0907 09:53:18.739000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8955296Z W0907 09:53:18.740000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8956105Z W0907 09:53:18.740000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8956925Z W0907 09:53:18.741000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8957721Z W0907 09:53:18.742000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8958387Z W0907 09:53:18.742000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8959046Z W0907 09:53:18.744000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8959705Z W0907 09:53:18.744000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8960486Z W0907 09:53:18.745000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8961151Z W0907 09:53:18.746000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8961800Z W0907 09:53:18.746000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8962445Z W0907 09:53:18.747000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8963082Z W0907 09:53:18.748000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8963909Z W0907 09:53:18.748000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8964552Z W0907 09:53:18.749000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8965331Z W0907 09:53:18.750000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8965982Z W0907 09:53:18.750000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8966625Z W0907 09:53:18.751000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8967273Z W0907 09:53:18.752000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8967941Z W0907 09:53:18.753000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8968582Z W0907 09:53:18.753000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8969224Z W0907 09:53:18.754000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8969886Z W0907 09:53:18.754000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8970672Z W0907 09:53:18.755000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8971328Z W0907 09:53:18.756000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8971985Z W0907 09:53:18.757000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8972640Z W0907 09:53:18.757000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8973286Z W0907 09:53:18.758000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8973946Z W0907 09:53:18.759000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8974587Z W0907 09:53:18.759000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8975234Z W0907 09:53:18.760000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8975877Z W0907 09:53:18.761000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8976534Z W0907 09:53:18.762000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8977183Z W0907 09:53:18.762000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8977824Z W0907 09:53:18.763000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8978472Z W0907 09:53:18.764000 87713 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T09:53:18.8983190Z pass 2025-09-07T09:53:25.0288320Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:53:25.0290676Z import pynvml # type: ignore[import] 2025-09-07T09:53:27.6662684Z 2025-09-07T09:53:30.4725952Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:53:30.4726319Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:53:30.4726621Z cuda train timm_resnest 2025-09-07T09:53:43.2455142Z Autotune Choices Stats: 2025-09-07T09:53:43.2456688Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_16", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.022431999444961548, "best_triton_pos": 0} 2025-09-07T09:53:43.2741804Z AUTOTUNE convolution(4x32x112x112, 64x32x3x3) 2025-09-07T09:53:43.2742099Z strides: [401408, 12544, 112, 1], [288, 9, 3, 1] 2025-09-07T09:53:43.2742383Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:43.2743172Z triton_convolution2d_16 0.0224 ms 100.0% 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 2025-09-07T09:53:43.2744336Z triton_convolution2d_14 0.0240 ms 93.6% 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 2025-09-07T09:53:43.2745472Z triton_convolution2d_19 0.0245 ms 91.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:43.2746595Z triton_convolution2d_17 0.0250 ms 89.8% 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 2025-09-07T09:53:43.2747715Z triton_convolution2d_18 0.0252 ms 89.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:53:43.2748832Z triton_convolution2d_13 0.0254 ms 88.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:43.2749516Z convolution 0.0330 ms 68.0% 2025-09-07T09:53:43.2750544Z triton_convolution2d_15 0.0705 ms 31.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:53:43.2751490Z SingleProcess AUTOTUNE benchmarking takes 0.1371 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T09:53:43.8356879Z Autotune Choices Stats: 2025-09-07T09:53:43.8358299Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009472000412642956, "best_triton_pos": 1, "best_triton_time": 0.009631999768316746, "best_triton_kernel": "triton_convolution2d_46", "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"} 2025-09-07T09:53:43.8872799Z AUTOTUNE convolution(4x64x56x56, 256x64x1x1) 2025-09-07T09:53:43.8873113Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:53:43.8873383Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:43.8873642Z convolution 0.0095 ms 100.0% 2025-09-07T09:53:43.8874390Z triton_convolution2d_46 0.0096 ms 98.3% 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 2025-09-07T09:53:43.8875612Z triton_convolution2d_45 0.0105 ms 90.5% 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 2025-09-07T09:53:43.8877215Z triton_convolution2d_48 0.0106 ms 89.4% 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 2025-09-07T09:53:43.8878627Z triton_convolution2d_47 0.0108 ms 87.8% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:43.8879836Z triton_convolution2d_42 0.0110 ms 86.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:43.8881347Z triton_convolution2d_43 0.0117 ms 80.7% 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 2025-09-07T09:53:43.8882573Z triton_convolution2d_44 0.0127 ms 74.6% 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 2025-09-07T09:53:43.8883307Z conv1x1_via_mm 0.0495 ms 19.1% 2025-09-07T09:53:43.8883797Z SingleProcess AUTOTUNE benchmarking takes 0.1893 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:46.1021262Z Autotune Choices Stats: 2025-09-07T09:53:46.1022487Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_6", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.020255999639630318, "best_triton_pos": 0} 2025-09-07T09:53:46.1554909Z AUTOTUNE convolution(4x32x112x112, 32x32x3x3) 2025-09-07T09:53:46.1555300Z strides: [401408, 12544, 112, 1], [288, 9, 3, 1] 2025-09-07T09:53:46.1555609Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:46.1556402Z triton_convolution2d_6 0.0203 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:46.1557648Z triton_convolution2d_9 0.0214 ms 94.5% 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 2025-09-07T09:53:46.1558861Z triton_convolution2d_7 0.0216 ms 93.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:53:46.1560069Z triton_convolution2d_10 0.0232 ms 87.3% 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 2025-09-07T09:53:46.1561487Z triton_convolution2d_12 0.0240 ms 84.5% 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 2025-09-07T09:53:46.1562710Z triton_convolution2d_11 0.0244 ms 82.9% 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 2025-09-07T09:53:46.1563441Z convolution 0.0295 ms 68.6% 2025-09-07T09:53:46.1564181Z triton_convolution2d_8 0.0383 ms 52.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:53:46.1565139Z SingleProcess AUTOTUNE benchmarking takes 0.3049 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:46.5936540Z Autotune Choices Stats: 2025-09-07T09:53:46.5938507Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010623999871313572, "best_triton_pos": 1, "best_triton_time": 0.013856000266969204, "best_triton_kernel": "triton_convolution2d_53", "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"} 2025-09-07T09:53:46.6228090Z AUTOTUNE convolution(4x256x56x56, 128x256x1x1) 2025-09-07T09:53:46.6228438Z strides: [802816, 3136, 56, 1], [256, 1, 1, 1] 2025-09-07T09:53:46.6228749Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:46.6229035Z convolution 0.0106 ms 100.0% 2025-09-07T09:53:46.6229788Z triton_convolution2d_53 0.0139 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 2025-09-07T09:53:46.6231256Z triton_convolution2d_54 0.0142 ms 74.9% 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 2025-09-07T09:53:46.6232487Z triton_convolution2d_52 0.0162 ms 65.5% 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 2025-09-07T09:53:46.6233723Z triton_convolution2d_55 0.0169 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 2025-09-07T09:53:46.6235086Z triton_convolution2d_49 0.0173 ms 61.3% 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 2025-09-07T09:53:46.6236302Z triton_convolution2d_50 0.0212 ms 50.1% 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 2025-09-07T09:53:46.6237519Z triton_convolution2d_51 0.0236 ms 45.0% 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 2025-09-07T09:53:46.6238261Z conv1x1_via_mm 0.0562 ms 18.9% 2025-09-07T09:53:46.6238733Z SingleProcess AUTOTUNE benchmarking takes 0.4264 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:47.5126692Z Autotune Choices Stats: 2025-09-07T09:53:47.5128162Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010239999741315842, "best_triton_pos": 1, "best_triton_time": 0.013504000380635262, "best_triton_kernel": "triton_convolution2d_76", "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"} 2025-09-07T09:53:47.5347842Z AUTOTUNE convolution(4x256x28x28, 512x256x1x1) 2025-09-07T09:53:47.5348209Z strides: [200704, 784, 28, 1], [256, 1, 1, 1] 2025-09-07T09:53:47.5348528Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:47.5348819Z convolution 0.0102 ms 100.0% 2025-09-07T09:53:47.5349588Z triton_convolution2d_76 0.0135 ms 75.8% 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 2025-09-07T09:53:47.5351049Z triton_convolution2d_75 0.0153 ms 66.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:47.5352310Z triton_convolution2d_77 0.0159 ms 64.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:47.5354009Z triton_convolution2d_78 0.0160 ms 64.1% 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 2025-09-07T09:53:47.5355685Z triton_convolution2d_73 0.0205 ms 49.9% 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 2025-09-07T09:53:47.5357031Z triton_convolution2d_72 0.0206 ms 49.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:47.5358374Z triton_convolution2d_74 0.0235 ms 43.6% 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 2025-09-07T09:53:47.5359198Z conv1x1_via_mm 0.0377 ms 27.2% 2025-09-07T09:53:47.5359703Z SingleProcess AUTOTUNE benchmarking takes 0.3062 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:48.8875349Z Autotune Choices Stats: 2025-09-07T09:53:48.8877020Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.009535999968647957, "best_triton_pos": 1, "best_triton_time": 0.01065600011497736, "best_triton_kernel": "triton_convolution2d_69", "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"} 2025-09-07T09:53:48.8924348Z AUTOTUNE convolution(4x128x28x28, 512x128x1x1) 2025-09-07T09:53:48.8924697Z strides: [100352, 784, 28, 1], [128, 1, 1, 1] 2025-09-07T09:53:48.8925012Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:48.8925373Z convolution 0.0095 ms 100.0% 2025-09-07T09:53:48.8926442Z triton_convolution2d_69 0.0107 ms 89.5% 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 2025-09-07T09:53:48.8928001Z triton_convolution2d_68 0.0114 ms 83.9% 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 2025-09-07T09:53:48.8929546Z triton_convolution2d_70 0.0117 ms 81.2% 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 2025-09-07T09:53:48.8931561Z triton_convolution2d_71 0.0120 ms 79.7% 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 2025-09-07T09:53:48.8933072Z triton_convolution2d_66 0.0140 ms 67.9% 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 2025-09-07T09:53:48.8934566Z triton_convolution2d_65 0.0143 ms 66.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:48.8936046Z triton_convolution2d_67 0.0155 ms 61.4% 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 2025-09-07T09:53:48.8936746Z conv1x1_via_mm 0.0321 ms 29.7% 2025-09-07T09:53:48.8937184Z SingleProcess AUTOTUNE benchmarking takes 0.1387 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:49.0668115Z Autotune Choices Stats: 2025-09-07T09:53:49.0669269Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_25", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8", "best_time": 0.008031999692320824, "best_triton_pos": 0} 2025-09-07T09:53:49.0723548Z AUTOTUNE convolution(4x64x56x56, 64x64x1x1) 2025-09-07T09:53:49.0723888Z strides: [200704, 3136, 56, 1], [64, 1, 1, 1] 2025-09-07T09:53:49.0724196Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:49.0724960Z triton_convolution2d_25 0.0080 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=8 2025-09-07T09:53:49.0726384Z triton_convolution2d_24 0.0082 ms 98.4% 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 2025-09-07T09:53:49.0727702Z triton_convolution2d_23 0.0086 ms 93.7% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:49.0728549Z convolution 0.0087 ms 92.3% 2025-09-07T09:53:49.0729330Z triton_convolution2d_20 0.0091 ms 88.7% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:49.0730798Z triton_convolution2d_26 0.0095 ms 84.5% 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 2025-09-07T09:53:49.0732124Z triton_convolution2d_21 0.0109 ms 73.6% 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 2025-09-07T09:53:49.0733454Z triton_convolution2d_22 0.0112 ms 71.7% 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 2025-09-07T09:53:49.0734259Z conv1x1_via_mm 0.0277 ms 29.0% 2025-09-07T09:53:49.0734776Z SingleProcess AUTOTUNE benchmarking takes 0.1388 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:49.4722029Z Autotune Choices Stats: 2025-09-07T09:53:49.4723390Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.010367999784648418, "best_triton_pos": 1, "best_triton_time": 0.018688000738620758, "best_triton_kernel": "triton_convolution2d_83", "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"} 2025-09-07T09:53:49.4807149Z AUTOTUNE convolution(4x512x28x28, 256x512x1x1) 2025-09-07T09:53:49.4807476Z strides: [401408, 784, 28, 1], [512, 1, 1, 1] 2025-09-07T09:53:49.4807763Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:49.4808025Z convolution 0.0104 ms 100.0% 2025-09-07T09:53:49.4808768Z triton_convolution2d_83 0.0187 ms 55.5% 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 2025-09-07T09:53:49.4810020Z triton_convolution2d_82 0.0226 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 2025-09-07T09:53:49.4811434Z triton_convolution2d_85 0.0226 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 2025-09-07T09:53:49.4813046Z triton_convolution2d_84 0.0238 ms 43.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:49.4814514Z triton_convolution2d_79 0.0320 ms 32.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:49.4815732Z triton_convolution2d_80 0.0334 ms 31.0% 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 2025-09-07T09:53:49.4816948Z triton_convolution2d_81 0.0385 ms 27.0% 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 2025-09-07T09:53:49.4817696Z conv1x1_via_mm 0.0388 ms 26.7% 2025-09-07T09:53:49.4818175Z SingleProcess AUTOTUNE benchmarking takes 0.1471 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:49.8612085Z Autotune Choices Stats: 2025-09-07T09:53:49.8613798Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.015647999942302704, "best_triton_pos": 1, "best_triton_time": 0.018912000581622124, "best_triton_kernel": "triton_convolution2d_108", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:53:49.8723427Z AUTOTUNE convolution(4x512x14x14, 1024x512x1x1) 2025-09-07T09:53:49.8723750Z strides: [100352, 196, 14, 1], [512, 1, 1, 1] 2025-09-07T09:53:49.8724064Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:49.8724330Z convolution 0.0156 ms 100.0% 2025-09-07T09:53:49.8725077Z triton_convolution2d_108 0.0189 ms 82.7% 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 2025-09-07T09:53:49.8726561Z triton_convolution2d_107 0.0229 ms 68.4% 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 2025-09-07T09:53:49.8727998Z triton_convolution2d_109 0.0233 ms 67.2% 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 2025-09-07T09:53:49.8729401Z triton_convolution2d_110 0.0235 ms 66.5% 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 2025-09-07T09:53:49.8730660Z conv1x1_via_mm 0.0273 ms 57.3% 2025-09-07T09:53:49.8731515Z triton_convolution2d_105 0.0286 ms 54.7% 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 2025-09-07T09:53:49.8732945Z triton_convolution2d_104 0.0323 ms 48.5% 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 2025-09-07T09:53:49.8734383Z triton_convolution2d_106 0.0413 ms 37.8% 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 2025-09-07T09:53:49.8735509Z SingleProcess AUTOTUNE benchmarking takes 0.1485 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:51.5744728Z Autotune Choices Stats: 2025-09-07T09:53:51.5746685Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.011648000217974186, "best_triton_pos": 1, "best_triton_time": 0.012959999963641167, "best_triton_kernel": "triton_convolution2d_101", "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"} 2025-09-07T09:53:51.6138725Z AUTOTUNE convolution(4x256x14x14, 1024x256x1x1) 2025-09-07T09:53:51.6139104Z strides: [50176, 196, 14, 1], [256, 1, 1, 1] 2025-09-07T09:53:51.6139413Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:51.6139690Z convolution 0.0116 ms 100.0% 2025-09-07T09:53:51.6140941Z triton_convolution2d_101 0.0130 ms 89.9% 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 2025-09-07T09:53:51.6142187Z triton_convolution2d_102 0.0153 ms 76.2% 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 2025-09-07T09:53:51.6143494Z triton_convolution2d_100 0.0154 ms 75.7% 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 2025-09-07T09:53:51.6144745Z triton_convolution2d_103 0.0156 ms 74.6% 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 2025-09-07T09:53:51.6146017Z triton_convolution2d_98 0.0183 ms 63.7% 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 2025-09-07T09:53:51.6147221Z triton_convolution2d_97 0.0201 ms 57.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:51.6148342Z triton_convolution2d_99 0.0249 ms 46.8% 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 2025-09-07T09:53:51.6149034Z conv1x1_via_mm 0.0263 ms 44.2% 2025-09-07T09:53:51.6149476Z SingleProcess AUTOTUNE benchmarking takes 0.1703 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:51.7993433Z Autotune Choices Stats: 2025-09-07T09:53:51.7994625Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020447999238967896, "best_triton_pos": 2, "best_triton_time": 0.03017600066959858, "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=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:53:51.8125201Z AUTOTUNE convolution(4x1024x14x14, 512x1024x1x1) 2025-09-07T09:53:51.8125557Z strides: [200704, 196, 14, 1], [1024, 1, 1, 1] 2025-09-07T09:53:51.8125841Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:51.8126174Z convolution 0.0204 ms 100.0% 2025-09-07T09:53:51.8126474Z conv1x1_via_mm 0.0301 ms 67.9% 2025-09-07T09:53:51.8127308Z triton_convolution2d_115 0.0302 ms 67.8% 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 2025-09-07T09:53:51.8128614Z triton_convolution2d_114 0.0371 ms 55.2% 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 2025-09-07T09:53:51.8129883Z triton_convolution2d_116 0.0382 ms 53.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:51.8131985Z triton_convolution2d_117 0.0387 ms 52.8% 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 2025-09-07T09:53:51.8133451Z triton_convolution2d_112 0.0500 ms 40.9% 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 2025-09-07T09:53:51.8134721Z triton_convolution2d_111 0.0576 ms 35.5% 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 2025-09-07T09:53:51.8136015Z triton_convolution2d_113 0.0766 ms 26.7% 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 2025-09-07T09:53:51.8136983Z SingleProcess AUTOTUNE benchmarking takes 0.1577 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:52.3529445Z Autotune Choices Stats: 2025-09-07T09:53:52.3531086Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.008576000109314919, "best_triton_pos": 2, "best_triton_time": 0.010591999627649784, "best_triton_kernel": "triton_convolution2d_128", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:53:52.3672776Z AUTOTUNE convolution(4x256x1x1, 1024x256x1x1) 2025-09-07T09:53:52.3673142Z strides: [256, 1, 1, 1], [256, 1, 1, 1] 2025-09-07T09:53:52.3673441Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:52.3673767Z convolution 0.0086 ms 100.0% 2025-09-07T09:53:52.3674023Z conv1x1_via_mm 0.0098 ms 87.3% 2025-09-07T09:53:52.3674788Z triton_convolution2d_128 0.0106 ms 81.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:52.3676095Z triton_convolution2d_127 0.0110 ms 78.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:52.3677384Z triton_convolution2d_126 0.0122 ms 70.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:53:52.3678600Z triton_convolution2d_129 0.0127 ms 67.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:53:52.3679810Z triton_convolution2d_125 0.0132 ms 65.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:52.3681177Z triton_convolution2d_124 0.0158 ms 54.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:53:52.3682142Z SingleProcess AUTOTUNE benchmarking takes 0.3072 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:52.8724159Z Autotune Choices Stats: 2025-09-07T09:53:52.8725284Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_95", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.007872000336647034, "best_triton_pos": 0} 2025-09-07T09:53:52.9146793Z AUTOTUNE convolution(4x128x1x1, 512x128x1x1) 2025-09-07T09:53:52.9147184Z strides: [128, 1, 1, 1], [128, 1, 1, 1] 2025-09-07T09:53:52.9147491Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:52.9148874Z triton_convolution2d_95 0.0079 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:52.9150199Z triton_convolution2d_94 0.0082 ms 96.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:52.9151666Z triton_convolution2d_93 0.0085 ms 92.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:53:52.9152912Z triton_convolution2d_92 0.0086 ms 91.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:52.9153661Z convolution 0.0092 ms 85.4% 2025-09-07T09:53:52.9154404Z triton_convolution2d_96 0.0093 ms 84.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:53:52.9155161Z conv1x1_via_mm 0.0105 ms 75.2% 2025-09-07T09:53:52.9155897Z triton_convolution2d_91 0.0105 ms 75.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:53:52.9156961Z SingleProcess AUTOTUNE benchmarking takes 0.1623 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:53.2928157Z Autotune Choices Stats: 2025-09-07T09:53:53.2929244Z {"num_choices": 8, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_63", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.006463999859988689, "best_triton_pos": 0} 2025-09-07T09:53:53.3376703Z AUTOTUNE convolution(4x64x1x1, 256x64x1x1) 2025-09-07T09:53:53.3377085Z strides: [64, 1, 1, 1], [64, 1, 1, 1] 2025-09-07T09:53:53.3377393Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:53.3378197Z triton_convolution2d_63 0.0065 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:53.3379445Z triton_convolution2d_60 0.0067 ms 97.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:53.3380858Z triton_convolution2d_61 0.0068 ms 95.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:53:53.3382085Z triton_convolution2d_62 0.0068 ms 94.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:53.3383431Z triton_convolution2d_64 0.0071 ms 90.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, 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 2025-09-07T09:53:53.3384202Z convolution 0.0079 ms 82.1% 2025-09-07T09:53:53.3384935Z triton_convolution2d_59 0.0079 ms 82.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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 2025-09-07T09:53:53.3386041Z conv1x1_via_mm 0.0090 ms 71.9% 2025-09-07T09:53:53.3386622Z SingleProcess AUTOTUNE benchmarking takes 0.2115 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:53:53.8752006Z Autotune Choices Stats: 2025-09-07T09:53:53.8753621Z {"num_choices": 7, "num_triton_choices": 5, "best_kernel": "triton_convolution2d_34", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.005824000108987093, "best_triton_pos": 0} 2025-09-07T09:53:53.8939746Z AUTOTUNE convolution(4x32x1x1, 128x32x1x1) 2025-09-07T09:53:53.8940072Z strides: [32, 1, 1, 1], [32, 1, 1, 1] 2025-09-07T09:53:53.8940713Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:53.8941504Z triton_convolution2d_34 0.0058 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:53.8942776Z triton_convolution2d_33 0.0059 ms 98.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:53.8944093Z triton_convolution2d_30 0.0060 ms 97.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:53.8945320Z triton_convolution2d_31 0.0060 ms 97.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:53.8946568Z triton_convolution2d_32 0.0060 ms 97.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:53:53.8947413Z convolution 0.0074 ms 79.1% 2025-09-07T09:53:53.8947651Z conv1x1_via_mm 0.0089 ms 65.7% 2025-09-07T09:53:53.8948143Z SingleProcess AUTOTUNE benchmarking takes 0.1252 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T09:53:55.2929296Z Autotune Choices Stats: 2025-09-07T09:53:55.2931923Z {"num_choices": 5, "num_triton_choices": 3, "best_kernel": "triton_convolution2d_58", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.007903999648988247, "best_triton_pos": 0} 2025-09-07T09:53:55.3254874Z AUTOTUNE convolution(4x128x1x1, 64x128x1x1) 2025-09-07T09:53:55.3255146Z strides: [128, 1, 1, 1], [128, 1, 1, 1] 2025-09-07T09:53:55.3255408Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:55.3256077Z triton_convolution2d_58 0.0079 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:55.3257105Z triton_convolution2d_57 0.0080 ms 99.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:53:55.3258087Z triton_convolution2d_56 0.0089 ms 89.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:55.3258683Z convolution 0.0090 ms 88.2% 2025-09-07T09:53:55.3258886Z conv1x1_via_mm 0.0105 ms 75.1% 2025-09-07T09:53:55.3259275Z SingleProcess AUTOTUNE benchmarking takes 0.2413 seconds and 0.0002 seconds precompiling for 5 choices 2025-09-07T09:53:56.1945948Z Autotune Choices Stats: 2025-09-07T09:53:56.1947192Z {"num_choices": 5, "num_triton_choices": 3, "best_kernel": "triton_convolution2d_29", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=2", "best_time": 0.006560000125318766, "best_triton_pos": 0} 2025-09-07T09:53:56.2124590Z AUTOTUNE convolution(4x64x1x1, 32x64x1x1) 2025-09-07T09:53:56.2124940Z strides: [64, 1, 1, 1], [64, 1, 1, 1] 2025-09-07T09:53:56.2125233Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:56.2126107Z triton_convolution2d_29 0.0066 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=2 2025-09-07T09:53:56.2127438Z triton_convolution2d_28 0.0068 ms 96.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, 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=1 2025-09-07T09:53:56.2128715Z triton_convolution2d_27 0.0069 ms 94.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=16, BLOCK_N=32, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=2 2025-09-07T09:53:56.2129456Z convolution 0.0079 ms 83.0% 2025-09-07T09:53:56.2129708Z conv1x1_via_mm 0.0119 ms 55.1% 2025-09-07T09:53:56.2130199Z SingleProcess AUTOTUNE benchmarking takes 0.1983 seconds and 0.0002 seconds precompiling for 5 choices 2025-09-07T09:53:58.0472305Z Autotune Choices Stats: 2025-09-07T09:53:58.0473766Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.017535999417304993, "best_triton_pos": 1, "best_triton_time": 0.02287999913096428, "best_triton_kernel": "triton_convolution2d_134", "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"} 2025-09-07T09:53:58.0775331Z AUTOTUNE convolution(4x512x7x7, 2048x512x1x1) 2025-09-07T09:53:58.0775854Z strides: [25088, 49, 7, 1], [512, 1, 1, 1] 2025-09-07T09:53:58.0776332Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:58.0776794Z convolution 0.0175 ms 100.0% 2025-09-07T09:53:58.0778065Z triton_convolution2d_134 0.0229 ms 76.6% 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 2025-09-07T09:53:58.0779583Z triton_convolution2d_133 0.0232 ms 75.5% 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 2025-09-07T09:53:58.0780884Z conv1x1_via_mm 0.0258 ms 67.9% 2025-09-07T09:53:58.0781639Z triton_convolution2d_135 0.0281 ms 62.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:58.0782939Z triton_convolution2d_132 0.0302 ms 58.0% 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 2025-09-07T09:53:58.0784170Z triton_convolution2d_136 0.0308 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 2025-09-07T09:53:58.0785380Z triton_convolution2d_130 0.0329 ms 53.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:58.0786591Z triton_convolution2d_131 0.0372 ms 47.2% 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 2025-09-07T09:53:58.0788113Z SingleProcess AUTOTUNE benchmarking takes 0.1695 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:58.2237735Z Autotune Choices Stats: 2025-09-07T09:53:58.2239781Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01913600042462349, "best_triton_pos": 2, "best_triton_time": 0.03830400109291077, "best_triton_kernel": "triton_convolution2d_140", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:53:58.2969316Z AUTOTUNE convolution(4x1024x7x7, 2048x1024x1x1) 2025-09-07T09:53:58.2969625Z strides: [50176, 49, 7, 1], [1024, 1, 1, 1] 2025-09-07T09:53:58.2969874Z dtypes: torch.float16, torch.float16 2025-09-07T09:53:58.2970127Z convolution 0.0191 ms 100.0% 2025-09-07T09:53:58.2970495Z conv1x1_via_mm 0.0300 ms 63.9% 2025-09-07T09:53:58.2971155Z triton_convolution2d_140 0.0383 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 2025-09-07T09:53:58.2972263Z triton_convolution2d_141 0.0396 ms 48.3% 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 2025-09-07T09:53:58.2973330Z triton_convolution2d_142 0.0484 ms 39.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:53:58.2974399Z triton_convolution2d_139 0.0544 ms 35.2% 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 2025-09-07T09:53:58.2975466Z triton_convolution2d_143 0.0552 ms 34.6% 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 2025-09-07T09:53:58.2976539Z triton_convolution2d_137 0.0583 ms 32.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:53:58.2977592Z triton_convolution2d_138 0.0674 ms 28.4% 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 2025-09-07T09:53:58.2978449Z SingleProcess AUTOTUNE benchmarking takes 0.2184 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:53:58.7946842Z Autotune Choices Stats: 2025-09-07T09:53:58.7947903Z {"num_choices": 19, "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=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2", "best_time": 0.010944000445306301, "best_triton_pos": 0} 2025-09-07T09:53:58.9405038Z AUTOTUNE addmm(4x1000, 4x2048, 2048x1000) 2025-09-07T09:53:58.9405343Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T09:53:58.9405679Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:53:58.9406407Z triton_mm_148 0.0109 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:58.9407050Z bias_addmm 0.0111 ms 98.6% 2025-09-07T09:53:58.9407655Z triton_mm_152 0.0115 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:53:58.9408951Z triton_mm_156 0.0137 ms 80.1% 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 2025-09-07T09:53:58.9409585Z addmm 0.0146 ms 74.8% 2025-09-07T09:53:58.9410176Z triton_mm_160 0.0154 ms 71.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:53:58.9411658Z triton_mm_147 0.0173 ms 63.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:53:58.9412627Z triton_mm_146 0.0181 ms 60.5% 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 2025-09-07T09:53:58.9413590Z triton_mm_151 0.0185 ms 59.3% 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 2025-09-07T09:53:58.9414555Z triton_mm_145 0.0187 ms 58.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:53:58.9415423Z SingleProcess AUTOTUNE benchmarking takes 0.6427 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:54:12.1358876Z Autotune Choices Stats: 2025-09-07T09:54:12.1359962Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_184", "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=3, num_warps=8", "best_time": 0.006783999968320131, "best_triton_pos": 0} 2025-09-07T09:54:12.2007099Z AUTOTUNE mm(1000x4, 4x2048) 2025-09-07T09:54:12.2007588Z strides: [1, 1000], [2048, 1] 2025-09-07T09:54:12.2008045Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.2009130Z triton_mm_184 0.0068 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 2025-09-07T09:54:12.2011012Z triton_mm_183 0.0069 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:54:12.2012631Z triton_mm_185 0.0069 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:12.2013526Z triton_mm_190 0.0069 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:12.2014417Z triton_mm_187 0.0070 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:12.2015310Z triton_mm_188 0.0070 ms 97.2% 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 2025-09-07T09:54:12.2016211Z triton_mm_186 0.0070 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:12.2017105Z triton_mm_182 0.0070 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:12.2017990Z triton_mm_189 0.0071 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:12.2018897Z triton_mm_193 0.0072 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:12.2020013Z SingleProcess AUTOTUNE benchmarking takes 0.2245 seconds and 0.0004 seconds precompiling for 17 choices 2025-09-07T09:54:12.7594114Z Autotune Choices Stats: 2025-09-07T09:54:12.7595718Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009440000168979168, "best_triton_pos": 1, "best_triton_time": 0.01017600018531084, "best_triton_kernel": "triton_mm_169", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:54:12.7697908Z AUTOTUNE mm(4x1000, 1000x2048) 2025-09-07T09:54:12.7698373Z strides: [1000, 1], [2048, 1] 2025-09-07T09:54:12.7698812Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:12.7699269Z mm 0.0094 ms 100.0% 2025-09-07T09:54:12.7700582Z triton_mm_169 0.0102 ms 92.8% 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 2025-09-07T09:54:12.7702347Z triton_mm_173 0.0105 ms 89.7% 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 2025-09-07T09:54:12.7703520Z triton_mm_165 0.0112 ms 84.3% 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 2025-09-07T09:54:12.7704438Z triton_mm_177 0.0118 ms 80.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:12.7705355Z triton_mm_163 0.0118 ms 79.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:12.7706258Z triton_mm_168 0.0124 ms 76.0% 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 2025-09-07T09:54:12.7707161Z triton_mm_164 0.0126 ms 74.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:54:12.7708063Z triton_mm_175 0.0132 ms 71.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:12.7708955Z triton_mm_172 0.0134 ms 70.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:12.7709749Z SingleProcess AUTOTUNE benchmarking takes 0.1938 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:54:22.7300022Z pass 2025-09-07T09:54:26.4645912Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:54:26.4648174Z import pynvml # type: ignore[import] 2025-09-07T09:54:28.8863396Z 2025-09-07T09:54:31.2728568Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:54:31.2728939Z loading model: 0it [00:02, ?it/s] 2025-09-07T09:54:31.2729277Z cuda train timm_vision_transformer 2025-09-07T09:54:45.0298414Z Autotune Choices Stats: 2025-09-07T09:54:45.0299717Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.010048000141978264, "best_triton_pos": 1, "best_triton_time": 0.010816000401973724, "best_triton_kernel": "triton_mm_52", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8"} 2025-09-07T09:54:45.0498123Z AUTOTUNE addmm(788x1536, 788x384, 384x1536) 2025-09-07T09:54:45.0498947Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T09:54:45.0499266Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:54:45.0499587Z bias_addmm 0.0100 ms 100.0% 2025-09-07T09:54:45.0500395Z triton_mm_52 0.0108 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 2025-09-07T09:54:45.0501689Z triton_mm_56 0.0110 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:45.0502693Z triton_mm_62 0.0110 ms 91.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:45.0503759Z triton_mm_63 0.0112 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:45.0504723Z triton_mm_55 0.0115 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 2025-09-07T09:54:45.0505669Z triton_mm_59 0.0115 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 2025-09-07T09:54:45.0506630Z triton_mm_54 0.0121 ms 82.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:45.0507587Z triton_mm_58 0.0122 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:45.0508560Z triton_mm_57 0.0127 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:45.0509431Z SingleProcess AUTOTUNE benchmarking takes 0.2979 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T09:54:45.9624877Z Autotune Choices Stats: 2025-09-07T09:54:45.9627229Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.0549440011382103, "best_triton_pos": 1, "best_triton_time": 0.08118399977684021, "best_triton_kernel": "triton_convolution2d_4", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:54:46.0471972Z AUTOTUNE convolution(4x3x224x224, 384x3x16x16) 2025-09-07T09:54:46.0472337Z strides: [150528, 50176, 224, 1], [768, 256, 16, 1] 2025-09-07T09:54:46.0472643Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:46.0472911Z convolution 0.0549 ms 100.0% 2025-09-07T09:54:46.0473696Z triton_convolution2d_4 0.0812 ms 67.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:46.0474952Z triton_convolution2d_6 0.1316 ms 41.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:54:46.0476204Z triton_convolution2d_3 0.1396 ms 39.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:54:46.0477443Z triton_convolution2d_1 0.1484 ms 37.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:46.0478674Z triton_convolution2d_5 0.1942 ms 28.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:54:46.0480462Z triton_convolution2d_0 0.2318 ms 23.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:54:46.0481926Z triton_convolution2d_2 0.3723 ms 14.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=16, KERNEL_W=16, PADDING_H=0, PADDING_W=0, STRIDE_H=16, STRIDE_W=16, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:54:46.0482885Z SingleProcess AUTOTUNE benchmarking takes 0.2854 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:54:46.3159042Z Autotune Choices Stats: 2025-09-07T09:54:46.3160017Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_19", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.009279999881982803, "best_triton_pos": 0} 2025-09-07T09:54:46.3286357Z AUTOTUNE addmm(788x1152, 788x384, 384x1152) 2025-09-07T09:54:46.3286639Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T09:54:46.3286943Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:54:46.3287581Z triton_mm_19 0.0093 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:46.3288477Z triton_mm_14 0.0099 ms 93.5% 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 2025-09-07T09:54:46.3289358Z triton_mm_18 0.0100 ms 93.2% 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 2025-09-07T09:54:46.3289926Z bias_addmm 0.0101 ms 92.1% 2025-09-07T09:54:46.3290633Z triton_mm_21 0.0104 ms 89.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:46.3291559Z triton_mm_17 0.0105 ms 88.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:46.3292456Z triton_mm_25 0.0109 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:46.3293350Z triton_mm_24 0.0110 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:46.3294248Z triton_mm_15 0.0114 ms 81.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:46.3295141Z triton_mm_16 0.0115 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:46.3295915Z SingleProcess AUTOTUNE benchmarking takes 0.2805 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T09:54:46.5675010Z Autotune Choices Stats: 2025-09-07T09:54:46.5675956Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_34", "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": 0.007807999849319458, "best_triton_pos": 0} 2025-09-07T09:54:46.7986506Z AUTOTUNE mm(788x384, 384x384) 2025-09-07T09:54:46.7987006Z strides: [384, 1], [1, 384] 2025-09-07T09:54:46.7987432Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:46.7988909Z triton_mm_34 0.0078 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:46.7989929Z mm 0.0082 ms 95.7% 2025-09-07T09:54:46.7991676Z triton_mm_38 0.0085 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:46.7993193Z triton_mm_33 0.0087 ms 89.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:54:46.7994149Z triton_mm_37 0.0092 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:46.7995155Z triton_mm_27 0.0093 ms 83.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:54:46.7996105Z triton_mm_36 0.0095 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:46.7997046Z triton_mm_29 0.0096 ms 81.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:46.8005775Z triton_mm_30 0.0096 ms 81.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:46.8006700Z triton_mm_40 0.0097 ms 80.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:46.8007425Z SingleProcess AUTOTUNE benchmarking takes 0.4694 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:54:47.3752248Z Autotune Choices Stats: 2025-09-07T09:54:47.3754111Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010463999584317207, "best_triton_pos": 1, "best_triton_time": 0.01119999960064888, "best_triton_kernel": "triton_mm_72", "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"} 2025-09-07T09:54:47.3813022Z AUTOTUNE mm(788x1536, 1536x384) 2025-09-07T09:54:47.3813345Z strides: [1536, 1], [1, 1536] 2025-09-07T09:54:47.3813654Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:47.3813979Z mm 0.0105 ms 100.0% 2025-09-07T09:54:47.3814695Z triton_mm_72 0.0112 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:47.3815900Z triton_mm_76 0.0125 ms 83.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:54:47.3817099Z triton_mm_68 0.0134 ms 78.2% 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 2025-09-07T09:54:47.3818359Z triton_mm_82 0.0150 ms 69.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:47.3819561Z triton_mm_71 0.0154 ms 68.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:54:47.3821145Z triton_mm_75 0.0167 ms 62.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:47.3822497Z triton_mm_65 0.0169 ms 61.9% 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 2025-09-07T09:54:47.3824110Z triton_mm_67 0.0179 ms 58.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:47.3825600Z triton_mm_81 0.0182 ms 57.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:47.3826734Z SingleProcess AUTOTUNE benchmarking takes 0.5820 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:54:47.6828051Z Autotune Choices Stats: 2025-09-07T09:54:47.6829693Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_923", "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": 0.007615999784320593, "best_triton_pos": 0} 2025-09-07T09:54:47.7017595Z AUTOTUNE addmm(4x1000, 4x384, 384x1000) 2025-09-07T09:54:47.7018001Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T09:54:47.7018407Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:54:47.7019326Z triton_mm_923 0.0076 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:54:47.7020798Z triton_mm_927 0.0079 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:47.7021630Z bias_addmm 0.0084 ms 90.5% 2025-09-07T09:54:47.7022426Z triton_mm_922 0.0085 ms 89.1% 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 2025-09-07T09:54:47.7023789Z triton_mm_926 0.0085 ms 89.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:47.7025108Z triton_mm_935 0.0086 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:47.7026382Z triton_mm_921 0.0087 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:54:47.7027654Z triton_mm_920 0.0087 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:54:47.7028941Z triton_mm_931 0.0089 ms 85.6% 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 2025-09-07T09:54:47.7030336Z triton_mm_933 0.0091 ms 83.5% 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 2025-09-07T09:54:47.7031461Z SingleProcess AUTOTUNE benchmarking takes 0.2638 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:54:59.8520593Z Autotune Choices Stats: 2025-09-07T09:54:59.8521957Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009375999681651592, "best_triton_pos": 1, "best_triton_time": 0.009983999654650688, "best_triton_kernel": "triton_mm_987", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T09:54:59.8796513Z AUTOTUNE mm(788x384, 384x1536) 2025-09-07T09:54:59.8796808Z strides: [384, 1], [1536, 1] 2025-09-07T09:54:59.8797073Z dtypes: torch.float16, torch.float16 2025-09-07T09:54:59.8797865Z mm 0.0094 ms 100.0% 2025-09-07T09:54:59.8798449Z triton_mm_987 0.0100 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:54:59.8799433Z triton_mm_980 0.0101 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:59.8800821Z triton_mm_986 0.0101 ms 92.7% 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 2025-09-07T09:54:59.8801829Z triton_mm_979 0.0104 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:59.8802791Z triton_mm_976 0.0104 ms 90.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:54:59.8803751Z triton_mm_983 0.0106 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:54:59.8804703Z triton_mm_978 0.0110 ms 85.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:59.8805670Z triton_mm_982 0.0115 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 2025-09-07T09:54:59.8806688Z triton_mm_985 0.0115 ms 81.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:54:59.8807510Z SingleProcess AUTOTUNE benchmarking takes 0.2238 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:55:00.6233816Z Autotune Choices Stats: 2025-09-07T09:55:00.6235142Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009952000342309475, "best_triton_pos": 1, "best_triton_time": 0.010944000445306301, "best_triton_kernel": "triton_mm_1000", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:55:00.6677607Z AUTOTUNE mm(384x788, 788x1536) 2025-09-07T09:55:00.6677920Z strides: [1, 384], [1536, 1] 2025-09-07T09:55:00.6678178Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:00.6678441Z mm 0.0100 ms 100.0% 2025-09-07T09:55:00.6679040Z triton_mm_1000 0.0109 ms 90.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:00.6680025Z triton_mm_995 0.0123 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:00.6681464Z triton_mm_999 0.0125 ms 79.3% 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 2025-09-07T09:55:00.6682501Z triton_mm_1002 0.0126 ms 78.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:00.6683515Z triton_mm_998 0.0127 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:00.6684508Z triton_mm_1006 0.0131 ms 76.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:00.6685500Z triton_mm_996 0.0134 ms 74.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:00.6687053Z triton_mm_1005 0.0138 ms 72.0% 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 2025-09-07T09:55:00.6688207Z triton_mm_991 0.0156 ms 64.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:00.6689003Z SingleProcess AUTOTUNE benchmarking takes 0.2480 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:01.0589127Z Autotune Choices Stats: 2025-09-07T09:55:01.0590796Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009952000342309475, "best_triton_pos": 1, "best_triton_time": 0.011008000001311302, "best_triton_kernel": "triton_mm_1038", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:55:01.0739604Z AUTOTUNE mm(1536x788, 788x384) 2025-09-07T09:55:01.0739954Z strides: [1, 1536], [384, 1] 2025-09-07T09:55:01.0740387Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:01.0740685Z mm 0.0100 ms 100.0% 2025-09-07T09:55:01.0741358Z triton_mm_1038 0.0110 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:01.0742378Z triton_mm_1033 0.0123 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:01.0743475Z triton_mm_1037 0.0124 ms 80.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:01.0744467Z triton_mm_1036 0.0125 ms 79.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:01.0745478Z triton_mm_1040 0.0125 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:01.0746541Z triton_mm_1044 0.0130 ms 76.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:01.0747456Z triton_mm_1034 0.0132 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:01.0748366Z triton_mm_1043 0.0136 ms 73.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:01.0749278Z triton_mm_1035 0.0152 ms 65.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:01.0750066Z SingleProcess AUTOTUNE benchmarking takes 0.2177 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:01.5594717Z Autotune Choices Stats: 2025-09-07T09:55:01.5595842Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1110", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.009631999768316746, "best_triton_pos": 0} 2025-09-07T09:55:01.5840457Z AUTOTUNE mm(1152x788, 788x384) 2025-09-07T09:55:01.5840754Z strides: [1, 1152], [384, 1] 2025-09-07T09:55:01.5841014Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:01.5841682Z triton_mm_1110 0.0096 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:01.5842835Z mm 0.0098 ms 98.0% 2025-09-07T09:55:01.5843426Z triton_mm_1114 0.0108 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:01.5844687Z triton_mm_1109 0.0114 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:01.5845680Z triton_mm_1113 0.0121 ms 79.8% 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 2025-09-07T09:55:01.5846682Z triton_mm_1112 0.0121 ms 79.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:01.5847650Z triton_mm_1116 0.0123 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:01.5848550Z triton_mm_1105 0.0126 ms 76.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:01.5849490Z triton_mm_1106 0.0127 ms 75.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:01.5850565Z triton_mm_1120 0.0129 ms 74.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:01.5851382Z SingleProcess AUTOTUNE benchmarking takes 0.2289 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:55:02.1519058Z Autotune Choices Stats: 2025-09-07T09:55:02.1520081Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_959", "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=3, num_warps=8", "best_time": 0.006240000016987324, "best_triton_pos": 0} 2025-09-07T09:55:02.1725396Z AUTOTUNE mm(1000x4, 4x384) 2025-09-07T09:55:02.1725789Z strides: [1, 1000], [384, 1] 2025-09-07T09:55:02.1726043Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:02.1726812Z triton_mm_959 0.0062 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 2025-09-07T09:55:02.1727913Z triton_mm_953 0.0063 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=1, num_warps=2 2025-09-07T09:55:02.1728937Z triton_mm_958 0.0063 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:55:02.1729931Z triton_mm_954 0.0064 ms 98.0% 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 2025-09-07T09:55:02.1731105Z triton_mm_960 0.0064 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:02.1732087Z triton_mm_955 0.0064 ms 97.5% 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 2025-09-07T09:55:02.1733071Z triton_mm_957 0.0064 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:02.1734542Z triton_mm_956 0.0065 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:02.1735539Z triton_mm_964 0.0066 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:02.1736733Z triton_mm_965 0.0066 ms 95.1% 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 2025-09-07T09:55:02.1737474Z SingleProcess AUTOTUNE benchmarking takes 0.1760 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:55:02.5691466Z Autotune Choices Stats: 2025-09-07T09:55:02.5692583Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.00886400043964386, "best_triton_pos": 1, "best_triton_time": 0.009279999881982803, "best_triton_kernel": "triton_mm_1068", "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"} 2025-09-07T09:55:02.5970328Z AUTOTUNE mm(384x788, 788x384) 2025-09-07T09:55:02.5970605Z strides: [1, 384], [384, 1] 2025-09-07T09:55:02.5970848Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:02.5971091Z mm 0.0089 ms 100.0% 2025-09-07T09:55:02.5971649Z triton_mm_1068 0.0093 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:02.5972537Z triton_mm_1072 0.0095 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:02.5973395Z triton_mm_1076 0.0105 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:02.5974261Z triton_mm_1067 0.0106 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:02.5975111Z triton_mm_1066 0.0109 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:02.5975966Z triton_mm_1071 0.0113 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:02.5976819Z triton_mm_1075 0.0118 ms 74.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:02.5977685Z triton_mm_1074 0.0120 ms 73.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:02.5978533Z triton_mm_1078 0.0120 ms 73.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:02.5979268Z SingleProcess AUTOTUNE benchmarking takes 0.2304 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:55:03.6147668Z Autotune Choices Stats: 2025-09-07T09:55:03.6148935Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.008671999908983707, "best_triton_pos": 1, "best_triton_time": 0.009184000082314014, "best_triton_kernel": "triton_mm_940", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T09:55:03.6487466Z AUTOTUNE mm(4x1000, 1000x384) 2025-09-07T09:55:03.6487914Z strides: [1000, 1], [384, 1] 2025-09-07T09:55:03.6488950Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:03.6489399Z mm 0.0087 ms 100.0% 2025-09-07T09:55:03.6490756Z triton_mm_940 0.0092 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:55:03.6492797Z triton_mm_944 0.0098 ms 88.3% 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 2025-09-07T09:55:03.6494411Z triton_mm_948 0.0101 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:03.6496001Z triton_mm_938 0.0112 ms 77.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:03.6497480Z triton_mm_939 0.0112 ms 77.7% 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 2025-09-07T09:55:03.6498344Z triton_mm_952 0.0116 ms 75.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:03.6499218Z triton_mm_943 0.0121 ms 71.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:03.6500062Z triton_mm_950 0.0127 ms 68.4% 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 2025-09-07T09:55:03.6501039Z triton_mm_947 0.0129 ms 67.1% 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 2025-09-07T09:55:03.6501782Z SingleProcess AUTOTUNE benchmarking takes 0.2212 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:55:03.8638295Z Autotune Choices Stats: 2025-09-07T09:55:03.8640773Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010400000028312206, "best_triton_pos": 1, "best_triton_time": 0.010975999757647514, "best_triton_kernel": "triton_mm_1015", "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"} 2025-09-07T09:55:03.8870512Z AUTOTUNE mm(788x1536, 1536x384) 2025-09-07T09:55:03.8870773Z strides: [1536, 1], [384, 1] 2025-09-07T09:55:03.8871035Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:03.8871290Z mm 0.0104 ms 100.0% 2025-09-07T09:55:03.8871879Z triton_mm_1015 0.0110 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:03.8872887Z triton_mm_1019 0.0124 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:03.8873864Z triton_mm_1011 0.0146 ms 71.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:03.8874840Z triton_mm_1025 0.0149 ms 69.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:03.8875823Z triton_mm_1014 0.0154 ms 67.7% 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 2025-09-07T09:55:03.8876787Z triton_mm_1018 0.0163 ms 64.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:03.8877946Z triton_mm_1017 0.0173 ms 60.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:03.8878850Z triton_mm_1010 0.0179 ms 58.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:03.8879893Z triton_mm_1024 0.0179 ms 58.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:03.8880831Z SingleProcess AUTOTUNE benchmarking takes 0.2368 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:04.0763169Z Autotune Choices Stats: 2025-09-07T09:55:04.0764196Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1053", "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": 0.008063999935984612, "best_triton_pos": 0} 2025-09-07T09:55:04.1267553Z AUTOTUNE mm(788x384, 384x384) 2025-09-07T09:55:04.1267943Z strides: [384, 1], [384, 1] 2025-09-07T09:55:04.1268288Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:04.1269216Z triton_mm_1053 0.0081 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:04.1270083Z mm 0.0082 ms 98.4% 2025-09-07T09:55:04.1271324Z triton_mm_1052 0.0087 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:55:04.1272694Z triton_mm_1057 0.0088 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:04.1274071Z triton_mm_1056 0.0088 ms 91.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:04.1275426Z triton_mm_1055 0.0094 ms 86.0% 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 2025-09-07T09:55:04.1276779Z triton_mm_1059 0.0095 ms 85.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:04.1278142Z triton_mm_1063 0.0097 ms 83.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:04.1279504Z triton_mm_1062 0.0097 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:04.1280984Z triton_mm_1048 0.0097 ms 82.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:04.1282158Z SingleProcess AUTOTUNE benchmarking takes 0.2387 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:55:04.3438542Z Autotune Choices Stats: 2025-09-07T09:55:04.3440141Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010015999898314476, "best_triton_pos": 1, "best_triton_time": 0.01027199998497963, "best_triton_kernel": "triton_mm_1091", "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"} 2025-09-07T09:55:04.3990018Z AUTOTUNE mm(788x1152, 1152x384) 2025-09-07T09:55:04.3990514Z strides: [1152, 1], [384, 1] 2025-09-07T09:55:04.3991416Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:04.3991795Z mm 0.0100 ms 100.0% 2025-09-07T09:55:04.3992621Z triton_mm_1091 0.0103 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:04.3994262Z triton_mm_1095 0.0111 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:04.3995635Z triton_mm_1087 0.0130 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:04.3996985Z triton_mm_1090 0.0130 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 2025-09-07T09:55:04.3998341Z triton_mm_1101 0.0134 ms 74.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:04.3999704Z triton_mm_1094 0.0134 ms 74.7% 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 2025-09-07T09:55:04.4001238Z triton_mm_1093 0.0147 ms 68.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:04.4002604Z triton_mm_1097 0.0149 ms 67.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:55:04.4003951Z triton_mm_1086 0.0150 ms 66.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:04.4005126Z SingleProcess AUTOTUNE benchmarking takes 0.2716 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:55:09.0361669Z pass 2025-09-07T09:55:12.9556669Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:55:12.9557930Z import pynvml # type: ignore[import] 2025-09-07T09:55:15.4098016Z 2025-09-07T09:55:27.7476110Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:27.7476454Z loading model: 0it [00:12, ?it/s] 2025-09-07T09:55:27.7476758Z cuda train timm_vision_transformer_large 2025-09-07T09:55:27.7965247Z pass_due_to_skip 2025-09-07T09:55:29.5561564Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:55:29.5563820Z import pynvml # type: ignore[import] 2025-09-07T09:55:32.0596735Z 2025-09-07T09:55:35.3419098Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:55:35.3419450Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:55:35.3419746Z cuda train timm_vovnet 2025-09-07T09:55:49.0079940Z Autotune Choices Stats: 2025-09-07T09:55:49.0082208Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_3", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=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": 0.012575999833643436, "best_triton_pos": 0} 2025-09-07T09:55:49.0382159Z AUTOTUNE convolution(4x3x224x224, 64x3x3x3) 2025-09-07T09:55:49.0382753Z strides: [150528, 50176, 224, 1], [27, 9, 3, 1] 2025-09-07T09:55:49.0383396Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.0385418Z triton_convolution2d_3 0.0126 ms 100.0% 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 2025-09-07T09:55:49.0387877Z triton_convolution2d_5 0.0128 ms 98.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.0390006Z triton_convolution2d_1 0.0136 ms 92.7% 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 2025-09-07T09:55:49.0391689Z triton_convolution2d_0 0.0137 ms 91.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.0392897Z triton_convolution2d_4 0.0152 ms 82.7% 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=8 2025-09-07T09:55:49.0394116Z triton_convolution2d_2 0.0252 ms 50.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.0394865Z convolution 0.0252 ms 49.9% 2025-09-07T09:55:49.0395330Z SingleProcess AUTOTUNE benchmarking takes 0.1236 seconds and 0.0003 seconds precompiling for 7 choices 2025-09-07T09:55:49.2116440Z Autotune Choices Stats: 2025-09-07T09:55:49.2117523Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_9", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.035679999738931656, "best_triton_pos": 0} 2025-09-07T09:55:49.2404717Z AUTOTUNE convolution(4x64x112x112, 64x64x3x3) 2025-09-07T09:55:49.2405074Z strides: [802816, 12544, 112, 1], [576, 9, 3, 1] 2025-09-07T09:55:49.2405397Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.2406206Z triton_convolution2d_9 0.0357 ms 100.0% 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 2025-09-07T09:55:49.2407442Z triton_convolution2d_12 0.0406 ms 87.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.2408661Z triton_convolution2d_10 0.0412 ms 86.6% 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 2025-09-07T09:55:49.2409406Z convolution 0.0413 ms 86.3% 2025-09-07T09:55:49.2410440Z triton_convolution2d_7 0.0429 ms 83.2% 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 2025-09-07T09:55:49.2411577Z triton_convolution2d_11 0.0429 ms 83.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.2412700Z triton_convolution2d_6 0.0497 ms 71.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.2413836Z triton_convolution2d_8 0.1307 ms 27.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:49.2415021Z SingleProcess AUTOTUNE benchmarking takes 0.1478 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:49.4147756Z Autotune Choices Stats: 2025-09-07T09:55:49.4149569Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018688000738620758, "best_triton_pos": 1, "best_triton_time": 0.030592000111937523, "best_triton_kernel": "triton_convolution2d_59", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T09:55:49.4380005Z AUTOTUNE convolution(4x768x56x56, 256x768x1x1) 2025-09-07T09:55:49.4380478Z strides: [2408448, 3136, 56, 1], [768, 1, 1, 1] 2025-09-07T09:55:49.4380751Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.4381018Z convolution 0.0187 ms 100.0% 2025-09-07T09:55:49.4381672Z triton_convolution2d_59 0.0306 ms 61.1% 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 2025-09-07T09:55:49.4382771Z triton_convolution2d_58 0.0332 ms 56.3% 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 2025-09-07T09:55:49.4383936Z triton_convolution2d_60 0.0357 ms 52.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:49.4385004Z triton_convolution2d_61 0.0363 ms 51.5% 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 2025-09-07T09:55:49.4386071Z triton_convolution2d_55 0.0458 ms 40.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:49.4387128Z triton_convolution2d_56 0.0507 ms 36.9% 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 2025-09-07T09:55:49.4388195Z triton_convolution2d_57 0.0610 ms 30.7% 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 2025-09-07T09:55:49.4388863Z conv1x1_via_mm 0.1325 ms 14.1% 2025-09-07T09:55:49.4389272Z SingleProcess AUTOTUNE benchmarking takes 0.1669 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:55:49.8357541Z Autotune Choices Stats: 2025-09-07T09:55:49.8358926Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_16", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8", "best_time": 0.02687999978661537, "best_triton_pos": 0} 2025-09-07T09:55:49.9319101Z AUTOTUNE convolution(4x64x112x112, 128x64x3x3) 2025-09-07T09:55:49.9319516Z strides: [802816, 12544, 112, 1], [576, 9, 3, 1] 2025-09-07T09:55:49.9319870Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:49.9320979Z triton_convolution2d_16 0.0269 ms 100.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.9322472Z triton_convolution2d_19 0.0280 ms 96.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.9323920Z triton_convolution2d_17 0.0302 ms 88.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.9325757Z triton_convolution2d_18 0.0309 ms 86.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:49.9326860Z convolution 0.0328 ms 82.0% 2025-09-07T09:55:49.9327719Z triton_convolution2d_14 0.0361 ms 74.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.9329170Z triton_convolution2d_13 0.0368 ms 73.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:49.9330754Z triton_convolution2d_15 0.1362 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 2025-09-07T09:55:49.9331848Z SingleProcess AUTOTUNE benchmarking takes 0.2111 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:50.1070844Z Autotune Choices Stats: 2025-09-07T09:55:50.1072572Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03286400064826012, "best_triton_pos": 1, "best_triton_time": 0.043455999344587326, "best_triton_kernel": "triton_convolution2d_26", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:55:50.1276916Z AUTOTUNE convolution(4x128x56x56, 128x128x3x3) 2025-09-07T09:55:50.1277393Z strides: [401408, 3136, 56, 1], [1152, 9, 3, 1] 2025-09-07T09:55:50.1277766Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:50.1278092Z convolution 0.0329 ms 100.0% 2025-09-07T09:55:50.1278984Z triton_convolution2d_26 0.0435 ms 75.6% 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 2025-09-07T09:55:50.1280595Z triton_convolution2d_23 0.0497 ms 66.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:50.1282070Z triton_convolution2d_24 0.0518 ms 63.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:50.1283541Z triton_convolution2d_25 0.0544 ms 60.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:50.1285002Z triton_convolution2d_21 0.0626 ms 52.5% 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 2025-09-07T09:55:50.1286454Z triton_convolution2d_20 0.0698 ms 47.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:50.1287910Z triton_convolution2d_22 0.1428 ms 23.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:50.1289063Z SingleProcess AUTOTUNE benchmarking takes 0.1494 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:50.5135879Z Autotune Choices Stats: 2025-09-07T09:55:50.5137885Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014879999682307243, "best_triton_pos": 1, "best_triton_time": 0.03254399821162224, "best_triton_kernel": "triton_convolution2d_101", "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"} 2025-09-07T09:55:50.5746885Z AUTOTUNE convolution(4x1056x28x28, 512x1056x1x1) 2025-09-07T09:55:50.5747522Z strides: [827904, 784, 28, 1], [1056, 1, 1, 1] 2025-09-07T09:55:50.5747951Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:50.5748268Z convolution 0.0149 ms 100.0% 2025-09-07T09:55:50.5749136Z triton_convolution2d_101 0.0325 ms 45.7% 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 2025-09-07T09:55:50.5750857Z triton_convolution2d_100 0.0389 ms 38.2% 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 2025-09-07T09:55:50.5752334Z triton_convolution2d_103 0.0400 ms 37.2% 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 2025-09-07T09:55:50.5753823Z triton_convolution2d_102 0.0414 ms 35.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:50.5755300Z triton_convolution2d_97 0.0574 ms 25.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:50.5756753Z triton_convolution2d_98 0.0609 ms 24.4% 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 2025-09-07T09:55:50.5757643Z conv1x1_via_mm 0.0692 ms 21.5% 2025-09-07T09:55:50.5758519Z triton_convolution2d_99 0.0728 ms 20.4% 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 2025-09-07T09:55:50.5759668Z SingleProcess AUTOTUNE benchmarking takes 0.3993 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:55:50.9781400Z Autotune Choices Stats: 2025-09-07T09:55:50.9782843Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02393599972128868, "best_triton_pos": 2, "best_triton_time": 0.04230400174856186, "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"} 2025-09-07T09:55:51.0202430Z AUTOTUNE convolution(4x1472x14x14, 768x1472x1x1) 2025-09-07T09:55:51.0202835Z strides: [288512, 196, 14, 1], [1472, 1, 1, 1] 2025-09-07T09:55:51.0203178Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:51.0203501Z convolution 0.0239 ms 100.0% 2025-09-07T09:55:51.0203803Z conv1x1_via_mm 0.0384 ms 62.3% 2025-09-07T09:55:51.0204692Z triton_convolution2d_143 0.0423 ms 56.6% 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 2025-09-07T09:55:51.0206176Z triton_convolution2d_142 0.0508 ms 47.1% 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 2025-09-07T09:55:51.0208046Z triton_convolution2d_144 0.0523 ms 45.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:51.0209518Z triton_convolution2d_145 0.0529 ms 45.2% 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 2025-09-07T09:55:51.0211403Z triton_convolution2d_140 0.0668 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 2025-09-07T09:55:51.0212867Z triton_convolution2d_139 0.0755 ms 31.7% 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 2025-09-07T09:55:51.0214332Z triton_convolution2d_141 0.1083 ms 22.1% 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 2025-09-07T09:55:51.0215499Z SingleProcess AUTOTUNE benchmarking takes 0.2023 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:55:51.4460527Z Autotune Choices Stats: 2025-09-07T09:55:51.4462006Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.025407999753952026, "best_triton_pos": 2, "best_triton_time": 0.04838399961590767, "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"} 2025-09-07T09:55:51.5114336Z AUTOTUNE convolution(4x1728x14x14, 768x1728x1x1) 2025-09-07T09:55:51.5114708Z strides: [338688, 196, 14, 1], [1728, 1, 1, 1] 2025-09-07T09:55:51.5115032Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:51.5115332Z convolution 0.0254 ms 100.0% 2025-09-07T09:55:51.5115578Z conv1x1_via_mm 0.0426 ms 59.7% 2025-09-07T09:55:51.5116334Z triton_convolution2d_185 0.0484 ms 52.5% 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 2025-09-07T09:55:51.5117601Z triton_convolution2d_184 0.0581 ms 43.7% 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 2025-09-07T09:55:51.5118841Z triton_convolution2d_186 0.0595 ms 42.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:51.5120060Z triton_convolution2d_187 0.0607 ms 41.9% 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 2025-09-07T09:55:51.5121430Z triton_convolution2d_182 0.0767 ms 33.1% 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 2025-09-07T09:55:51.5122553Z triton_convolution2d_181 0.0884 ms 28.7% 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 2025-09-07T09:55:51.5123685Z triton_convolution2d_183 0.1242 ms 20.5% 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 2025-09-07T09:55:51.5124582Z SingleProcess AUTOTUNE benchmarking takes 0.2308 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:55:51.6875424Z Autotune Choices Stats: 2025-09-07T09:55:51.6877219Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03248000144958496, "best_triton_pos": 1, "best_triton_time": 0.07100799679756165, "best_triton_kernel": "triton_convolution2d_66", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:51.7152790Z AUTOTUNE convolution(4x256x28x28, 160x256x3x3) 2025-09-07T09:55:51.7153128Z strides: [200704, 784, 28, 1], [2304, 9, 3, 1] 2025-09-07T09:55:51.7153418Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:51.7153692Z convolution 0.0325 ms 100.0% 2025-09-07T09:55:51.7154427Z triton_convolution2d_66 0.0710 ms 45.7% 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 2025-09-07T09:55:51.7155665Z triton_convolution2d_65 0.0855 ms 38.0% 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 2025-09-07T09:55:51.7156890Z triton_convolution2d_68 0.0885 ms 36.7% 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 2025-09-07T09:55:51.7158113Z triton_convolution2d_67 0.0899 ms 36.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:51.7159324Z triton_convolution2d_63 0.1177 ms 27.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:51.7160964Z triton_convolution2d_62 0.1388 ms 23.4% 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 2025-09-07T09:55:51.7162179Z triton_convolution2d_64 0.2118 ms 15.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:51.7163077Z SingleProcess AUTOTUNE benchmarking takes 0.1922 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:52.1187274Z Autotune Choices Stats: 2025-09-07T09:55:52.1188735Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.029440000653266907, "best_triton_pos": 1, "best_triton_time": 0.045632001012563705, "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"} 2025-09-07T09:55:52.1279241Z AUTOTUNE convolution(4x160x28x28, 160x160x3x3) 2025-09-07T09:55:52.1279604Z strides: [125440, 784, 28, 1], [1440, 9, 3, 1] 2025-09-07T09:55:52.1279925Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:52.1280390Z convolution 0.0294 ms 100.0% 2025-09-07T09:55:52.1281218Z triton_convolution2d_73 0.0456 ms 64.5% 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 2025-09-07T09:55:52.1282568Z triton_convolution2d_75 0.0559 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 2025-09-07T09:55:52.1283896Z triton_convolution2d_72 0.0561 ms 52.5% 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 2025-09-07T09:55:52.1285643Z triton_convolution2d_74 0.0589 ms 50.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:52.1287241Z triton_convolution2d_70 0.0746 ms 39.5% 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 2025-09-07T09:55:52.1288560Z triton_convolution2d_69 0.0879 ms 33.5% 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 2025-09-07T09:55:52.1289881Z triton_convolution2d_71 0.1378 ms 21.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:52.1291140Z SingleProcess AUTOTUNE benchmarking takes 0.1435 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:52.3955937Z Autotune Choices Stats: 2025-09-07T09:55:52.3957448Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020576000213623047, "best_triton_pos": 2, "best_triton_time": 0.06499200314283371, "best_triton_kernel": "triton_convolution2d_226", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:55:52.4188843Z AUTOTUNE convolution(4x1888x7x7, 1024x1888x1x1) 2025-09-07T09:55:52.4189197Z strides: [92512, 49, 7, 1], [1888, 1, 1, 1] 2025-09-07T09:55:52.4189495Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:52.4189793Z convolution 0.0206 ms 100.0% 2025-09-07T09:55:52.4190072Z conv1x1_via_mm 0.0344 ms 59.9% 2025-09-07T09:55:52.4191341Z triton_convolution2d_226 0.0650 ms 31.7% 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 2025-09-07T09:55:52.4192613Z triton_convolution2d_227 0.0844 ms 24.4% 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 2025-09-07T09:55:52.4193827Z triton_convolution2d_229 0.0935 ms 22.0% 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 2025-09-07T09:55:52.4195065Z triton_convolution2d_225 0.0943 ms 21.8% 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 2025-09-07T09:55:52.4196289Z triton_convolution2d_223 0.0997 ms 20.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:52.4197506Z triton_convolution2d_224 0.1145 ms 18.0% 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 2025-09-07T09:55:52.4198730Z triton_convolution2d_228 0.1387 ms 14.8% 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=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:52.4199698Z SingleProcess AUTOTUNE benchmarking takes 0.2524 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:55:52.9092556Z Autotune Choices Stats: 2025-09-07T09:55:52.9094595Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.033440001308918, "best_triton_pos": 1, "best_triton_time": 0.1247360035777092, "best_triton_kernel": "triton_convolution2d_108", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:52.9623868Z AUTOTUNE convolution(4x512x14x14, 192x512x3x3) 2025-09-07T09:55:52.9624598Z strides: [100352, 196, 14, 1], [4608, 9, 3, 1] 2025-09-07T09:55:52.9624902Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:52.9625177Z convolution 0.0334 ms 100.0% 2025-09-07T09:55:52.9625878Z triton_convolution2d_108 0.1247 ms 26.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:52.9627043Z triton_convolution2d_107 0.1708 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 2025-09-07T09:55:52.9628211Z triton_convolution2d_110 0.1720 ms 19.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:52.9629345Z triton_convolution2d_109 0.1889 ms 17.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:52.9630647Z triton_convolution2d_105 0.2397 ms 14.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:52.9631893Z triton_convolution2d_104 0.3154 ms 10.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:52.9633126Z triton_convolution2d_106 0.3741 ms 8.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:52.9634098Z SingleProcess AUTOTUNE benchmarking takes 0.2834 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:53.3688783Z Autotune Choices Stats: 2025-09-07T09:55:53.3691296Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02566399984061718, "best_triton_pos": 1, "best_triton_time": 0.049855999648571014, "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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:53.4356002Z AUTOTUNE convolution(4x192x14x14, 192x192x3x3) 2025-09-07T09:55:53.4356365Z strides: [37632, 196, 14, 1], [1728, 9, 3, 1] 2025-09-07T09:55:53.4356660Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:53.4356942Z convolution 0.0257 ms 100.0% 2025-09-07T09:55:53.4357736Z triton_convolution2d_115 0.0499 ms 51.5% 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 2025-09-07T09:55:53.4358978Z triton_convolution2d_117 0.0676 ms 38.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:53.4360419Z triton_convolution2d_114 0.0680 ms 37.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:53.4362011Z triton_convolution2d_116 0.0744 ms 34.5% 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 2025-09-07T09:55:53.4363477Z triton_convolution2d_112 0.0945 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 2025-09-07T09:55:53.4364702Z triton_convolution2d_111 0.1156 ms 22.2% 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 2025-09-07T09:55:53.4365923Z triton_convolution2d_113 0.1510 ms 17.0% 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 2025-09-07T09:55:53.4366898Z SingleProcess AUTOTUNE benchmarking takes 0.2119 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:53.7338684Z Autotune Choices Stats: 2025-09-07T09:55:53.7339915Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.038047999143600464, "best_triton_pos": 1, "best_triton_time": 0.1865919977426529, "best_triton_kernel": "triton_convolution2d_150", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:53.9004911Z AUTOTUNE convolution(4x768x14x14, 192x768x3x3) 2025-09-07T09:55:53.9005489Z strides: [150528, 196, 14, 1], [6912, 9, 3, 1] 2025-09-07T09:55:53.9005977Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:53.9006432Z convolution 0.0380 ms 100.0% 2025-09-07T09:55:53.9007655Z triton_convolution2d_150 0.1866 ms 20.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:53.9009705Z triton_convolution2d_149 0.2556 ms 14.9% 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 2025-09-07T09:55:53.9012115Z triton_convolution2d_152 0.2560 ms 14.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:53.9013220Z triton_convolution2d_151 0.2815 ms 13.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:53.9014299Z triton_convolution2d_147 0.3572 ms 10.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:53.9015374Z triton_convolution2d_146 0.4463 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 2025-09-07T09:55:53.9016449Z triton_convolution2d_148 0.5731 ms 6.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:53.9017306Z SingleProcess AUTOTUNE benchmarking takes 0.4270 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:54.2034472Z Autotune Choices Stats: 2025-09-07T09:55:54.2035879Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03807999938726425, "best_triton_pos": 1, "best_triton_time": 0.1849920004606247, "best_triton_kernel": "triton_convolution2d_192", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:54.3760120Z AUTOTUNE convolution(4x768x7x7, 224x768x3x3) 2025-09-07T09:55:54.3760658Z strides: [37632, 49, 7, 1], [6912, 9, 3, 1] 2025-09-07T09:55:54.3760940Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:54.3761548Z convolution 0.0381 ms 100.0% 2025-09-07T09:55:54.3762478Z triton_convolution2d_192 0.1850 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 2025-09-07T09:55:54.3763771Z triton_convolution2d_194 0.2398 ms 15.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:54.3765030Z triton_convolution2d_191 0.2458 ms 15.5% 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 2025-09-07T09:55:54.3766315Z triton_convolution2d_190 0.2550 ms 14.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:54.3767555Z triton_convolution2d_193 0.2969 ms 12.8% 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 2025-09-07T09:55:54.3768792Z triton_convolution2d_189 0.3361 ms 11.3% 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 2025-09-07T09:55:54.3770035Z triton_convolution2d_188 0.5288 ms 7.2% 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 2025-09-07T09:55:54.3771285Z SingleProcess AUTOTUNE benchmarking takes 0.4268 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:54.7735512Z Autotune Choices Stats: 2025-09-07T09:55:54.7737806Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.026688000187277794, "best_triton_pos": 1, "best_triton_time": 0.05721599981188774, "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=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:54.8514793Z AUTOTUNE convolution(4x224x7x7, 224x224x3x3) 2025-09-07T09:55:54.8515093Z strides: [10976, 49, 7, 1], [2016, 9, 3, 1] 2025-09-07T09:55:54.8515398Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:54.8515676Z convolution 0.0267 ms 100.0% 2025-09-07T09:55:54.8516417Z triton_convolution2d_199 0.0572 ms 46.6% 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 2025-09-07T09:55:54.8517684Z triton_convolution2d_197 0.0602 ms 44.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:54.8518933Z triton_convolution2d_201 0.0756 ms 35.3% 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 2025-09-07T09:55:54.8520161Z triton_convolution2d_198 0.0774 ms 34.5% 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 2025-09-07T09:55:54.8521878Z triton_convolution2d_200 0.0937 ms 28.5% 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 2025-09-07T09:55:54.8523305Z triton_convolution2d_196 0.1056 ms 25.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:54.8524442Z triton_convolution2d_195 0.1595 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 2025-09-07T09:55:54.8525341Z SingleProcess AUTOTUNE benchmarking takes 0.2256 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:55.7197853Z Autotune Choices Stats: 2025-09-07T09:55:55.7199257Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.044224001467227936, "best_triton_pos": 1, "best_triton_time": 0.2553600072860718, "best_triton_kernel": "triton_convolution2d_234", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:55:55.8298996Z AUTOTUNE convolution(4x1024x7x7, 224x1024x3x3) 2025-09-07T09:55:55.8299550Z strides: [50176, 49, 7, 1], [9216, 9, 3, 1] 2025-09-07T09:55:55.8300024Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:55.8300913Z convolution 0.0442 ms 100.0% 2025-09-07T09:55:55.8302120Z triton_convolution2d_234 0.2554 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 2025-09-07T09:55:55.8303588Z triton_convolution2d_236 0.3129 ms 14.1% 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 2025-09-07T09:55:55.8304822Z triton_convolution2d_233 0.3298 ms 13.4% 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 2025-09-07T09:55:55.8306049Z triton_convolution2d_232 0.3347 ms 13.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:55:55.8307277Z triton_convolution2d_235 0.4020 ms 11.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:55:55.8308496Z triton_convolution2d_231 0.4393 ms 10.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:55:55.8309731Z triton_convolution2d_230 0.7978 ms 5.5% 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 2025-09-07T09:55:55.8310828Z SingleProcess AUTOTUNE benchmarking takes 0.9430 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:55:56.4454639Z Autotune Choices Stats: 2025-09-07T09:55:56.4456091Z {"num_choices": 9, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.025855999439954758, "best_triton_pos": 2, "best_triton_time": 0.0732479989528656, "best_triton_kernel": "triton_convolution2d_268", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T09:55:56.5562863Z AUTOTUNE convolution(4x2144x7x7, 1024x2144x1x1) 2025-09-07T09:55:56.5563250Z strides: [105056, 49, 7, 1], [2144, 1, 1, 1] 2025-09-07T09:55:56.5563543Z dtypes: torch.float16, torch.float16 2025-09-07T09:55:56.5563824Z convolution 0.0259 ms 100.0% 2025-09-07T09:55:56.5564075Z conv1x1_via_mm 0.0387 ms 66.9% 2025-09-07T09:55:56.5565276Z triton_convolution2d_268 0.0732 ms 35.3% 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 2025-09-07T09:55:56.5566543Z triton_convolution2d_269 0.0942 ms 27.5% 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 2025-09-07T09:55:56.5567777Z triton_convolution2d_271 0.1056 ms 24.5% 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 2025-09-07T09:55:56.5569012Z triton_convolution2d_265 0.1135 ms 22.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:56.5570683Z triton_convolution2d_267 0.1200 ms 21.5% 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 2025-09-07T09:55:56.5571979Z triton_convolution2d_266 0.1306 ms 19.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T09:55:56.5573149Z triton_convolution2d_270 0.1549 ms 16.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=1, STRIDE_W=1, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T09:55:56.5574050Z SingleProcess AUTOTUNE benchmarking takes 0.3047 seconds and 0.0002 seconds precompiling for 9 choices 2025-09-07T09:55:56.8062357Z Autotune Choices Stats: 2025-09-07T09:55:56.8063473Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_276", "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": 0.009119999594986439, "best_triton_pos": 0} 2025-09-07T09:55:57.0433687Z AUTOTUNE addmm(4x1000, 4x1024, 1024x1000) 2025-09-07T09:55:57.0433998Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T09:55:57.0434306Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:55:57.0435002Z triton_mm_276 0.0091 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:55:57.0436020Z triton_mm_280 0.0097 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:57.0436650Z bias_addmm 0.0100 ms 91.1% 2025-09-07T09:55:57.0437246Z triton_mm_284 0.0108 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:55:57.0438213Z triton_mm_288 0.0113 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:55:57.0439167Z triton_mm_275 0.0121 ms 75.6% 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 2025-09-07T09:55:57.0440119Z triton_mm_274 0.0125 ms 73.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:55:57.0441727Z triton_mm_279 0.0128 ms 71.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:55:57.0442926Z triton_mm_273 0.0130 ms 70.4% 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 2025-09-07T09:55:57.0443512Z addmm 0.0131 ms 69.5% 2025-09-07T09:55:57.0443942Z SingleProcess AUTOTUNE benchmarking takes 0.4860 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:56:08.2821315Z Autotune Choices Stats: 2025-09-07T09:56:08.2823105Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_312", "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=3, num_warps=8", "best_time": 0.006432000081986189, "best_triton_pos": 0} 2025-09-07T09:56:08.4200099Z AUTOTUNE mm(1000x4, 4x1024) 2025-09-07T09:56:08.4200520Z strides: [1, 1000], [1024, 1] 2025-09-07T09:56:08.4200782Z dtypes: torch.float16, torch.float16 2025-09-07T09:56:08.4201446Z triton_mm_312 0.0064 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 2025-09-07T09:56:08.4202433Z triton_mm_314 0.0065 ms 99.5% 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 2025-09-07T09:56:08.4203410Z triton_mm_311 0.0066 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:56:08.4204374Z triton_mm_313 0.0066 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:56:08.4205354Z triton_mm_318 0.0066 ms 97.1% 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 2025-09-07T09:56:08.4206316Z triton_mm_307 0.0067 ms 96.6% 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 2025-09-07T09:56:08.4207206Z triton_mm_308 0.0067 ms 96.6% 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 2025-09-07T09:56:08.4208098Z triton_mm_315 0.0067 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 2025-09-07T09:56:08.4208989Z triton_mm_310 0.0067 ms 96.2% 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 2025-09-07T09:56:08.4209885Z triton_mm_316 0.0067 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:56:08.4210820Z SingleProcess AUTOTUNE benchmarking takes 0.2977 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:56:09.1181011Z Autotune Choices Stats: 2025-09-07T09:56:09.1182348Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.009184000082314014, "best_triton_pos": 1, "best_triton_time": 0.009664000011980534, "best_triton_kernel": "triton_mm_297", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:56:09.1723690Z AUTOTUNE mm(4x1000, 1000x1024) 2025-09-07T09:56:09.1724499Z strides: [1000, 1], [1024, 1] 2025-09-07T09:56:09.1724756Z dtypes: torch.float16, torch.float16 2025-09-07T09:56:09.1725019Z mm 0.0092 ms 100.0% 2025-09-07T09:56:09.1725691Z triton_mm_297 0.0097 ms 95.0% 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 2025-09-07T09:56:09.1727220Z triton_mm_293 0.0097 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:56:09.1728291Z triton_mm_301 0.0103 ms 89.4% 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 2025-09-07T09:56:09.1729319Z triton_mm_291 0.0114 ms 80.6% 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 2025-09-07T09:56:09.1730532Z triton_mm_305 0.0116 ms 79.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:56:09.1731520Z triton_mm_292 0.0117 ms 78.4% 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 2025-09-07T09:56:09.1732509Z triton_mm_296 0.0118 ms 78.0% 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 2025-09-07T09:56:09.1733504Z triton_mm_303 0.0127 ms 72.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:56:09.1734480Z triton_mm_300 0.0130 ms 70.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:56:09.1735360Z SingleProcess AUTOTUNE benchmarking takes 0.2375 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:56:16.8141348Z pass 2025-09-07T09:56:20.8150022Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:56:20.8151478Z import pynvml # type: ignore[import] 2025-09-07T09:56:23.3429867Z 2025-09-07T09:56:27.1698229Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:56:27.1698593Z loading model: 0it [00:03, ?it/s] 2025-09-07T09:56:27.1698923Z cuda train torch_multimodal_clip 2025-09-07T09:56:54.7411397Z Autotune Choices Stats: 2025-09-07T09:56:54.7412756Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.016863999888300896, "best_triton_pos": 1, "best_triton_time": 0.020160000771284103, "best_triton_kernel": "triton_mm_991", "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"} 2025-09-07T09:56:54.9072135Z AUTOTUNE addmm(2464x2048, 2464x512, 512x2048) 2025-09-07T09:56:54.9072463Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T09:56:54.9072789Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:56:54.9073117Z bias_addmm 0.0169 ms 100.0% 2025-09-07T09:56:54.9073752Z triton_mm_991 0.0202 ms 83.7% 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 2025-09-07T09:56:54.9074737Z triton_mm_985 0.0207 ms 81.6% 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 2025-09-07T09:56:54.9075723Z triton_mm_990 0.0227 ms 74.3% 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 2025-09-07T09:56:54.9077147Z triton_mm_992 0.0241 ms 70.1% 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 2025-09-07T09:56:54.9078410Z triton_mm_984 0.0248 ms 68.1% 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 2025-09-07T09:56:54.9079373Z triton_mm_988 0.0248 ms 68.1% 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 2025-09-07T09:56:54.9080784Z triton_mm_986 0.0257 ms 65.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:56:54.9081698Z triton_mm_983 0.0257 ms 65.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:56:54.9082581Z triton_mm_981 0.0258 ms 65.5% 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 2025-09-07T09:56:54.9083354Z SingleProcess AUTOTUNE benchmarking takes 0.8906 seconds and 0.0005 seconds precompiling for 21 choices 2025-09-07T09:56:55.9483090Z Autotune Choices Stats: 2025-09-07T09:56:55.9484422Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.01104000024497509, "best_triton_pos": 1, "best_triton_time": 0.011807999573647976, "best_triton_kernel": "triton_mm_57", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:56:55.9546950Z AUTOTUNE addmm(200x3072, 200x768, 768x3072) 2025-09-07T09:56:55.9547298Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T09:56:55.9547621Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:56:55.9547955Z bias_addmm 0.0110 ms 100.0% 2025-09-07T09:56:55.9548600Z triton_mm_57 0.0118 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:56:55.9549736Z triton_mm_52 0.0129 ms 85.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:56:55.9551080Z triton_mm_63 0.0131 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:56:55.9552037Z triton_mm_56 0.0132 ms 83.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:56:55.9552993Z triton_mm_53 0.0134 ms 82.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:56:55.9553946Z triton_mm_62 0.0142 ms 77.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:56:55.9554898Z triton_mm_55 0.0144 ms 76.8% 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 2025-09-07T09:56:55.9555845Z triton_mm_59 0.0144 ms 76.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:56:55.9556448Z addmm 0.0150 ms 73.7% 2025-09-07T09:56:55.9556900Z SingleProcess AUTOTUNE benchmarking takes 0.2773 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T09:56:57.0880418Z Autotune Choices Stats: 2025-09-07T09:56:57.0882321Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.013088000006973743, "best_triton_pos": 1, "best_triton_time": 0.013504000380635262, "best_triton_kernel": "triton_mm_904", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:56:57.1389412Z AUTOTUNE mm(200x3072, 3072x768) 2025-09-07T09:56:57.1389739Z strides: [3072, 1], [1, 3072] 2025-09-07T09:56:57.1389986Z dtypes: torch.float16, torch.float16 2025-09-07T09:56:57.1390390Z mm 0.0131 ms 100.0% 2025-09-07T09:56:57.1390994Z triton_mm_904 0.0135 ms 96.9% 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 2025-09-07T09:56:57.1392022Z triton_mm_908 0.0147 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:56:57.1393001Z triton_mm_912 0.0168 ms 78.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:56:57.1393978Z triton_mm_918 0.0228 ms 57.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:56:57.1394942Z triton_mm_903 0.0242 ms 54.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:56:57.1395894Z triton_mm_902 0.0252 ms 51.8% 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 2025-09-07T09:56:57.1396849Z triton_mm_907 0.0264 ms 49.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:56:57.1397817Z triton_mm_911 0.0268 ms 48.9% 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 2025-09-07T09:56:57.1398781Z triton_mm_901 0.0270 ms 48.5% 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 2025-09-07T09:56:57.1399624Z SingleProcess AUTOTUNE benchmarking takes 0.4311 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:56:59.1610775Z Autotune Choices Stats: 2025-09-07T09:56:59.1611955Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "triton_convolution2d_4", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=4", "best_time": 0.3402239978313446, "best_triton_pos": 0} 2025-09-07T09:56:59.2559115Z AUTOTUNE convolution(4x3x224x224, 768x3x32x32) 2025-09-07T09:56:59.2559465Z strides: [150528, 50176, 224, 1], [3072, 1024, 32, 1] 2025-09-07T09:56:59.2559788Z dtypes: torch.float16, torch.float16 2025-09-07T09:56:59.2561997Z triton_convolution2d_4 0.3402 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:56:59.2562823Z convolution 0.3823 ms 89.0% 2025-09-07T09:56:59.2563585Z triton_convolution2d_6 0.5884 ms 57.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:56:59.2564835Z triton_convolution2d_3 0.6492 ms 52.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:56:59.2566653Z triton_convolution2d_1 0.6925 ms 49.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:56:59.2568145Z triton_convolution2d_2 0.8263 ms 41.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:56:59.2569397Z triton_convolution2d_5 0.8503 ms 40.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:56:59.2570804Z triton_convolution2d_0 1.2844 ms 26.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=32, KERNEL_W=32, PADDING_H=0, PADDING_W=0, STRIDE_H=32, STRIDE_W=32, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:56:59.2571716Z SingleProcess AUTOTUNE benchmarking takes 0.3911 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:56:59.5006629Z Autotune Choices Stats: 2025-09-07T09:56:59.5008094Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010111999697983265, "best_triton_pos": 1, "best_triton_time": 0.010816000401973724, "best_triton_kernel": "triton_mm_19", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:56:59.7017750Z AUTOTUNE mm(200x768, 768x2304) 2025-09-07T09:56:59.7018095Z strides: [768, 1], [1, 768] 2025-09-07T09:56:59.7018361Z dtypes: torch.float16, torch.float16 2025-09-07T09:56:59.7018630Z mm 0.0101 ms 100.0% 2025-09-07T09:56:59.7019266Z triton_mm_19 0.0108 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:56:59.7020432Z triton_mm_25 0.0121 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:56:59.7021408Z triton_mm_14 0.0122 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:56:59.7022357Z triton_mm_18 0.0123 ms 82.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:56:59.7023375Z triton_mm_15 0.0125 ms 81.0% 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 2025-09-07T09:56:59.7024328Z triton_mm_8 0.0133 ms 76.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:56:59.7025271Z triton_mm_21 0.0134 ms 75.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:56:59.7026224Z triton_mm_24 0.0135 ms 75.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:56:59.7027175Z triton_mm_17 0.0137 ms 74.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:56:59.7028007Z SingleProcess AUTOTUNE benchmarking takes 0.4448 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:56:59.9692734Z Autotune Choices Stats: 2025-09-07T09:56:59.9693723Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_30", "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": 0.00848000030964613, "best_triton_pos": 0} 2025-09-07T09:57:00.1829698Z AUTOTUNE mm(200x768, 768x768) 2025-09-07T09:57:00.1830530Z strides: [768, 1], [1, 768] 2025-09-07T09:57:00.1831420Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:00.1832101Z triton_mm_30 0.0085 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 2025-09-07T09:57:00.1833092Z triton_mm_34 0.0089 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 2025-09-07T09:57:00.1834057Z triton_mm_38 0.0098 ms 86.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:00.1835023Z triton_mm_29 0.0103 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:00.1835979Z triton_mm_28 0.0108 ms 78.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:00.1836916Z triton_mm_33 0.0109 ms 77.9% 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 2025-09-07T09:57:00.1837849Z triton_mm_27 0.0114 ms 74.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:00.1838795Z triton_mm_37 0.0114 ms 74.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:00.1839744Z triton_mm_44 0.0115 ms 73.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:00.1840842Z triton_mm_43 0.0124 ms 68.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:00.1841643Z SingleProcess AUTOTUNE benchmarking takes 0.4791 seconds and 0.0005 seconds precompiling for 20 choices 2025-09-07T09:57:00.4742803Z Autotune Choices Stats: 2025-09-07T09:57:00.4753160Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_923", "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": 0.007679999805986881, "best_triton_pos": 0} 2025-09-07T09:57:00.6556975Z AUTOTUNE mm(4x768, 768x512) 2025-09-07T09:57:00.6557290Z strides: [768, 1], [512, 1] 2025-09-07T09:57:00.6557520Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:00.6558333Z triton_mm_923 0.0077 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 2025-09-07T09:57:00.6559252Z mm 0.0085 ms 90.2% 2025-09-07T09:57:00.6560041Z triton_mm_927 0.0085 ms 90.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:00.6561932Z triton_mm_935 0.0097 ms 79.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:00.6563319Z triton_mm_922 0.0098 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:57:00.6565200Z triton_mm_921 0.0099 ms 77.9% 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 2025-09-07T09:57:00.6566696Z triton_mm_931 0.0101 ms 76.2% 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 2025-09-07T09:57:00.6567548Z triton_mm_926 0.0102 ms 75.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:00.6568546Z triton_mm_920 0.0109 ms 70.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:57:00.6569348Z triton_mm_933 0.0109 ms 70.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:00.6570059Z SingleProcess AUTOTUNE benchmarking takes 0.3975 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:57:00.9096100Z Autotune Choices Stats: 2025-09-07T09:57:00.9098120Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01369599997997284, "best_triton_pos": 1, "best_triton_time": 0.014336000196635723, "best_triton_kernel": "triton_mm_953", "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"} 2025-09-07T09:57:00.9457942Z AUTOTUNE mm(2464x512, 512x1536) 2025-09-07T09:57:00.9458396Z strides: [512, 1], [1, 512] 2025-09-07T09:57:00.9458813Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:00.9459273Z mm 0.0137 ms 100.0% 2025-09-07T09:57:00.9460525Z triton_mm_953 0.0143 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:00.9462163Z triton_mm_952 0.0158 ms 86.6% 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 2025-09-07T09:57:00.9463886Z triton_mm_954 0.0168 ms 81.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:00.9465434Z triton_mm_947 0.0170 ms 80.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:00.9466956Z triton_mm_945 0.0176 ms 78.0% 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 2025-09-07T09:57:00.9468527Z triton_mm_949 0.0182 ms 75.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:00.9470065Z triton_mm_950 0.0193 ms 70.9% 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 2025-09-07T09:57:00.9471740Z triton_mm_946 0.0194 ms 70.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:00.9472710Z triton_mm_943 0.0195 ms 70.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:00.9473548Z SingleProcess AUTOTUNE benchmarking takes 0.2894 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T09:57:01.2009833Z Autotune Choices Stats: 2025-09-07T09:57:01.2012139Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011136000044643879, "best_triton_pos": 1, "best_triton_time": 0.011264000087976456, "best_triton_kernel": "triton_mm_966", "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"} 2025-09-07T09:57:01.3366104Z AUTOTUNE mm(2464x512, 512x512) 2025-09-07T09:57:01.3366401Z strides: [512, 1], [1, 512] 2025-09-07T09:57:01.3366677Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:01.3366921Z mm 0.0111 ms 100.0% 2025-09-07T09:57:01.3367453Z triton_mm_966 0.0113 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:01.3368329Z triton_mm_973 0.0114 ms 97.5% 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 2025-09-07T09:57:01.3369193Z triton_mm_962 0.0115 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:01.3370040Z triton_mm_972 0.0116 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:01.3371328Z triton_mm_965 0.0120 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:01.3372113Z triton_mm_969 0.0121 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 2025-09-07T09:57:01.3372883Z triton_mm_967 0.0128 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:01.3373664Z triton_mm_968 0.0134 ms 83.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:01.3374437Z triton_mm_964 0.0136 ms 82.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:01.3375119Z SingleProcess AUTOTUNE benchmarking takes 0.3890 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:01.6002716Z Autotune Choices Stats: 2025-09-07T09:57:01.6004028Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.015231999568641186, "best_triton_pos": 1, "best_triton_time": 0.01894400082528591, "best_triton_kernel": "triton_mm_1011", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T09:57:01.8104892Z AUTOTUNE mm(2464x2048, 2048x512) 2025-09-07T09:57:01.8105202Z strides: [2048, 1], [1, 2048] 2025-09-07T09:57:01.8105442Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:01.8105693Z mm 0.0152 ms 100.0% 2025-09-07T09:57:01.8106285Z triton_mm_1011 0.0189 ms 80.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:01.8107214Z triton_mm_1004 0.0224 ms 67.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:01.8108127Z triton_mm_1005 0.0235 ms 64.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:01.8109032Z triton_mm_1010 0.0236 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:01.8110793Z triton_mm_1000 0.0236 ms 64.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:01.8112003Z triton_mm_1001 0.0263 ms 57.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:01.8112991Z triton_mm_1003 0.0264 ms 57.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:01.8113975Z triton_mm_1007 0.0269 ms 56.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:01.8114955Z triton_mm_1002 0.0326 ms 46.7% 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 2025-09-07T09:57:01.8115809Z SingleProcess AUTOTUNE benchmarking takes 0.4714 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T09:57:02.1230626Z Autotune Choices Stats: 2025-09-07T09:57:02.1231940Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_1852", "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=5, num_warps=4", "best_time": 0.007648000027984381, "best_triton_pos": 0} 2025-09-07T09:57:02.8285385Z AUTOTUNE mm(32x512, 512x512) 2025-09-07T09:57:02.8285846Z strides: [512, 1], [1, 512] 2025-09-07T09:57:02.8286257Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:02.8287344Z triton_mm_1852 0.0076 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=5, num_warps=4 2025-09-07T09:57:02.8288979Z triton_mm_1856 0.0079 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:02.8289969Z mm 0.0080 ms 95.6% 2025-09-07T09:57:02.8291302Z triton_mm_1860 0.0086 ms 88.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:02.8292398Z triton_mm_1851 0.0088 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:02.8293297Z triton_mm_1850 0.0092 ms 83.6% 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 2025-09-07T09:57:02.8294194Z triton_mm_1855 0.0092 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:02.8295092Z triton_mm_1849 0.0092 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:02.8296006Z triton_mm_1864 0.0094 ms 81.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:02.8296915Z triton_mm_1859 0.0098 ms 78.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:02.8297702Z SingleProcess AUTOTUNE benchmarking takes 0.9223 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:57:26.8203209Z Autotune Choices Stats: 2025-09-07T09:57:26.8205232Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.016416000202298164, "best_triton_pos": 1, "best_triton_time": 0.01664000004529953, "best_triton_kernel": "triton_mm_1915", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:57:27.0107943Z AUTOTUNE mm(2464x512, 512x2048) 2025-09-07T09:57:27.0108731Z strides: [512, 1], [2048, 1] 2025-09-07T09:57:27.0109010Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:27.0109280Z mm 0.0164 ms 100.0% 2025-09-07T09:57:27.0109907Z triton_mm_1915 0.0166 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.0111120Z triton_mm_1908 0.0175 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.0112117Z triton_mm_1916 0.0187 ms 87.7% 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 2025-09-07T09:57:27.0113100Z triton_mm_1910 0.0191 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.0114092Z triton_mm_1912 0.0196 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.0115064Z triton_mm_1909 0.0196 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:27.0116035Z triton_mm_1917 0.0207 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:27.0117010Z triton_mm_1913 0.0240 ms 68.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:27.0117986Z triton_mm_1906 0.0241 ms 68.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:27.0118823Z SingleProcess AUTOTUNE benchmarking takes 0.4237 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T09:57:27.7417381Z Autotune Choices Stats: 2025-09-07T09:57:27.7418702Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010048000141978264, "best_triton_pos": 1, "best_triton_time": 0.010400000028312206, "best_triton_kernel": "triton_mm_3791", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:57:27.7837220Z AUTOTUNE mm(768x200, 200x3072) 2025-09-07T09:57:27.7837468Z strides: [1, 768], [3072, 1] 2025-09-07T09:57:27.7837719Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:27.7838025Z mm 0.0100 ms 100.0% 2025-09-07T09:57:27.7838786Z triton_mm_3791 0.0104 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.7839881Z triton_mm_3784 0.0105 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.7841059Z triton_mm_3788 0.0107 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:27.7842067Z triton_mm_3786 0.0107 ms 93.7% 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 2025-09-07T09:57:27.7843625Z triton_mm_3789 0.0107 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:27.7844850Z triton_mm_3785 0.0108 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:27.7845850Z triton_mm_3792 0.0113 ms 89.0% 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 2025-09-07T09:57:27.7846840Z triton_mm_3781 0.0116 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:27.7847835Z triton_mm_3782 0.0118 ms 85.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:27.7848718Z SingleProcess AUTOTUNE benchmarking takes 0.2669 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:28.1708813Z Autotune Choices Stats: 2025-09-07T09:57:28.1710086Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009855999611318111, "best_triton_pos": 1, "best_triton_time": 0.010239999741315842, "best_triton_kernel": "triton_mm_3822", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:57:28.2129638Z AUTOTUNE mm(3072x200, 200x768) 2025-09-07T09:57:28.2129930Z strides: [1, 3072], [768, 1] 2025-09-07T09:57:28.2130385Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:28.2130661Z mm 0.0099 ms 100.0% 2025-09-07T09:57:28.2131299Z triton_mm_3822 0.0102 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.2132289Z triton_mm_3826 0.0104 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.2133277Z triton_mm_3823 0.0105 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:28.2134240Z triton_mm_3824 0.0106 ms 93.3% 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 2025-09-07T09:57:28.2135212Z triton_mm_3829 0.0106 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.2136178Z triton_mm_3827 0.0107 ms 91.9% 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 2025-09-07T09:57:28.2137150Z triton_mm_3830 0.0114 ms 86.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.2138168Z triton_mm_3819 0.0116 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:28.2139114Z triton_mm_3820 0.0118 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:28.2139906Z SingleProcess AUTOTUNE benchmarking takes 0.2391 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:28.6876822Z Autotune Choices Stats: 2025-09-07T09:57:28.6877869Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_3881", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.009279999881982803, "best_triton_pos": 0} 2025-09-07T09:57:28.7814502Z AUTOTUNE mm(2304x200, 200x768) 2025-09-07T09:57:28.7815407Z strides: [1, 2304], [768, 1] 2025-09-07T09:57:28.7815707Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:28.7816414Z triton_mm_3881 0.0093 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 2025-09-07T09:57:28.7817470Z triton_mm_3879 0.0093 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.7818516Z triton_mm_3880 0.0093 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:28.7819384Z triton_mm_3884 0.0095 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:28.7820549Z triton_mm_3883 0.0095 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.7821119Z mm 0.0096 ms 97.0% 2025-09-07T09:57:28.7821629Z triton_mm_3886 0.0097 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.7822494Z triton_mm_3888 0.0097 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:28.7823451Z triton_mm_3887 0.0097 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:28.7824305Z triton_mm_3877 0.0105 ms 88.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:28.7825047Z SingleProcess AUTOTUNE benchmarking takes 0.2892 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:29.3413032Z Autotune Choices Stats: 2025-09-07T09:57:29.3414232Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.015744000673294067, "best_triton_pos": 1, "best_triton_time": 0.01849599927663803, "best_triton_kernel": "triton_mm_1930", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:57:29.4655755Z AUTOTUNE mm(512x2464, 2464x2048) 2025-09-07T09:57:29.4656044Z strides: [1, 512], [2048, 1] 2025-09-07T09:57:29.4656315Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:29.4656610Z mm 0.0157 ms 100.0% 2025-09-07T09:57:29.4657234Z triton_mm_1930 0.0185 ms 85.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:29.4658261Z triton_mm_1926 0.0229 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:29.4659291Z triton_mm_1936 0.0232 ms 67.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:29.4661939Z triton_mm_1929 0.0251 ms 62.8% 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 2025-09-07T09:57:29.4663590Z triton_mm_1925 0.0252 ms 62.4% 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 2025-09-07T09:57:29.4667559Z triton_mm_1932 0.0267 ms 59.0% 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 2025-09-07T09:57:29.4668599Z triton_mm_1935 0.0270 ms 58.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:29.4669456Z triton_mm_1928 0.0274 ms 57.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:29.4670457Z triton_mm_1931 0.0344 ms 45.8% 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 2025-09-07T09:57:29.4671215Z SingleProcess AUTOTUNE benchmarking takes 0.3736 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:29.7592987Z Autotune Choices Stats: 2025-09-07T09:57:29.7594350Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.016095999628305435, "best_triton_pos": 1, "best_triton_time": 0.01788800023496151, "best_triton_kernel": "triton_mm_1968", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:57:29.8151017Z AUTOTUNE mm(2048x2464, 2464x512) 2025-09-07T09:57:29.8151298Z strides: [1, 2048], [512, 1] 2025-09-07T09:57:29.8151565Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:29.8151839Z mm 0.0161 ms 100.0% 2025-09-07T09:57:29.8152496Z triton_mm_1968 0.0179 ms 90.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:29.8153573Z triton_mm_1964 0.0224 ms 71.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:29.8154650Z triton_mm_1974 0.0234 ms 68.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:29.8155704Z triton_mm_1963 0.0249 ms 64.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:29.8156752Z triton_mm_1967 0.0249 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 2025-09-07T09:57:29.8157811Z triton_mm_1973 0.0266 ms 60.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:29.8158865Z triton_mm_1966 0.0267 ms 60.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:29.8159912Z triton_mm_1970 0.0273 ms 59.0% 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 2025-09-07T09:57:29.8161316Z triton_mm_1965 0.0337 ms 47.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:29.8162243Z SingleProcess AUTOTUNE benchmarking takes 0.3028 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:30.3383772Z Autotune Choices Stats: 2025-09-07T09:57:30.3385104Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.014655999839305878, "best_triton_pos": 1, "best_triton_time": 0.01727999933063984, "best_triton_kernel": "triton_mm_2044", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:57:30.5386580Z AUTOTUNE mm(1536x2464, 2464x512) 2025-09-07T09:57:30.5386928Z strides: [1, 1536], [512, 1] 2025-09-07T09:57:30.5387197Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:30.5387477Z mm 0.0147 ms 100.0% 2025-09-07T09:57:30.5388124Z triton_mm_2044 0.0173 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:30.5389299Z triton_mm_2040 0.0218 ms 67.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:30.5390457Z triton_mm_2050 0.0230 ms 63.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:30.5391452Z triton_mm_2043 0.0235 ms 62.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:30.5392434Z triton_mm_2039 0.0236 ms 62.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:30.5393406Z triton_mm_2042 0.0256 ms 57.2% 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 2025-09-07T09:57:30.5394398Z triton_mm_2046 0.0259 ms 56.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:30.5395387Z triton_mm_2049 0.0261 ms 56.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:30.5396391Z triton_mm_2036 0.0285 ms 51.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:30.5397239Z SingleProcess AUTOTUNE benchmarking takes 0.4425 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:31.0583475Z Autotune Choices Stats: 2025-09-07T09:57:31.0584766Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010784000158309937, "best_triton_pos": 1, "best_triton_time": 0.010944000445306301, "best_triton_kernel": "triton_mm_3768", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T09:57:31.2577807Z AUTOTUNE mm(200x768, 768x3072) 2025-09-07T09:57:31.2578105Z strides: [768, 1], [3072, 1] 2025-09-07T09:57:31.2578373Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:31.2578647Z mm 0.0108 ms 100.0% 2025-09-07T09:57:31.2579306Z triton_mm_3768 0.0109 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:31.2580481Z triton_mm_3774 0.0120 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:31.2581480Z triton_mm_3767 0.0122 ms 88.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:31.2582821Z triton_mm_3763 0.0124 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:31.2583916Z triton_mm_3766 0.0129 ms 83.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:31.2585321Z triton_mm_3770 0.0130 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:31.2586295Z triton_mm_3764 0.0132 ms 82.0% 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 2025-09-07T09:57:31.2587283Z triton_mm_3773 0.0132 ms 82.0% 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 2025-09-07T09:57:31.2588271Z triton_mm_3765 0.0152 ms 71.1% 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 2025-09-07T09:57:31.2589194Z SingleProcess AUTOTUNE benchmarking takes 0.4017 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:31.9414475Z Autotune Choices Stats: 2025-09-07T09:57:31.9415763Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.008224000222980976, "best_triton_pos": 1, "best_triton_time": 0.008224000222980976, "best_triton_kernel": "triton_mm_3862", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T09:57:31.9558500Z AUTOTUNE mm(768x200, 200x768) 2025-09-07T09:57:31.9558782Z strides: [1, 768], [768, 1] 2025-09-07T09:57:31.9559030Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:31.9559372Z mm 0.0082 ms 100.0% 2025-09-07T09:57:31.9560119Z triton_mm_3862 0.0082 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 2025-09-07T09:57:31.9561496Z triton_mm_3863 0.0083 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:31.9562504Z triton_mm_3861 0.0084 ms 98.5% 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 2025-09-07T09:57:31.9563508Z triton_mm_3858 0.0086 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:31.9564489Z triton_mm_3865 0.0087 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:31.9565470Z triton_mm_3860 0.0088 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:31.9566436Z triton_mm_3864 0.0093 ms 88.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:31.9567419Z triton_mm_3868 0.0094 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:31.9568416Z triton_mm_3869 0.0094 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:31.9569313Z SingleProcess AUTOTUNE benchmarking takes 0.2043 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:32.2739849Z Autotune Choices Stats: 2025-09-07T09:57:32.2741135Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_3729", "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=3, num_warps=8", "best_time": 0.006335999816656113, "best_triton_pos": 0} 2025-09-07T09:57:32.3121442Z AUTOTUNE mm(768x4, 4x512) 2025-09-07T09:57:32.3121711Z strides: [1, 768], [512, 1] 2025-09-07T09:57:32.3121976Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:32.3122658Z triton_mm_3729 0.0063 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 2025-09-07T09:57:32.3123707Z triton_mm_3728 0.0064 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:32.3124736Z triton_mm_3730 0.0064 ms 99.5% 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 2025-09-07T09:57:32.3125727Z triton_mm_3725 0.0064 ms 98.5% 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 2025-09-07T09:57:32.3126746Z triton_mm_3727 0.0064 ms 98.5% 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 2025-09-07T09:57:32.3127731Z triton_mm_3724 0.0065 ms 98.0% 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 2025-09-07T09:57:32.3128738Z triton_mm_3723 0.0065 ms 97.5% 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 2025-09-07T09:57:32.3129785Z triton_mm_3726 0.0065 ms 97.1% 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 2025-09-07T09:57:32.3130860Z triton_mm_3731 0.0065 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:32.3131766Z triton_mm_3732 0.0065 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:32.3132555Z SingleProcess AUTOTUNE benchmarking takes 0.1938 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:57:32.8818014Z Autotune Choices Stats: 2025-09-07T09:57:32.8819068Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_1868", "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": 0.0063680000603199005, "best_triton_pos": 0} 2025-09-07T09:57:33.0424653Z AUTOTUNE mm(512x32, 32x512) 2025-09-07T09:57:33.0424937Z strides: [1, 512], [512, 1] 2025-09-07T09:57:33.0425185Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:33.0425878Z triton_mm_1868 0.0064 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 2025-09-07T09:57:33.0426922Z triton_mm_1871 0.0065 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:33.0427892Z triton_mm_1867 0.0065 ms 98.0% 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 2025-09-07T09:57:33.0429181Z triton_mm_1873 0.0065 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:33.0430582Z triton_mm_1866 0.0065 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:33.0431891Z triton_mm_1872 0.0065 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:33.0432855Z triton_mm_1869 0.0066 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:33.0433816Z triton_mm_1876 0.0066 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:33.0434795Z triton_mm_1874 0.0067 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:33.0435769Z triton_mm_1878 0.0067 ms 95.2% 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 2025-09-07T09:57:33.0436617Z SingleProcess AUTOTUNE benchmarking takes 0.5404 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:57:33.4712814Z Autotune Choices Stats: 2025-09-07T09:57:33.4714052Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01235199999064207, "best_triton_pos": 1, "best_triton_time": 0.013151999562978745, "best_triton_kernel": "triton_mm_2002", "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"} 2025-09-07T09:57:33.5165093Z AUTOTUNE mm(512x2464, 2464x512) 2025-09-07T09:57:33.5165379Z strides: [1, 512], [512, 1] 2025-09-07T09:57:33.5165631Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:33.5165902Z mm 0.0124 ms 100.0% 2025-09-07T09:57:33.5166515Z triton_mm_2002 0.0132 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:33.5167566Z triton_mm_1998 0.0137 ms 90.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:33.5168565Z triton_mm_2006 0.0163 ms 75.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:33.5169578Z triton_mm_1997 0.0203 ms 61.0% 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 2025-09-07T09:57:33.5170825Z triton_mm_1996 0.0203 ms 60.8% 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 2025-09-07T09:57:33.5171742Z triton_mm_2012 0.0211 ms 58.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:33.5172655Z triton_mm_2001 0.0220 ms 56.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:33.5173552Z triton_mm_2005 0.0222 ms 55.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:33.5174453Z triton_mm_2004 0.0245 ms 50.5% 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 2025-09-07T09:57:33.5175433Z SingleProcess AUTOTUNE benchmarking takes 0.2797 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:33.8213581Z Autotune Choices Stats: 2025-09-07T09:57:33.8215003Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_1886", "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=5, num_warps=4", "best_time": 0.007840000092983246, "best_triton_pos": 0} 2025-09-07T09:57:33.8817248Z AUTOTUNE mm(32x512, 512x512) 2025-09-07T09:57:33.8817528Z strides: [512, 1], [512, 1] 2025-09-07T09:57:33.8817792Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:33.8818472Z triton_mm_1886 0.0078 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=5, num_warps=4 2025-09-07T09:57:33.8819129Z mm 0.0080 ms 98.4% 2025-09-07T09:57:33.8819735Z triton_mm_1890 0.0083 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:33.8820955Z triton_mm_1885 0.0088 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:33.8821807Z triton_mm_1894 0.0088 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:33.8822643Z triton_mm_1884 0.0091 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:33.8823567Z triton_mm_1898 0.0092 ms 85.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:33.8824407Z triton_mm_1889 0.0092 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:33.8825243Z triton_mm_1893 0.0096 ms 81.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:33.8826085Z triton_mm_1883 0.0097 ms 80.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:33.8826830Z SingleProcess AUTOTUNE benchmarking takes 0.2325 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:57:35.1345999Z Autotune Choices Stats: 2025-09-07T09:57:35.1347294Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.014976000413298607, "best_triton_pos": 1, "best_triton_time": 0.01942400075495243, "best_triton_kernel": "triton_mm_1955", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T09:57:35.2383986Z AUTOTUNE mm(2464x2048, 2048x512) 2025-09-07T09:57:35.2384323Z strides: [2048, 1], [512, 1] 2025-09-07T09:57:35.2384605Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:35.2384875Z mm 0.0150 ms 100.0% 2025-09-07T09:57:35.2385509Z triton_mm_1955 0.0194 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:35.2386535Z triton_mm_1948 0.0219 ms 68.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:35.2387507Z triton_mm_1944 0.0232 ms 64.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:35.2388853Z triton_mm_1954 0.0233 ms 64.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:35.2391250Z triton_mm_1949 0.0236 ms 63.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:35.2392284Z triton_mm_1945 0.0251 ms 59.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:35.2393259Z triton_mm_1947 0.0260 ms 57.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:35.2394219Z triton_mm_1951 0.0265 ms 56.6% 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 2025-09-07T09:57:35.2395174Z triton_mm_1946 0.0312 ms 48.0% 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 2025-09-07T09:57:35.2396016Z SingleProcess AUTOTUNE benchmarking takes 0.3466 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:35.4369743Z Autotune Choices Stats: 2025-09-07T09:57:35.4371217Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009952000342309475, "best_triton_pos": 1, "best_triton_time": 0.011071999557316303, "best_triton_kernel": "triton_mm_1993", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T09:57:35.4596005Z AUTOTUNE mm(2464x512, 512x512) 2025-09-07T09:57:35.4596256Z strides: [512, 1], [512, 1] 2025-09-07T09:57:35.4596500Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:35.4596753Z mm 0.0100 ms 100.0% 2025-09-07T09:57:35.4597356Z triton_mm_1993 0.0111 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:35.4598363Z triton_mm_1986 0.0111 ms 89.6% 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 2025-09-07T09:57:35.4599349Z triton_mm_1992 0.0114 ms 87.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:35.4600599Z triton_mm_1982 0.0115 ms 86.9% 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 2025-09-07T09:57:35.4601570Z triton_mm_1985 0.0116 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:35.4602486Z triton_mm_1989 0.0117 ms 85.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:35.4603383Z triton_mm_1984 0.0127 ms 78.5% 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 2025-09-07T09:57:35.4604289Z triton_mm_1988 0.0130 ms 76.8% 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 2025-09-07T09:57:35.4605192Z triton_mm_1987 0.0132 ms 75.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:35.4606272Z SingleProcess AUTOTUNE benchmarking takes 0.2200 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:35.6863401Z Autotune Choices Stats: 2025-09-07T09:57:35.6865001Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.013279999606311321, "best_triton_pos": 1, "best_triton_time": 0.015776000916957855, "best_triton_kernel": "triton_mm_2031", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T09:57:35.7272639Z AUTOTUNE mm(2464x1536, 1536x512) 2025-09-07T09:57:35.7272893Z strides: [1536, 1], [512, 1] 2025-09-07T09:57:35.7273165Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:35.7273428Z mm 0.0133 ms 100.0% 2025-09-07T09:57:35.7274018Z triton_mm_2031 0.0158 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:35.7275019Z triton_mm_2024 0.0182 ms 73.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:35.7276008Z triton_mm_2020 0.0182 ms 72.9% 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 2025-09-07T09:57:35.7276989Z triton_mm_2030 0.0192 ms 69.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:35.7277973Z triton_mm_2023 0.0199 ms 66.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:57:35.7278954Z triton_mm_2025 0.0199 ms 66.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:35.7279941Z triton_mm_2027 0.0207 ms 64.1% 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 2025-09-07T09:57:35.7281251Z triton_mm_2021 0.0212 ms 62.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:35.7282192Z triton_mm_2022 0.0250 ms 53.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:35.7282975Z SingleProcess AUTOTUNE benchmarking takes 0.2664 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:35.9959866Z Autotune Choices Stats: 2025-09-07T09:57:35.9961322Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_3743", "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": 0.007455999962985516, "best_triton_pos": 0} 2025-09-07T09:57:36.0114086Z AUTOTUNE mm(4x512, 512x768) 2025-09-07T09:57:36.0114358Z strides: [512, 1], [1, 512] 2025-09-07T09:57:36.0114609Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:36.0115270Z triton_mm_3743 0.0075 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 2025-09-07T09:57:36.0116263Z triton_mm_3747 0.0078 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:36.0116875Z mm 0.0078 ms 95.1% 2025-09-07T09:57:36.0117446Z triton_mm_3751 0.0086 ms 86.9% 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 2025-09-07T09:57:36.0118639Z triton_mm_3742 0.0086 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:57:36.0119905Z triton_mm_3755 0.0086 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.0121103Z triton_mm_3741 0.0088 ms 84.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:36.0122035Z triton_mm_3746 0.0089 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:36.0122935Z triton_mm_3740 0.0091 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:57:36.0123837Z triton_mm_3750 0.0093 ms 80.3% 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 2025-09-07T09:57:36.0124632Z SingleProcess AUTOTUNE benchmarking takes 0.1862 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:57:36.2596588Z Autotune Choices Stats: 2025-09-07T09:57:36.2597817Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.012959999963641167, "best_triton_pos": 1, "best_triton_time": 0.013088000006973743, "best_triton_kernel": "triton_mm_3798", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:57:36.3067767Z AUTOTUNE mm(200x3072, 3072x768) 2025-09-07T09:57:36.3068065Z strides: [3072, 1], [768, 1] 2025-09-07T09:57:36.3068335Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:36.3068616Z mm 0.0130 ms 100.0% 2025-09-07T09:57:36.3069237Z triton_mm_3798 0.0131 ms 99.0% 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 2025-09-07T09:57:36.3070696Z triton_mm_3802 0.0137 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:36.3071699Z triton_mm_3806 0.0165 ms 78.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:36.3072693Z triton_mm_3796 0.0236 ms 54.9% 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 2025-09-07T09:57:36.3073673Z triton_mm_3812 0.0238 ms 54.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.3074645Z triton_mm_3797 0.0239 ms 54.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.3075612Z triton_mm_3801 0.0252 ms 51.5% 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 2025-09-07T09:57:36.3076576Z triton_mm_3805 0.0252 ms 51.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:36.3077548Z triton_mm_3795 0.0281 ms 46.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:36.3078610Z SingleProcess AUTOTUNE benchmarking takes 0.2940 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:36.5051461Z Autotune Choices Stats: 2025-09-07T09:57:36.5052781Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_3836", "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": 0.008608000352978706, "best_triton_pos": 0} 2025-09-07T09:57:36.5184001Z AUTOTUNE mm(200x768, 768x768) 2025-09-07T09:57:36.5184278Z strides: [768, 1], [768, 1] 2025-09-07T09:57:36.5184562Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:36.5185255Z triton_mm_3836 0.0086 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 2025-09-07T09:57:36.5186279Z triton_mm_3840 0.0086 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:36.5186924Z mm 0.0087 ms 98.5% 2025-09-07T09:57:36.5187504Z triton_mm_3844 0.0096 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:36.5188491Z triton_mm_3835 0.0105 ms 82.0% 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 2025-09-07T09:57:36.5189455Z triton_mm_3834 0.0107 ms 80.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.5190823Z triton_mm_3839 0.0108 ms 79.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:57:36.5191817Z triton_mm_3843 0.0110 ms 78.2% 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 2025-09-07T09:57:36.5192792Z triton_mm_3850 0.0113 ms 76.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.5193766Z triton_mm_3833 0.0117 ms 73.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:57:36.5194614Z SingleProcess AUTOTUNE benchmarking takes 0.2103 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:36.7554690Z Autotune Choices Stats: 2025-09-07T09:57:36.7555934Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011392000131309032, "best_triton_pos": 1, "best_triton_time": 0.011680000461637974, "best_triton_kernel": "triton_mm_3893", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:57:36.7915524Z AUTOTUNE mm(200x2304, 2304x768) 2025-09-07T09:57:36.7915779Z strides: [2304, 1], [768, 1] 2025-09-07T09:57:36.7916031Z dtypes: torch.float16, torch.float16 2025-09-07T09:57:36.7916297Z mm 0.0114 ms 100.0% 2025-09-07T09:57:36.7916892Z triton_mm_3893 0.0117 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:36.7917873Z triton_mm_3897 0.0122 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:57:36.7918844Z triton_mm_3901 0.0144 ms 78.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:57:36.7920138Z triton_mm_3892 0.0195 ms 58.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.7921643Z triton_mm_3891 0.0196 ms 58.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.7922698Z triton_mm_3907 0.0197 ms 57.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:57:36.7923679Z triton_mm_3900 0.0204 ms 55.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:36.7924638Z triton_mm_3896 0.0205 ms 55.5% 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 2025-09-07T09:57:36.7925634Z triton_mm_3906 0.0227 ms 50.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:57:36.7926484Z SingleProcess AUTOTUNE benchmarking takes 0.2727 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T09:57:43.8963866Z 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 2025-09-07T09:57:43.8965243Z pred = mod(*cloned_inputs) 2025-09-07T09:57:43.8965952Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchmultimodal/models/clip/model.py", line 72, in forward 2025-09-07T09:57:43.8966665Z embeddings_b = self.encoder_b(features_b) 2025-09-07T09:57:43.8967432Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchmultimodal/models/clip/text_encoder.py", line 132, in forward 2025-09-07T09:57:43.8968285Z hidden_state[torch.arange(hidden_state.shape[0]), text.argmax(dim=-1)] 2025-09-07T09:57:43.8968647Z 2025-09-07T09:57:43.8968651Z 2025-09-07T09:57:45.1317940Z W0907 09:57:45.131000 106268 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T09:58:25.9553346Z pass 2025-09-07T09:58:32.8324944Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:58:32.8326172Z import pynvml # type: ignore[import] 2025-09-07T09:58:35.5683341Z 2025-09-07T09:58:36.4223904Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:58:36.4224295Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:58:36.4224615Z cuda train tts_angular 2025-09-07T09:58:39.5195536Z W0907 09:58:39.518000 114332 site-packages/torch/_logging/_internal.py:1199] [10/0] Profiler function will be ignored 2025-09-07T09:58:41.6514066Z pass 2025-09-07T09:58:44.4469882Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:58:44.4471422Z import pynvml # type: ignore[import] 2025-09-07T09:58:47.7555909Z 2025-09-07T09:58:51.9474858Z loading model: 0it [00:00, ?it/s] 2025-09-07T09:58:51.9475210Z loading model: 0it [00:04, ?it/s] 2025-09-07T09:58:51.9475511Z cuda train vgg16 2025-09-07T09:59:00.6419312Z Autotune Choices Stats: 2025-09-07T09:59:00.6421036Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.08905600011348724, "best_triton_pos": 1, "best_triton_time": 0.0899519994854927, "best_triton_kernel": "triton_mm_94", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T09:59:00.6495415Z AUTOTUNE mm(4x25088, 25088x4096) 2025-09-07T09:59:00.6495723Z strides: [25088, 1], [1, 25088] 2025-09-07T09:59:00.6495994Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:00.6496268Z mm 0.0891 ms 100.0% 2025-09-07T09:59:00.6496878Z triton_mm_94 0.0900 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:59:00.6497879Z triton_mm_98 0.0900 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:00.6498895Z triton_mm_102 0.1044 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:00.6499867Z triton_mm_106 0.1348 ms 66.1% 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 2025-09-07T09:59:00.6501025Z triton_mm_93 0.1686 ms 52.8% 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 2025-09-07T09:59:00.6501997Z triton_mm_97 0.1775 ms 50.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:00.6503049Z triton_mm_91 0.1800 ms 49.5% 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 2025-09-07T09:59:00.6504032Z triton_mm_92 0.1810 ms 49.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:00.6505073Z triton_mm_101 0.1915 ms 46.5% 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 2025-09-07T09:59:00.6505866Z SingleProcess AUTOTUNE benchmarking takes 0.5167 seconds and 0.0003 seconds precompiling for 18 choices 2025-09-07T09:59:01.1816857Z Autotune Choices Stats: 2025-09-07T09:59:01.1817942Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_111", "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": 0.023711999878287315, "best_triton_pos": 0} 2025-09-07T09:59:01.1888503Z AUTOTUNE mm(4x4096, 4096x4096) 2025-09-07T09:59:01.1888858Z strides: [4096, 1], [1, 4096] 2025-09-07T09:59:01.1889158Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:01.1889914Z triton_mm_111 0.0237 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:59:01.1891232Z triton_mm_115 0.0238 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:01.1891906Z mm 0.0256 ms 92.5% 2025-09-07T09:59:01.1892567Z triton_mm_119 0.0271 ms 87.6% 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 2025-09-07T09:59:01.1893622Z triton_mm_123 0.0310 ms 76.4% 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 2025-09-07T09:59:01.1895046Z triton_mm_108 0.0385 ms 61.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T09:59:01.1896159Z triton_mm_114 0.0394 ms 60.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:01.1897178Z triton_mm_110 0.0403 ms 58.9% 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 2025-09-07T09:59:01.1898079Z triton_mm_118 0.0417 ms 56.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:01.1898974Z triton_mm_109 0.0418 ms 56.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:01.1899759Z SingleProcess AUTOTUNE benchmarking takes 0.2722 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:59:01.7145339Z Autotune Choices Stats: 2025-09-07T09:59:01.7147115Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.03606399893760681, "best_triton_pos": 1, "best_triton_time": 0.051872000098228455, "best_triton_kernel": "triton_convolution2d_4", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:59:01.7224613Z AUTOTUNE convolution(4x3x224x224, 64x3x3x3) 2025-09-07T09:59:01.7224973Z strides: [150528, 1, 672, 3], [27, 1, 9, 3] 2025-09-07T09:59:01.7225297Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:01.7225616Z convolution 0.0361 ms 100.0% 2025-09-07T09:59:01.7226474Z triton_convolution2d_4 0.0519 ms 69.5% 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=8 2025-09-07T09:59:01.7227898Z triton_convolution2d_0 0.0542 ms 66.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:01.7229303Z triton_convolution2d_3 0.0554 ms 65.1% 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 2025-09-07T09:59:01.7230882Z triton_convolution2d_2 0.0726 ms 49.6% 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 2025-09-07T09:59:01.7232306Z triton_convolution2d_5 0.0735 ms 49.1% 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=8 2025-09-07T09:59:01.7233730Z triton_convolution2d_1 0.1245 ms 29.0% 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 2025-09-07T09:59:01.7234971Z SingleProcess AUTOTUNE benchmarking takes 0.1464 seconds and 0.0006 seconds precompiling for 7 choices 2025-09-07T09:59:01.8893298Z Autotune Choices Stats: 2025-09-07T09:59:01.8894858Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.04710400104522705, "best_triton_pos": 1, "best_triton_time": 0.06543999910354614, "best_triton_kernel": "triton_convolution2d_9", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:59:01.8965894Z AUTOTUNE convolution(4x64x224x224, 64x64x3x3) 2025-09-07T09:59:01.8966389Z strides: [3211264, 1, 14336, 64], [576, 1, 192, 64] 2025-09-07T09:59:01.8966761Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:01.8967091Z convolution 0.0471 ms 100.0% 2025-09-07T09:59:01.8968492Z triton_convolution2d_9 0.0654 ms 72.0% 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 2025-09-07T09:59:01.8970065Z triton_convolution2d_12 0.0694 ms 67.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:01.8971772Z triton_convolution2d_10 0.0794 ms 59.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:01.8973291Z triton_convolution2d_11 0.0812 ms 58.0% 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 2025-09-07T09:59:01.8974837Z triton_convolution2d_7 0.0985 ms 47.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:01.8976163Z triton_convolution2d_6 0.1526 ms 30.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:01.8977481Z triton_convolution2d_8 0.2942 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 2025-09-07T09:59:01.8978543Z SingleProcess AUTOTUNE benchmarking takes 0.1732 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:02.0259278Z Autotune Choices Stats: 2025-09-07T09:59:02.0260973Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03139200061559677, "best_triton_pos": 1, "best_triton_time": 0.03356799855828285, "best_triton_kernel": "triton_convolution2d_16", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T09:59:02.0333308Z AUTOTUNE convolution(4x64x112x112, 128x64x3x3) 2025-09-07T09:59:02.0333688Z strides: [802816, 1, 7168, 64], [576, 1, 192, 64] 2025-09-07T09:59:02.0334027Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:02.0334329Z convolution 0.0314 ms 100.0% 2025-09-07T09:59:02.0335214Z triton_convolution2d_16 0.0336 ms 93.5% 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 2025-09-07T09:59:02.0336523Z triton_convolution2d_18 0.0339 ms 92.5% 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 2025-09-07T09:59:02.0337775Z triton_convolution2d_19 0.0403 ms 77.9% 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 2025-09-07T09:59:02.0339011Z triton_convolution2d_17 0.0407 ms 77.1% 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 2025-09-07T09:59:02.0340454Z triton_convolution2d_14 0.0545 ms 57.6% 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 2025-09-07T09:59:02.0341888Z triton_convolution2d_13 0.0595 ms 52.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:02.0343532Z triton_convolution2d_15 0.1441 ms 21.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:59:02.0344531Z SingleProcess AUTOTUNE benchmarking takes 0.1359 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:02.1951906Z Autotune Choices Stats: 2025-09-07T09:59:02.1953495Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.035232000052928925, "best_triton_pos": 1, "best_triton_time": 0.06560000032186508, "best_triton_kernel": "triton_convolution2d_25", "best_triton_kernel_desc": "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"} 2025-09-07T09:59:02.2023765Z AUTOTUNE convolution(4x128x112x112, 128x128x3x3) 2025-09-07T09:59:02.2024190Z strides: [1605632, 1, 14336, 128], [1152, 1, 384, 128] 2025-09-07T09:59:02.2024533Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:02.2024868Z convolution 0.0352 ms 100.0% 2025-09-07T09:59:02.2025731Z triton_convolution2d_25 0.0656 ms 53.7% 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 2025-09-07T09:59:02.2027167Z triton_convolution2d_23 0.0698 ms 50.5% 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 2025-09-07T09:59:02.2028597Z triton_convolution2d_26 0.0730 ms 48.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:02.2030009Z triton_convolution2d_24 0.0788 ms 44.7% 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 2025-09-07T09:59:02.2031787Z triton_convolution2d_21 0.0999 ms 35.3% 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 2025-09-07T09:59:02.2033266Z triton_convolution2d_20 0.1214 ms 29.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:02.2035059Z triton_convolution2d_22 0.2820 ms 12.5% 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 2025-09-07T09:59:02.2036049Z SingleProcess AUTOTUNE benchmarking takes 0.1682 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:02.3311231Z Autotune Choices Stats: 2025-09-07T09:59:02.3312671Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023360000923275948, "best_triton_pos": 1, "best_triton_time": 0.03481600061058998, "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"} 2025-09-07T09:59:02.3383697Z AUTOTUNE convolution(4x128x56x56, 256x128x3x3) 2025-09-07T09:59:02.3384367Z strides: [401408, 1, 7168, 128], [1152, 1, 384, 128] 2025-09-07T09:59:02.3384685Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:02.3384976Z convolution 0.0234 ms 100.0% 2025-09-07T09:59:02.3385740Z triton_convolution2d_31 0.0348 ms 67.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T09:59:02.3387364Z triton_convolution2d_30 0.0394 ms 59.3% 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 2025-09-07T09:59:02.3388639Z triton_convolution2d_32 0.0429 ms 54.5% 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 2025-09-07T09:59:02.3389908Z triton_convolution2d_33 0.0432 ms 54.1% 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 2025-09-07T09:59:02.3391772Z triton_convolution2d_28 0.0564 ms 41.4% 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 2025-09-07T09:59:02.3393062Z triton_convolution2d_27 0.0578 ms 40.4% 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 2025-09-07T09:59:02.3394329Z triton_convolution2d_29 0.1910 ms 12.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:59:02.3395410Z SingleProcess AUTOTUNE benchmarking takes 0.1353 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:02.4981411Z Autotune Choices Stats: 2025-09-07T09:59:02.4982976Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03340800106525421, "best_triton_pos": 1, "best_triton_time": 0.061344001442193985, "best_triton_kernel": "triton_convolution2d_38", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:59:02.5058092Z AUTOTUNE convolution(4x256x56x56, 256x256x3x3) 2025-09-07T09:59:02.5058411Z strides: [802816, 1, 14336, 256], [2304, 1, 768, 256] 2025-09-07T09:59:02.5058679Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:02.5058910Z convolution 0.0334 ms 100.0% 2025-09-07T09:59:02.5059507Z triton_convolution2d_38 0.0613 ms 54.5% 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 2025-09-07T09:59:02.5060742Z triton_convolution2d_37 0.0712 ms 46.9% 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 2025-09-07T09:59:02.5061744Z triton_convolution2d_39 0.0774 ms 43.2% 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 2025-09-07T09:59:02.5062743Z triton_convolution2d_40 0.0774 ms 43.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:02.5063861Z triton_convolution2d_35 0.1032 ms 32.4% 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 2025-09-07T09:59:02.5065221Z triton_convolution2d_34 0.1072 ms 31.2% 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 2025-09-07T09:59:02.5066446Z triton_convolution2d_36 0.3756 ms 8.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:59:02.5067365Z SingleProcess AUTOTUNE benchmarking takes 0.1666 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:02.6592171Z Autotune Choices Stats: 2025-09-07T09:59:02.6593677Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023104000836610794, "best_triton_pos": 1, "best_triton_time": 0.05571199953556061, "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"} 2025-09-07T09:59:02.6664734Z AUTOTUNE convolution(4x256x28x28, 512x256x3x3) 2025-09-07T09:59:02.6676929Z strides: [200704, 1, 7168, 256], [2304, 1, 768, 256] 2025-09-07T09:59:02.6677390Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:02.6677729Z convolution 0.0231 ms 100.0% 2025-09-07T09:59:02.6678636Z triton_convolution2d_52 0.0557 ms 41.5% 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 2025-09-07T09:59:02.6680101Z triton_convolution2d_51 0.0701 ms 32.9% 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 2025-09-07T09:59:02.6681722Z triton_convolution2d_54 0.0739 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 2025-09-07T09:59:02.6683223Z triton_convolution2d_53 0.0744 ms 31.0% 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 2025-09-07T09:59:02.6684688Z triton_convolution2d_49 0.0903 ms 25.6% 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 2025-09-07T09:59:02.6686058Z triton_convolution2d_48 0.1028 ms 22.5% 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 2025-09-07T09:59:02.6687111Z triton_convolution2d_50 0.1886 ms 12.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T09:59:02.6687959Z SingleProcess AUTOTUNE benchmarking takes 0.1573 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:02.9584575Z Autotune Choices Stats: 2025-09-07T09:59:02.9586050Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03311999887228012, "best_triton_pos": 1, "best_triton_time": 0.1072319969534874, "best_triton_kernel": "triton_convolution2d_59", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T09:59:02.9664968Z AUTOTUNE convolution(4x512x28x28, 512x512x3x3) 2025-09-07T09:59:02.9665332Z strides: [401408, 1, 14336, 512], [4608, 1, 1536, 512] 2025-09-07T09:59:02.9665653Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:02.9666253Z convolution 0.0331 ms 100.0% 2025-09-07T09:59:02.9666986Z triton_convolution2d_59 0.1072 ms 30.9% 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 2025-09-07T09:59:02.9668497Z triton_convolution2d_58 0.1334 ms 24.8% 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 2025-09-07T09:59:02.9669855Z triton_convolution2d_61 0.1412 ms 23.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:02.9671546Z triton_convolution2d_60 0.1423 ms 23.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:02.9672799Z triton_convolution2d_56 0.1761 ms 18.8% 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 2025-09-07T09:59:02.9674034Z triton_convolution2d_55 0.2021 ms 16.4% 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 2025-09-07T09:59:02.9675261Z triton_convolution2d_57 0.3537 ms 9.4% 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 2025-09-07T09:59:02.9676226Z SingleProcess AUTOTUNE benchmarking takes 0.2991 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:03.1786801Z Autotune Choices Stats: 2025-09-07T09:59:03.1788246Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02143999934196472, "best_triton_pos": 1, "best_triton_time": 0.1088000014424324, "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"} 2025-09-07T09:59:03.1867434Z AUTOTUNE convolution(4x512x14x14, 512x512x3x3) 2025-09-07T09:59:03.1867798Z strides: [100352, 1, 7168, 512], [4608, 1, 1536, 512] 2025-09-07T09:59:03.1868118Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:03.1868391Z convolution 0.0214 ms 100.0% 2025-09-07T09:59:03.1869146Z triton_convolution2d_73 0.1088 ms 19.7% 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 2025-09-07T09:59:03.1870585Z triton_convolution2d_72 0.1332 ms 16.1% 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 2025-09-07T09:59:03.1871838Z triton_convolution2d_75 0.1388 ms 15.5% 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 2025-09-07T09:59:03.1873066Z triton_convolution2d_74 0.1403 ms 15.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T09:59:03.1874280Z triton_convolution2d_70 0.1745 ms 12.3% 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 2025-09-07T09:59:03.1875664Z triton_convolution2d_69 0.1991 ms 10.8% 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 2025-09-07T09:59:03.1877317Z triton_convolution2d_71 0.3413 ms 6.3% 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 2025-09-07T09:59:03.1878714Z SingleProcess AUTOTUNE benchmarking takes 0.2167 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T09:59:03.4773905Z Autotune Choices Stats: 2025-09-07T09:59:03.4775294Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "bias_addmm", "best_time": 0.014879999682307243, "best_triton_pos": 1, "best_triton_time": 0.01759999990463257, "best_triton_kernel": "triton_mm_128", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2"} 2025-09-07T09:59:03.4851364Z AUTOTUNE addmm(4x1000, 4x4096, 4096x1000) 2025-09-07T09:59:03.4851723Z strides: [0, 1], [4096, 1], [1, 4096] 2025-09-07T09:59:03.4852062Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T09:59:03.4852421Z bias_addmm 0.0149 ms 100.0% 2025-09-07T09:59:03.4853084Z triton_mm_128 0.0176 ms 84.5% 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 2025-09-07T09:59:03.4854124Z triton_mm_132 0.0187 ms 79.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:03.4855156Z triton_mm_136 0.0201 ms 74.0% 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 2025-09-07T09:59:03.4855852Z addmm 0.0207 ms 71.9% 2025-09-07T09:59:03.4856383Z triton_mm_140 0.0244 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:03.4857279Z triton_mm_127 0.0293 ms 50.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:59:03.4858166Z triton_mm_125 0.0300 ms 49.5% 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 2025-09-07T09:59:03.4859049Z triton_mm_126 0.0311 ms 47.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:03.4859930Z triton_mm_131 0.0313 ms 47.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:03.4860986Z SingleProcess AUTOTUNE benchmarking takes 0.2924 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T09:59:09.4975377Z Autotune Choices Stats: 2025-09-07T09:59:09.4976486Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_233", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8", "best_time": 0.0697920024394989, "best_triton_pos": 0} 2025-09-07T09:59:09.5052917Z AUTOTUNE mm(4096x4, 4x25088) 2025-09-07T09:59:09.5053205Z strides: [1, 4096], [25088, 1] 2025-09-07T09:59:09.5053501Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:09.5054223Z triton_mm_233 0.0698 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:59:09.5055293Z triton_mm_232 0.0698 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:09.5056805Z triton_mm_234 0.0700 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:09.5058235Z triton_mm_229 0.0716 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:59:09.5059419Z triton_mm_231 0.0717 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:09.5060751Z triton_mm_238 0.0718 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:09.5061852Z triton_mm_237 0.0732 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:59:09.5063006Z triton_mm_228 0.0737 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:09.5064064Z triton_mm_230 0.0739 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:59:09.5065124Z triton_mm_239 0.0742 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:09.5066052Z SingleProcess AUTOTUNE benchmarking takes 0.2916 seconds and 0.0003 seconds precompiling for 17 choices 2025-09-07T09:59:09.9763851Z Autotune Choices Stats: 2025-09-07T09:59:09.9765232Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_197", "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=3, num_warps=8", "best_time": 0.01651199907064438, "best_triton_pos": 0} 2025-09-07T09:59:09.9837877Z AUTOTUNE mm(4096x4, 4x4096) 2025-09-07T09:59:09.9838211Z strides: [1, 4096], [4096, 1] 2025-09-07T09:59:09.9838542Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:09.9839437Z triton_mm_197 0.0165 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:59:09.9841181Z triton_mm_199 0.0165 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:09.9842545Z triton_mm_201 0.0165 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:09.9843880Z triton_mm_196 0.0166 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:59:09.9845197Z triton_mm_200 0.0166 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:59:09.9846523Z triton_mm_203 0.0166 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:59:09.9847770Z triton_mm_204 0.0167 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:59:09.9848841Z triton_mm_205 0.0167 ms 99.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:09.9850410Z triton_mm_198 0.0167 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:09.9851766Z triton_mm_206 0.0167 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:09.9852847Z SingleProcess AUTOTUNE benchmarking takes 0.2139 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:59:10.3420703Z Autotune Choices Stats: 2025-09-07T09:59:10.3421804Z {"num_choices": 17, "num_triton_choices": 16, "best_kernel": "triton_mm_163", "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": 0.008352000266313553, "best_triton_pos": 0} 2025-09-07T09:59:10.3494692Z AUTOTUNE mm(1000x4, 4x4096) 2025-09-07T09:59:10.3494973Z strides: [1, 1000], [4096, 1] 2025-09-07T09:59:10.3495269Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:10.3495987Z triton_mm_163 0.0084 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T09:59:10.3497079Z triton_mm_165 0.0084 ms 99.6% 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 2025-09-07T09:59:10.3498151Z triton_mm_169 0.0085 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:10.3499200Z triton_mm_167 0.0086 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:59:10.3500393Z triton_mm_168 0.0086 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:10.3501453Z triton_mm_171 0.0087 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T09:59:10.3502522Z triton_mm_173 0.0087 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:10.3503662Z triton_mm_164 0.0087 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T09:59:10.3504707Z triton_mm_170 0.0087 ms 95.6% 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 2025-09-07T09:59:10.3505755Z triton_mm_166 0.0088 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:10.3506674Z SingleProcess AUTOTUNE benchmarking takes 0.1676 seconds and 0.0002 seconds precompiling for 17 choices 2025-09-07T09:59:10.7364153Z Autotune Choices Stats: 2025-09-07T09:59:10.7365527Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.010847999714314938, "best_triton_pos": 1, "best_triton_time": 0.012032000347971916, "best_triton_kernel": "triton_mm_149", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:59:10.7441240Z AUTOTUNE mm(4x1000, 1000x4096) 2025-09-07T09:59:10.7441546Z strides: [1000, 1], [4096, 1] 2025-09-07T09:59:10.7441860Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:10.7442401Z mm 0.0108 ms 100.0% 2025-09-07T09:59:10.7443125Z triton_mm_149 0.0120 ms 90.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:10.7444327Z triton_mm_157 0.0124 ms 87.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:10.7445868Z triton_mm_153 0.0128 ms 84.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:10.7447043Z triton_mm_143 0.0129 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:10.7448178Z triton_mm_148 0.0136 ms 79.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:10.7449229Z triton_mm_145 0.0142 ms 76.5% 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 2025-09-07T09:59:10.7450456Z triton_mm_155 0.0143 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:10.7451518Z triton_mm_151 0.0149 ms 72.9% 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 2025-09-07T09:59:10.7452576Z triton_mm_152 0.0155 ms 69.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:10.7453500Z SingleProcess AUTOTUNE benchmarking takes 0.2019 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:59:11.2191008Z Autotune Choices Stats: 2025-09-07T09:59:11.2192416Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "mm", "best_time": 0.02160000056028366, "best_triton_pos": 1, "best_triton_time": 0.024320000782608986, "best_triton_kernel": "triton_mm_182", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T09:59:11.2266067Z AUTOTUNE mm(4x4096, 4096x4096) 2025-09-07T09:59:11.2266344Z strides: [4096, 1], [4096, 1] 2025-09-07T09:59:11.2266617Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:11.2266889Z mm 0.0216 ms 100.0% 2025-09-07T09:59:11.2267513Z triton_mm_182 0.0243 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:11.2268578Z triton_mm_178 0.0260 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T09:59:11.2269663Z triton_mm_186 0.0266 ms 81.1% 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 2025-09-07T09:59:11.2270910Z triton_mm_190 0.0289 ms 74.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:11.2271956Z triton_mm_176 0.0354 ms 61.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:11.2272976Z triton_mm_177 0.0372 ms 58.1% 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 2025-09-07T09:59:11.2274317Z triton_mm_181 0.0386 ms 56.0% 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 2025-09-07T09:59:11.2275350Z triton_mm_185 0.0396 ms 54.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:11.2276774Z triton_mm_188 0.0420 ms 51.4% 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 2025-09-07T09:59:11.2277689Z SingleProcess AUTOTUNE benchmarking takes 0.2617 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:59:12.0148500Z Autotune Choices Stats: 2025-09-07T09:59:12.0149628Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_218", "best_kernel_desc": "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", "best_time": 0.08035200089216232, "best_triton_pos": 0} 2025-09-07T09:59:12.0222877Z AUTOTUNE mm(4x4096, 4096x25088) 2025-09-07T09:59:12.0223242Z strides: [4096, 1], [25088, 1] 2025-09-07T09:59:12.0223510Z dtypes: torch.float16, torch.float16 2025-09-07T09:59:12.0224247Z triton_mm_218 0.0804 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 2025-09-07T09:59:12.0225328Z triton_mm_209 0.0807 ms 99.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:12.0226333Z triton_mm_214 0.0811 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T09:59:12.0227351Z triton_mm_217 0.0817 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T09:59:12.0228568Z triton_mm_221 0.0819 ms 98.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T09:59:12.0229616Z triton_mm_223 0.0832 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=16, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T09:59:12.0230826Z triton_mm_215 0.0836 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=16, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T09:59:12.0231880Z triton_mm_219 0.0846 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 2025-09-07T09:59:12.0232545Z mm 0.0847 ms 94.8% 2025-09-07T09:59:12.0233152Z triton_mm_208 0.0878 ms 91.5% 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 2025-09-07T09:59:12.0234072Z SingleProcess AUTOTUNE benchmarking takes 0.3380 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T09:59:15.4569736Z pass 2025-09-07T09:59:18.5846367Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T09:59:18.5847464Z import pynvml # type: ignore[import] 2025-09-07T09:59:21.0953679Z 2025-09-07T09:59:33.4553624Z loading model: 0it [00:00, ?it/s]skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:59:33.4555263Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:59:33.4556037Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:59:33.4556643Z v4 = masked_index(y_high, x_high) 2025-09-07T09:59:33.4557635Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:59:33.4558168Z return input[ 2025-09-07T09:59:33.4558293Z 2025-09-07T09:59:33.4558297Z 2025-09-07T09:59:43.0176879Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:59:43.0178064Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:59:43.0178868Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:59:43.0179478Z v4 = masked_index(y_high, x_high) 2025-09-07T09:59:43.0180024Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:59:43.0180896Z return input[ 2025-09-07T09:59:43.0181030Z 2025-09-07T09:59:43.0181034Z 2025-09-07T09:59:50.8667917Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:59:50.8669052Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:59:50.8669900Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:59:50.8670932Z v4 = masked_index(y_high, x_high) 2025-09-07T09:59:50.8671521Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:59:50.8672079Z return input[ 2025-09-07T09:59:50.8672217Z 2025-09-07T09:59:50.8672220Z 2025-09-07T09:59:58.0156955Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T09:59:58.0158107Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T09:59:58.0158860Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T09:59:58.0159455Z v4 = masked_index(y_high, x_high) 2025-09-07T09:59:58.0159981Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T09:59:58.0160827Z return input[ 2025-09-07T09:59:58.0160959Z 2025-09-07T09:59:58.0160963Z 2025-09-07T10:00:06.9343656Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:00:06.9344778Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:00:06.9345487Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:00:06.9346045Z v4 = masked_index(y_high, x_high) 2025-09-07T10:00:06.9346538Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:00:06.9347026Z return input[ 2025-09-07T10:00:06.9347143Z 2025-09-07T10:00:06.9347146Z 2025-09-07T10:00:15.1230825Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:00:15.1232341Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:00:15.1233483Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:00:15.1234284Z v4 = masked_index(y_high, x_high) 2025-09-07T10:00:15.1234855Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:00:15.1235395Z return input[ 2025-09-07T10:00:15.1235530Z 2025-09-07T10:00:15.1235536Z 2025-09-07T10:00:26.3085301Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:00:26.3086579Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:00:26.3087426Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:00:26.3088072Z v4 = masked_index(y_high, x_high) 2025-09-07T10:00:26.3088680Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:00:26.3089319Z return input[ 2025-09-07T10:00:26.3089480Z 2025-09-07T10:00:26.3089483Z 2025-09-07T10:00:30.1929938Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:00:30.1931402Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:00:30.1932136Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:00:30.1932685Z v4 = masked_index(y_high, x_high) 2025-09-07T10:00:30.1933173Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:00:30.1933665Z return input[ 2025-09-07T10:00:30.1933792Z 2025-09-07T10:00:30.1933797Z 2025-09-07T10:00:31.3651967Z 2025-09-07T10:00:31.3652348Z loading model: 0it [01:10, ?it/s] 2025-09-07T10:00:31.3652715Z cuda train vision_maskrcnn 2025-09-07T10:00:31.4909487Z W0907 10:00:31.490000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T10:00:31.4910950Z W0907 10:00:31.490000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] function: '_roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:114) 2025-09-07T10:00:31.4912111Z W0907 10:00:31.490000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] last reason: 0/7: tensor 'rois' dtype mismatch. expected Float, actual Double 2025-09-07T10:00:31.4913098Z W0907 10:00:31.490000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T10:00:31.4914239Z W0907 10:00:31.490000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [0/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T10:00:49.4165383Z Autotune Choices Stats: 2025-09-07T10:00:49.4166896Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_66", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.020287999883294106, "best_triton_pos": 0} 2025-09-07T10:00:49.4244953Z AUTOTUNE mm(60800x64, 64x256) 2025-09-07T10:00:49.4245859Z strides: [64, 1], [1, 64] 2025-09-07T10:00:49.4246218Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:49.4247170Z triton_mm_66 0.0203 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:49.4249184Z triton_mm_61 0.0203 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:49.4251142Z triton_mm_62 0.0204 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:00:49.4252049Z mm 0.0206 ms 98.4% 2025-09-07T10:00:49.4252864Z triton_mm_63 0.0208 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:49.4254312Z triton_mm_58 0.0212 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:00:49.4255737Z triton_mm_59 0.0215 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:49.4257173Z triton_mm_60 0.0226 ms 89.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:49.4258588Z triton_mm_64 0.0231 ms 87.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:49.4260009Z triton_mm_68 0.0232 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:49.4261430Z SingleProcess AUTOTUNE benchmarking takes 0.2600 seconds and 0.0004 seconds precompiling for 20 choices 2025-09-07T10:00:50.3954903Z Autotune Choices Stats: 2025-09-07T10:00:50.3956622Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.10838399827480316, "best_triton_pos": 1, "best_triton_time": 0.2699519991874695, "best_triton_kernel": "triton_convolution2d_865", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:00:50.4035683Z AUTOTUNE convolution(1x256x200x304, 256x256x3x3) 2025-09-07T10:00:50.4036100Z strides: [15564800, 1, 77824, 256], [2304, 1, 768, 256] 2025-09-07T10:00:50.4036456Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:50.4036771Z convolution 0.1084 ms 100.0% 2025-09-07T10:00:50.4037666Z triton_convolution2d_865 0.2700 ms 40.1% 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 2025-09-07T10:00:50.4039136Z triton_convolution2d_863 0.2813 ms 38.5% 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 2025-09-07T10:00:50.4041138Z triton_convolution2d_866 0.3091 ms 35.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:00:50.4042590Z triton_convolution2d_864 0.3358 ms 32.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:00:50.4044035Z triton_convolution2d_860 0.3827 ms 28.3% 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 2025-09-07T10:00:50.4046005Z triton_convolution2d_861 0.4254 ms 25.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:00:50.4047915Z triton_convolution2d_862 1.5030 ms 7.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:00:50.4049068Z SingleProcess AUTOTUNE benchmarking takes 0.2846 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:00:51.8241441Z Autotune Choices Stats: 2025-09-07T10:00:51.8242878Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.036320000886917114, "best_triton_pos": 1, "best_triton_time": 0.03859199956059456, "best_triton_kernel": "triton_mm_858", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:00:51.8320677Z AUTOTUNE addmm(60800x256, 60800x256, 256x256) 2025-09-07T10:00:51.8321022Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:00:51.8321363Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:00:51.8321722Z bias_addmm 0.0363 ms 100.0% 2025-09-07T10:00:51.8322429Z triton_mm_858 0.0386 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:51.8323492Z triton_mm_852 0.0401 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:51.8324534Z triton_mm_851 0.0415 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:51.8325574Z triton_mm_855 0.0421 ms 86.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:51.8326704Z triton_mm_857 0.0423 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:51.8327692Z triton_mm_850 0.0426 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:51.8328645Z triton_mm_854 0.0430 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:51.8329608Z triton_mm_859 0.0463 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:51.8330714Z triton_mm_848 0.0469 ms 77.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:51.8331576Z SingleProcess AUTOTUNE benchmarking takes 0.3407 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T10:00:52.4581347Z Autotune Choices Stats: 2025-09-07T10:00:52.4582609Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_174", "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": 0.02502400055527687, "best_triton_pos": 0} 2025-09-07T10:00:52.4658390Z AUTOTUNE mm(60800x256, 256x128) 2025-09-07T10:00:52.4658709Z strides: [256, 1], [1, 256] 2025-09-07T10:00:52.4659400Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:52.4660392Z triton_mm_174 0.0250 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:52.4661954Z triton_mm_168 0.0253 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:52.4662956Z mm 0.0260 ms 96.4% 2025-09-07T10:00:52.4663676Z triton_mm_175 0.0282 ms 88.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:52.4664882Z triton_mm_167 0.0289 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:52.4666082Z triton_mm_173 0.0294 ms 85.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:52.4667390Z triton_mm_164 0.0296 ms 84.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:52.4668542Z triton_mm_171 0.0297 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:52.4669694Z triton_mm_166 0.0298 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:52.4670982Z triton_mm_170 0.0303 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:52.4671988Z SingleProcess AUTOTUNE benchmarking takes 0.2713 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:00:52.9951580Z Autotune Choices Stats: 2025-09-07T10:00:52.9952977Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.014368000440299511, "best_triton_pos": 1, "best_triton_time": 0.016256000846624374, "best_triton_kernel": "triton_mm_252", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:00:53.0028411Z AUTOTUNE mm(15200x128, 128x512) 2025-09-07T10:00:53.0028715Z strides: [128, 1], [1, 128] 2025-09-07T10:00:53.0028981Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:53.0029255Z mm 0.0144 ms 100.0% 2025-09-07T10:00:53.0029892Z triton_mm_252 0.0163 ms 88.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:53.0031310Z triton_mm_244 0.0164 ms 87.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:53.0032376Z triton_mm_251 0.0164 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:53.0033434Z triton_mm_248 0.0171 ms 84.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:53.0034481Z triton_mm_249 0.0171 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:53.0035518Z triton_mm_241 0.0173 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:00:53.0036897Z triton_mm_245 0.0173 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:53.0037948Z triton_mm_247 0.0174 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:00:53.0039414Z triton_mm_250 0.0178 ms 80.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:00:53.0040473Z SingleProcess AUTOTUNE benchmarking takes 0.2593 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:00:54.4159946Z Autotune Choices Stats: 2025-09-07T10:00:54.4161904Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_23", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8", "best_time": 0.011455999687314034, "best_triton_pos": 0} 2025-09-07T10:00:54.4243484Z AUTOTUNE mm(60800x64, 64x64) 2025-09-07T10:00:54.4243920Z strides: [64, 1], [1, 64] 2025-09-07T10:00:54.4244299Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:54.4245294Z triton_mm_23 0.0115 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:54.4246798Z triton_mm_22 0.0116 ms 98.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:54.4248247Z triton_mm_12 0.0116 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:00:54.4249674Z triton_mm_13 0.0117 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:54.4251345Z triton_mm_21 0.0118 ms 96.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:00:54.4252827Z triton_mm_20 0.0121 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:54.4254267Z triton_mm_19 0.0121 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:54.4255748Z triton_mm_18 0.0123 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:00:54.4257209Z triton_mm_17 0.0124 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:54.4258673Z triton_mm_14 0.0126 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:00:54.4259962Z SingleProcess AUTOTUNE benchmarking takes 0.2407 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T10:00:54.9793264Z Autotune Choices Stats: 2025-09-07T10:00:54.9794774Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_80", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.02239999920129776, "best_triton_pos": 0} 2025-09-07T10:00:54.9872657Z AUTOTUNE mm(60800x256, 256x64) 2025-09-07T10:00:54.9873090Z strides: [256, 1], [1, 256] 2025-09-07T10:00:54.9874064Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:54.9875041Z triton_mm_80 0.0224 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:54.9876970Z triton_mm_76 0.0227 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:54.9878679Z triton_mm_85 0.0228 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:54.9879619Z mm 0.0239 ms 93.6% 2025-09-07T10:00:54.9880937Z triton_mm_86 0.0244 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:54.9882438Z triton_mm_83 0.0266 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:54.9883926Z triton_mm_79 0.0270 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:54.9885404Z triton_mm_84 0.0271 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:00:54.9886870Z triton_mm_70 0.0271 ms 82.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:00:54.9888327Z triton_mm_82 0.0273 ms 82.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:54.9889623Z SingleProcess AUTOTUNE benchmarking takes 0.2403 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:00:55.2920933Z Autotune Choices Stats: 2025-09-07T10:00:55.2922761Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.016704000532627106, "best_triton_pos": 1, "best_triton_time": 0.016736000776290894, "best_triton_kernel": "triton_mm_361", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:00:55.3000811Z AUTOTUNE mm(15200x512, 512x256) 2025-09-07T10:00:55.3001214Z strides: [512, 1], [1, 512] 2025-09-07T10:00:55.3001597Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:55.3001984Z mm 0.0167 ms 100.0% 2025-09-07T10:00:55.3002885Z triton_mm_361 0.0167 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.3004416Z triton_mm_360 0.0190 ms 87.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.3005897Z triton_mm_362 0.0196 ms 85.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:55.3007409Z triton_mm_355 0.0201 ms 83.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.3008906Z triton_mm_353 0.0214 ms 77.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.3010616Z triton_mm_357 0.0215 ms 77.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.3012471Z triton_mm_351 0.0217 ms 76.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:55.3013914Z triton_mm_354 0.0223 ms 74.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:55.3015938Z triton_mm_358 0.0225 ms 74.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:55.3017243Z SingleProcess AUTOTUNE benchmarking takes 0.2575 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:00:55.8049836Z Autotune Choices Stats: 2025-09-07T10:00:55.8051793Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01158399973064661, "best_triton_pos": 1, "best_triton_time": 0.011807999573647976, "best_triton_kernel": "triton_mm_439", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:00:55.8130126Z AUTOTUNE mm(3800x256, 256x1024) 2025-09-07T10:00:55.8130612Z strides: [256, 1], [1, 256] 2025-09-07T10:00:55.8130917Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:55.8131201Z mm 0.0116 ms 100.0% 2025-09-07T10:00:55.8131867Z triton_mm_439 0.0118 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.8132916Z triton_mm_438 0.0124 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.8133922Z triton_mm_435 0.0133 ms 86.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.8134897Z triton_mm_431 0.0134 ms 86.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.8135857Z triton_mm_433 0.0136 ms 85.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:55.8136807Z triton_mm_428 0.0138 ms 83.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:00:55.8137846Z triton_mm_440 0.0139 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:55.8138788Z triton_mm_436 0.0140 ms 82.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:55.8139696Z triton_mm_432 0.0143 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:55.8140626Z SingleProcess AUTOTUNE benchmarking takes 0.2464 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:00:56.8825021Z Autotune Choices Stats: 2025-09-07T10:00:56.8826501Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.03488000109791756, "best_triton_pos": 1, "best_triton_time": 0.07318399846553802, "best_triton_kernel": "triton_convolution2d_837", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:00:56.8908274Z AUTOTUNE convolution(1x256x100x152, 256x256x3x3) 2025-09-07T10:00:56.8909198Z strides: [3891200, 1, 38912, 256], [2304, 1, 768, 256] 2025-09-07T10:00:56.8909541Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:56.8909843Z convolution 0.0349 ms 100.0% 2025-09-07T10:00:56.8911252Z triton_convolution2d_837 0.0732 ms 47.7% 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 2025-09-07T10:00:56.8912769Z triton_convolution2d_838 0.0780 ms 44.7% 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 2025-09-07T10:00:56.8914104Z triton_convolution2d_840 0.0788 ms 44.3% 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 2025-09-07T10:00:56.8915434Z triton_convolution2d_839 0.0805 ms 43.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:00:56.8916763Z triton_convolution2d_835 0.1041 ms 33.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:00:56.8918109Z triton_convolution2d_834 0.1119 ms 31.2% 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 2025-09-07T10:00:56.8919279Z triton_convolution2d_836 0.3623 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 2025-09-07T10:00:56.8920183Z SingleProcess AUTOTUNE benchmarking takes 0.1714 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:00:58.2135414Z Autotune Choices Stats: 2025-09-07T10:00:58.2136904Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_832", "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": 0.0180479995906353, "best_triton_pos": 0} 2025-09-07T10:00:58.2215887Z AUTOTUNE addmm(15200x256, 15200x512, 512x256) 2025-09-07T10:00:58.2216347Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:00:58.2216814Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:00:58.2217836Z triton_mm_832 0.0180 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.2218773Z bias_addmm 0.0185 ms 97.7% 2025-09-07T10:00:58.2219653Z triton_mm_831 0.0205 ms 88.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.2221549Z triton_mm_826 0.0211 ms 85.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.2222969Z triton_mm_833 0.0217 ms 83.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:58.2224276Z triton_mm_828 0.0222 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.2225688Z triton_mm_824 0.0223 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.2227664Z triton_mm_822 0.0226 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:58.2229088Z triton_mm_825 0.0231 ms 78.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:58.2231211Z triton_mm_829 0.0232 ms 77.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:58.2232473Z SingleProcess AUTOTUNE benchmarking takes 0.2899 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T10:00:58.7745183Z Autotune Choices Stats: 2025-09-07T10:00:58.7746271Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_220", "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": 0.014655999839305878, "best_triton_pos": 0} 2025-09-07T10:00:58.7826381Z AUTOTUNE mm(15200x512, 512x128) 2025-09-07T10:00:58.7826675Z strides: [512, 1], [1, 512] 2025-09-07T10:00:58.7826939Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:58.7827615Z triton_mm_220 0.0147 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.7828822Z triton_mm_227 0.0150 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:58.7829880Z triton_mm_226 0.0151 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.7830893Z mm 0.0155 ms 94.4% 2025-09-07T10:00:58.7831501Z triton_mm_216 0.0159 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:58.7832571Z triton_mm_221 0.0167 ms 87.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:00:58.7833629Z triton_mm_219 0.0171 ms 85.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:58.7834663Z triton_mm_223 0.0173 ms 84.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:58.7835703Z triton_mm_222 0.0178 ms 82.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.7836749Z triton_mm_225 0.0181 ms 81.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:58.7837668Z SingleProcess AUTOTUNE benchmarking takes 0.2573 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:00:59.3780452Z Autotune Choices Stats: 2025-09-07T10:00:59.3781725Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01360000018030405, "best_triton_pos": 1, "best_triton_time": 0.0144640002399683, "best_triton_kernel": "triton_mm_639", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T10:00:59.3864527Z AUTOTUNE mm(3800x1024, 1024x512) 2025-09-07T10:00:59.3864885Z strides: [1024, 1], [1, 1024] 2025-09-07T10:00:59.3865197Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:59.3865507Z mm 0.0136 ms 100.0% 2025-09-07T10:00:59.3866611Z triton_mm_639 0.0145 ms 94.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:59.3867784Z triton_mm_632 0.0155 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.3869422Z triton_mm_638 0.0163 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.3870769Z triton_mm_628 0.0170 ms 80.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:59.3871934Z triton_mm_631 0.0178 ms 76.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:59.3873102Z triton_mm_633 0.0179 ms 76.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:00:59.3874269Z triton_mm_635 0.0179 ms 76.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:59.3875422Z triton_mm_630 0.0204 ms 66.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.3876574Z triton_mm_634 0.0206 ms 66.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.3877603Z SingleProcess AUTOTUNE benchmarking takes 0.2714 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:00:59.8936491Z Autotune Choices Stats: 2025-09-07T10:00:59.8937966Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01065600011497736, "best_triton_pos": 1, "best_triton_time": 0.011136000044643879, "best_triton_kernel": "triton_mm_717", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8"} 2025-09-07T10:00:59.9018132Z AUTOTUNE mm(950x512, 512x2048) 2025-09-07T10:00:59.9018437Z strides: [512, 1], [1, 512] 2025-09-07T10:00:59.9018730Z dtypes: torch.float16, torch.float16 2025-09-07T10:00:59.9019034Z mm 0.0107 ms 100.0% 2025-09-07T10:00:59.9019748Z triton_mm_717 0.0111 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:00:59.9021422Z triton_mm_716 0.0115 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.9022619Z triton_mm_710 0.0116 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.9023936Z triton_mm_709 0.0124 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:59.9025102Z triton_mm_706 0.0125 ms 85.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:00:59.9026258Z triton_mm_713 0.0127 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:00:59.9027426Z triton_mm_712 0.0134 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.9029098Z triton_mm_711 0.0135 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:00:59.9030778Z triton_mm_708 0.0138 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:00:59.9031960Z SingleProcess AUTOTUNE benchmarking takes 0.2490 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:01:01.0334016Z Autotune Choices Stats: 2025-09-07T10:01:01.0335880Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.012384000234305859, "best_triton_pos": 1, "best_triton_time": 0.012543999589979649, "best_triton_kernel": "triton_mm_408", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:01:01.0417814Z AUTOTUNE mm(3800x1024, 1024x256) 2025-09-07T10:01:01.0418238Z strides: [1024, 1], [1, 1024] 2025-09-07T10:01:01.0418628Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:01.0419021Z mm 0.0124 ms 100.0% 2025-09-07T10:01:01.0419942Z triton_mm_408 0.0125 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:01.0422018Z triton_mm_414 0.0140 ms 88.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:01.0423642Z triton_mm_407 0.0143 ms 86.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:01.0425141Z triton_mm_403 0.0146 ms 85.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:01.0426587Z triton_mm_404 0.0149 ms 83.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:01.0428030Z triton_mm_413 0.0156 ms 79.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:01.0429515Z triton_mm_406 0.0163 ms 76.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:01.0431185Z triton_mm_410 0.0165 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 2025-09-07T10:01:01.0432689Z triton_mm_400 0.0196 ms 63.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:01.0433973Z SingleProcess AUTOTUNE benchmarking takes 0.2600 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:01:01.5738504Z Autotune Choices Stats: 2025-09-07T10:01:01.5740004Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.017184000462293625, "best_triton_pos": 1, "best_triton_time": 0.0533440001308918, "best_triton_kernel": "triton_convolution2d_812", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:01.5818439Z AUTOTUNE convolution(1x256x50x76, 256x256x3x3) 2025-09-07T10:01:01.5818803Z strides: [972800, 1, 19456, 256], [2304, 1, 768, 256] 2025-09-07T10:01:01.5819455Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:01.5819739Z convolution 0.0172 ms 100.0% 2025-09-07T10:01:01.5820692Z triton_convolution2d_812 0.0533 ms 32.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:01.5822454Z triton_convolution2d_811 0.0700 ms 24.6% 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 2025-09-07T10:01:01.5823863Z triton_convolution2d_814 0.0723 ms 23.8% 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 2025-09-07T10:01:01.5825097Z triton_convolution2d_813 0.0749 ms 22.9% 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 2025-09-07T10:01:01.5826333Z triton_convolution2d_809 0.0977 ms 17.6% 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 2025-09-07T10:01:01.5827556Z triton_convolution2d_808 0.1047 ms 16.4% 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 2025-09-07T10:01:01.5828784Z triton_convolution2d_810 0.1826 ms 9.4% 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 2025-09-07T10:01:01.5829909Z SingleProcess AUTOTUNE benchmarking takes 0.1569 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:02.5805087Z Autotune Choices Stats: 2025-09-07T10:01:02.5806663Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_801", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.012927999719977379, "best_triton_pos": 0} 2025-09-07T10:01:02.5886646Z AUTOTUNE addmm(3800x256, 3800x1024, 1024x256) 2025-09-07T10:01:02.5887141Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:01:02.5887589Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:02.5888598Z triton_mm_801 0.0129 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:02.5889551Z bias_addmm 0.0132 ms 97.6% 2025-09-07T10:01:02.5890866Z triton_mm_807 0.0147 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:02.5892337Z triton_mm_796 0.0148 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:02.5893757Z triton_mm_800 0.0154 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:02.5895257Z triton_mm_797 0.0155 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 2025-09-07T10:01:02.5896703Z triton_mm_806 0.0164 ms 79.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:02.5897635Z addmm 0.0166 ms 78.0% 2025-09-07T10:01:02.5898501Z triton_mm_799 0.0168 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:02.5900554Z triton_mm_803 0.0171 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:02.5901803Z SingleProcess AUTOTUNE benchmarking takes 0.2847 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:01:03.1551882Z Autotune Choices Stats: 2025-09-07T10:01:03.1553716Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01158399973064661, "best_triton_pos": 1, "best_triton_time": 0.012768000364303589, "best_triton_kernel": "triton_mm_681", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T10:01:03.1632682Z AUTOTUNE mm(950x2048, 2048x512) 2025-09-07T10:01:03.1632975Z strides: [2048, 1], [1, 2048] 2025-09-07T10:01:03.1633263Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:03.1633540Z mm 0.0116 ms 100.0% 2025-09-07T10:01:03.1634175Z triton_mm_681 0.0128 ms 90.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:03.1635252Z triton_mm_685 0.0143 ms 81.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:03.1636304Z triton_mm_677 0.0169 ms 68.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:03.1637353Z triton_mm_691 0.0182 ms 63.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:03.1638398Z triton_mm_680 0.0196 ms 59.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:03.1639438Z triton_mm_684 0.0199 ms 58.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:03.1640744Z triton_mm_674 0.0218 ms 53.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:01:03.1641717Z triton_mm_676 0.0220 ms 52.8% 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 2025-09-07T10:01:03.1642683Z triton_mm_690 0.0220 ms 52.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:03.1643540Z SingleProcess AUTOTUNE benchmarking takes 0.2649 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:01:03.6109108Z Autotune Choices Stats: 2025-09-07T10:01:03.6111160Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014208000153303146, "best_triton_pos": 1, "best_triton_time": 0.05407999828457832, "best_triton_kernel": "triton_convolution2d_786", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:03.6191825Z AUTOTUNE convolution(1x256x25x38, 256x256x3x3) 2025-09-07T10:01:03.6192191Z strides: [243200, 1, 9728, 256], [2304, 1, 768, 256] 2025-09-07T10:01:03.6192528Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:03.6192816Z convolution 0.0142 ms 100.0% 2025-09-07T10:01:03.6193627Z triton_convolution2d_786 0.0541 ms 26.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:03.6195350Z triton_convolution2d_785 0.0708 ms 20.1% 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 2025-09-07T10:01:03.6197047Z triton_convolution2d_788 0.0732 ms 19.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:03.6198380Z triton_convolution2d_787 0.0745 ms 19.1% 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 2025-09-07T10:01:03.6199705Z triton_convolution2d_783 0.0982 ms 14.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:03.6201155Z triton_convolution2d_782 0.1064 ms 13.3% 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 2025-09-07T10:01:03.6202391Z triton_convolution2d_784 0.1993 ms 7.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:03.6203358Z SingleProcess AUTOTUNE benchmarking takes 0.1618 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:05.7396635Z Autotune Choices Stats: 2025-09-07T10:01:05.7398059Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.0939520001411438, "best_triton_pos": 1, "best_triton_time": 0.30108800530433655, "best_triton_kernel": "triton_convolution2d_0", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:05.7486630Z AUTOTUNE convolution(1x3x800x1216, 64x3x7x7) 2025-09-07T10:01:05.7486970Z strides: [2918400, 1, 3648, 3], [147, 1, 21, 3] 2025-09-07T10:01:05.7487279Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:05.7487592Z convolution 0.0940 ms 100.0% 2025-09-07T10:01:05.7488359Z triton_convolution2d_0 0.3011 ms 31.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:05.7489599Z triton_convolution2d_3 0.3078 ms 30.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:05.7491314Z triton_convolution2d_4 0.3385 ms 27.8% 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 2025-09-07T10:01:05.7492496Z triton_convolution2d_2 0.3651 ms 25.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:05.7493634Z triton_convolution2d_5 0.4126 ms 22.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:05.7494771Z triton_convolution2d_1 0.5193 ms 18.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=7, KERNEL_W=7, PADDING_H=3, PADDING_W=3, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:05.7496063Z SingleProcess AUTOTUNE benchmarking takes 0.2816 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T10:01:05.8622964Z Autotune Choices Stats: 2025-09-07T10:01:05.8624777Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.021536000072956085, "best_triton_pos": 1, "best_triton_time": 0.024512000381946564, "best_triton_kernel": "triton_convolution2d_27", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:01:05.8702199Z AUTOTUNE convolution(1x64x200x304, 64x64x3x3) 2025-09-07T10:01:05.8702544Z strides: [3891200, 1, 19456, 64], [576, 1, 192, 64] 2025-09-07T10:01:05.8702955Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:05.8703238Z convolution 0.0215 ms 100.0% 2025-09-07T10:01:05.8703993Z triton_convolution2d_27 0.0245 ms 87.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:05.8705247Z triton_convolution2d_30 0.0280 ms 77.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:05.8706469Z triton_convolution2d_28 0.0317 ms 67.9% 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 2025-09-07T10:01:05.8707673Z triton_convolution2d_29 0.0327 ms 65.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:05.8708885Z triton_convolution2d_25 0.0354 ms 60.8% 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 2025-09-07T10:01:05.8710113Z triton_convolution2d_24 0.0547 ms 39.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:05.8711760Z triton_convolution2d_26 0.0917 ms 23.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:05.8712737Z SingleProcess AUTOTUNE benchmarking takes 0.1205 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:05.9928215Z Autotune Choices Stats: 2025-09-07T10:01:05.9929590Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.020767999812960625, "best_triton_pos": 1, "best_triton_time": 0.035711999982595444, "best_triton_kernel": "triton_convolution2d_180", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:06.0008434Z AUTOTUNE convolution(1x128x200x304, 128x128x3x3) 2025-09-07T10:01:06.0008907Z strides: [7782400, 1, 38912, 128], [1152, 1, 384, 128] 2025-09-07T10:01:06.0009232Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.0009516Z convolution 0.0208 ms 100.0% 2025-09-07T10:01:06.0010425Z triton_convolution2d_180 0.0357 ms 58.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.0011701Z triton_convolution2d_181 0.0384 ms 54.1% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.0013169Z triton_convolution2d_182 0.0423 ms 49.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.0014570Z triton_convolution2d_179 0.0435 ms 47.8% 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 2025-09-07T10:01:06.0015910Z triton_convolution2d_176 0.0494 ms 42.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.0017154Z triton_convolution2d_177 0.0549 ms 37.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.0018401Z triton_convolution2d_178 0.1041 ms 20.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:06.0019385Z SingleProcess AUTOTUNE benchmarking takes 0.1243 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:06.1099729Z Autotune Choices Stats: 2025-09-07T10:01:06.1101387Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02131200022995472, "best_triton_pos": 1, "best_triton_time": 0.025087999179959297, "best_triton_kernel": "triton_convolution2d_207", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8"} 2025-09-07T10:01:06.1181434Z AUTOTUNE convolution(1x256x200x304, 512x256x1x1) 2025-09-07T10:01:06.1181809Z strides: [15564800, 1, 77824, 256], [256, 1, 256, 256] 2025-09-07T10:01:06.1182148Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.1182437Z convolution 0.0213 ms 100.0% 2025-09-07T10:01:06.1183309Z triton_convolution2d_207 0.0251 ms 84.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:01:06.1184585Z triton_convolution2d_205 0.0252 ms 84.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:01:06.1185859Z triton_convolution2d_206 0.0253 ms 84.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:01:06.1187109Z triton_convolution2d_208 0.0269 ms 79.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:01:06.1188351Z triton_convolution2d_202 0.0324 ms 65.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:01:06.1189584Z triton_convolution2d_203 0.0359 ms 59.3% 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 2025-09-07T10:01:06.1191050Z triton_convolution2d_204 0.0933 ms 22.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:01:06.1192028Z SingleProcess AUTOTUNE benchmarking takes 0.1162 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:06.2328896Z Autotune Choices Stats: 2025-09-07T10:01:06.2332082Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018303999677300453, "best_triton_pos": 1, "best_triton_time": 0.03171199932694435, "best_triton_kernel": "triton_convolution2d_232", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:06.2408995Z AUTOTUNE convolution(1x128x100x152, 128x128x3x3) 2025-09-07T10:01:06.2409554Z strides: [1945600, 1, 19456, 128], [1152, 1, 384, 128] 2025-09-07T10:01:06.2410020Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.2410629Z convolution 0.0183 ms 100.0% 2025-09-07T10:01:06.2411716Z triton_convolution2d_232 0.0317 ms 57.7% 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 2025-09-07T10:01:06.2413544Z triton_convolution2d_233 0.0350 ms 52.3% 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 2025-09-07T10:01:06.2415363Z triton_convolution2d_231 0.0407 ms 45.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.2417110Z triton_convolution2d_234 0.0417 ms 43.9% 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 2025-09-07T10:01:06.2418866Z triton_convolution2d_228 0.0467 ms 39.2% 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 2025-09-07T10:01:06.2420833Z triton_convolution2d_229 0.0505 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 2025-09-07T10:01:06.2422625Z triton_convolution2d_230 0.0947 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 2025-09-07T10:01:06.2424148Z SingleProcess AUTOTUNE benchmarking takes 0.1219 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:06.4037295Z Autotune Choices Stats: 2025-09-07T10:01:06.4038749Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.0180479995906353, "best_triton_pos": 1, "best_triton_time": 0.05584000051021576, "best_triton_kernel": "triton_convolution2d_367", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:06.4120602Z AUTOTUNE convolution(1x256x100x152, 256x256x3x3) 2025-09-07T10:01:06.4121048Z strides: [3891200, 1, 38912, 256], [2304, 1, 768, 256] 2025-09-07T10:01:06.4121431Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.4121761Z convolution 0.0180 ms 100.0% 2025-09-07T10:01:06.4122572Z triton_convolution2d_367 0.0558 ms 32.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.4123830Z triton_convolution2d_366 0.0711 ms 25.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.4125095Z triton_convolution2d_369 0.0722 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 2025-09-07T10:01:06.4126815Z triton_convolution2d_368 0.0788 ms 22.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.4128510Z triton_convolution2d_364 0.1023 ms 17.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.4129749Z triton_convolution2d_363 0.1056 ms 17.1% 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 2025-09-07T10:01:06.4131172Z triton_convolution2d_365 0.1910 ms 9.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:06.4132030Z SingleProcess AUTOTUNE benchmarking takes 0.1639 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:06.5184874Z Autotune Choices Stats: 2025-09-07T10:01:06.5187367Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.017376000061631203, "best_triton_pos": 1, "best_triton_time": 0.02070399932563305, "best_triton_kernel": "triton_convolution2d_393", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:01:06.5268316Z AUTOTUNE convolution(1x512x100x152, 1024x512x1x1) 2025-09-07T10:01:06.5268857Z strides: [7782400, 1, 77824, 512], [512, 1, 512, 512] 2025-09-07T10:01:06.5269319Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.5269739Z convolution 0.0174 ms 100.0% 2025-09-07T10:01:06.5271028Z triton_convolution2d_393 0.0207 ms 83.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:01:06.5272877Z triton_convolution2d_392 0.0215 ms 80.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:01:06.5274713Z triton_convolution2d_394 0.0221 ms 78.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:01:06.5276523Z triton_convolution2d_395 0.0229 ms 75.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=8 2025-09-07T10:01:06.5278323Z triton_convolution2d_389 0.0284 ms 61.3% 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 2025-09-07T10:01:06.5280132Z triton_convolution2d_390 0.0293 ms 59.3% 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 2025-09-07T10:01:06.5282221Z triton_convolution2d_391 0.0897 ms 19.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:01:06.5283661Z SingleProcess AUTOTUNE benchmarking takes 0.1136 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:06.7464038Z Autotune Choices Stats: 2025-09-07T10:01:06.7465185Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018079999834299088, "best_triton_pos": 1, "best_triton_time": 0.10943999886512756, "best_triton_kernel": "triton_convolution2d_644", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:06.7547048Z AUTOTUNE convolution(1x512x50x76, 512x512x3x3) 2025-09-07T10:01:06.7547917Z strides: [1945600, 1, 38912, 512], [4608, 1, 1536, 512] 2025-09-07T10:01:06.7548251Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.7548532Z convolution 0.0181 ms 100.0% 2025-09-07T10:01:06.7549290Z triton_convolution2d_644 0.1094 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.7550945Z triton_convolution2d_643 0.1328 ms 13.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.7552068Z triton_convolution2d_646 0.1336 ms 13.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:06.7553160Z triton_convolution2d_645 0.1416 ms 12.8% 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 2025-09-07T10:01:06.7554228Z triton_convolution2d_641 0.1974 ms 9.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.7555285Z triton_convolution2d_640 0.2036 ms 8.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:06.7556356Z triton_convolution2d_642 0.3945 ms 4.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:06.7557203Z SingleProcess AUTOTUNE benchmarking takes 0.2102 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:06.8660135Z Autotune Choices Stats: 2025-09-07T10:01:06.8662515Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.019200000911951065, "best_triton_pos": 1, "best_triton_time": 0.029023999348282814, "best_triton_kernel": "triton_convolution2d_670", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4"} 2025-09-07T10:01:06.8741855Z AUTOTUNE convolution(1x1024x50x76, 2048x1024x1x1) 2025-09-07T10:01:06.8742417Z strides: [3891200, 1, 77824, 1024], [1024, 1, 1024, 1024] 2025-09-07T10:01:06.8742961Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:06.8743335Z convolution 0.0192 ms 100.0% 2025-09-07T10:01:06.8744366Z triton_convolution2d_670 0.0290 ms 66.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:01:06.8746125Z triton_convolution2d_669 0.0331 ms 58.0% 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 2025-09-07T10:01:06.8747854Z triton_convolution2d_672 0.0334 ms 57.5% 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 2025-09-07T10:01:06.8749967Z triton_convolution2d_671 0.0338 ms 56.8% 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 2025-09-07T10:01:06.8751865Z triton_convolution2d_667 0.0444 ms 43.3% 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 2025-09-07T10:01:06.8753951Z triton_convolution2d_666 0.0462 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=2, STRIDE_W=2, UNROLL=True, num_stages=2, num_warps=4 2025-09-07T10:01:06.8755665Z triton_convolution2d_668 0.0911 ms 21.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=1, KERNEL_W=1, PADDING_H=0, PADDING_W=0, STRIDE_H=2, STRIDE_W=2, UNROLL=True, num_stages=1, num_warps=8 2025-09-07T10:01:06.8757019Z SingleProcess AUTOTUNE benchmarking takes 0.1183 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:07.0764209Z Autotune Choices Stats: 2025-09-07T10:01:07.0765672Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.018592000007629395, "best_triton_pos": 1, "best_triton_time": 0.10899200290441513, "best_triton_kernel": "triton_convolution2d_696", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:07.0847316Z AUTOTUNE convolution(1x512x25x38, 512x512x3x3) 2025-09-07T10:01:07.0847685Z strides: [486400, 1, 19456, 512], [4608, 1, 1536, 512] 2025-09-07T10:01:07.0848031Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:07.0848317Z convolution 0.0186 ms 100.0% 2025-09-07T10:01:07.0849116Z triton_convolution2d_696 0.1090 ms 17.1% 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 2025-09-07T10:01:07.0850813Z triton_convolution2d_695 0.1305 ms 14.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:07.0852038Z triton_convolution2d_697 0.1394 ms 13.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:07.0853191Z triton_convolution2d_698 0.1431 ms 13.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:07.0854336Z triton_convolution2d_693 0.1946 ms 9.6% 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 2025-09-07T10:01:07.0855483Z triton_convolution2d_692 0.2029 ms 9.2% 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 2025-09-07T10:01:07.0856627Z triton_convolution2d_694 0.3801 ms 4.9% 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 2025-09-07T10:01:07.0857536Z SingleProcess AUTOTUNE benchmarking takes 0.2098 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:07.3716726Z Autotune Choices Stats: 2025-09-07T10:01:07.3717988Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.011776000261306763, "best_triton_pos": 1, "best_triton_time": 0.011807999573647976, "best_triton_kernel": "triton_mm_767", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T10:01:07.3799206Z AUTOTUNE addmm(950x256, 950x2048, 2048x256) 2025-09-07T10:01:07.3799597Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T10:01:07.3799913Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:07.3800686Z bias_addmm 0.0118 ms 100.0% 2025-09-07T10:01:07.3801679Z triton_mm_767 0.0118 ms 99.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:07.3802804Z triton_mm_771 0.0126 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:07.3803799Z triton_mm_775 0.0144 ms 81.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:07.3804447Z addmm 0.0151 ms 78.0% 2025-09-07T10:01:07.3805038Z triton_mm_781 0.0184 ms 64.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:07.3806039Z triton_mm_766 0.0185 ms 63.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:07.3807031Z triton_mm_765 0.0187 ms 62.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:07.3808005Z triton_mm_764 0.0192 ms 61.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:01:07.3808967Z triton_mm_770 0.0192 ms 61.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:07.3809823Z SingleProcess AUTOTUNE benchmarking takes 0.2908 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:01:17.4886158Z W0907 10:01:17.485000 118496 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T10:01:17.4886889Z W0907 10:01:17.487000 118496 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T10:01:17.4887713Z W0907 10:01:17.487000 118496 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T10:01:17.4921359Z W0907 10:01:17.488000 118496 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T10:01:17.4922033Z W0907 10:01:17.489000 118496 site-packages/torch/_inductor/utils.py:2298] [4/0_1] DeviceCopy in input program 2025-09-07T10:01:18.3046535Z Autotune Choices Stats: 2025-09-07T10:01:18.3047640Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_884", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.021056000143289566, "best_triton_pos": 0} 2025-09-07T10:01:18.3133455Z AUTOTUNE addmm(60800x3, 60800x256, 256x3) 2025-09-07T10:01:18.3133757Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:18.3134101Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:18.3134826Z triton_mm_884 0.0211 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:18.3135835Z triton_mm_878 0.0212 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:18.3136821Z triton_mm_889 0.0216 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:18.3138153Z triton_mm_881 0.0221 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.3139583Z triton_mm_875 0.0223 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:18.3141515Z triton_mm_888 0.0224 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.3142502Z triton_mm_877 0.0243 ms 86.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:18.3143601Z triton_mm_880 0.0246 ms 85.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:01:18.3144674Z triton_mm_882 0.0249 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.3145587Z triton_mm_885 0.0251 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.3146383Z SingleProcess AUTOTUNE benchmarking takes 0.2412 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:18.5410808Z Autotune Choices Stats: 2025-09-07T10:01:18.5411798Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_894", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.020735999569296837, "best_triton_pos": 0} 2025-09-07T10:01:18.5493104Z AUTOTUNE addmm(60800x12, 60800x256, 256x12) 2025-09-07T10:01:18.5493398Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:18.5493709Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:18.5494402Z triton_mm_894 0.0207 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:18.5495411Z triton_mm_900 0.0208 ms 99.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:18.5496394Z triton_mm_905 0.0215 ms 96.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:18.5497391Z triton_mm_891 0.0217 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:18.5498371Z triton_mm_897 0.0219 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.5499348Z triton_mm_904 0.0219 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.5500520Z triton_mm_898 0.0235 ms 88.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.5501494Z triton_mm_899 0.0239 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:18.5502660Z triton_mm_896 0.0239 ms 86.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:01:18.5503745Z triton_mm_893 0.0242 ms 85.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:18.5504795Z SingleProcess AUTOTUNE benchmarking takes 0.2354 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:18.7799599Z Autotune Choices Stats: 2025-09-07T10:01:18.7800810Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_923", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.010751999914646149, "best_triton_pos": 0} 2025-09-07T10:01:18.7881406Z AUTOTUNE addmm(15200x3, 15200x256, 256x3) 2025-09-07T10:01:18.7881708Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:18.7882010Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:18.7882701Z triton_mm_923 0.0108 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:18.7883701Z triton_mm_917 0.0108 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:18.7884844Z triton_mm_928 0.0109 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:18.7885963Z triton_mm_920 0.0110 ms 98.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.7886982Z triton_mm_927 0.0112 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.7887984Z triton_mm_916 0.0113 ms 95.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:18.7888978Z triton_mm_921 0.0113 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:18.7889968Z triton_mm_922 0.0115 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:18.7891178Z triton_mm_925 0.0116 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:18.7892188Z triton_mm_914 0.0117 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:18.7893062Z SingleProcess AUTOTUNE benchmarking takes 0.2355 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:19.0154361Z Autotune Choices Stats: 2025-09-07T10:01:19.0155398Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_930", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2", "best_time": 0.010463999584317207, "best_triton_pos": 0} 2025-09-07T10:01:19.0235048Z AUTOTUNE addmm(15200x12, 15200x256, 256x12) 2025-09-07T10:01:19.0235390Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:19.0235721Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:19.0236457Z triton_mm_930 0.0105 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:19.0237792Z triton_mm_936 0.0105 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.0239049Z triton_mm_939 0.0106 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.0240189Z triton_mm_933 0.0106 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.0241425Z triton_mm_943 0.0108 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.0242454Z triton_mm_944 0.0108 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:19.0243481Z triton_mm_938 0.0109 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.0244501Z triton_mm_932 0.0111 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.0245526Z triton_mm_937 0.0112 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.0246561Z triton_mm_941 0.0115 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:19.0247470Z SingleProcess AUTOTUNE benchmarking takes 0.2349 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:19.2539140Z Autotune Choices Stats: 2025-09-07T10:01:19.2540190Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_956", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.008224000222980976, "best_triton_pos": 0} 2025-09-07T10:01:19.2625103Z AUTOTUNE addmm(3800x3, 3800x256, 256x3) 2025-09-07T10:01:19.2625400Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:19.2625721Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:19.2626452Z triton_mm_956 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.2627490Z triton_mm_955 0.0084 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.2628512Z triton_mm_959 0.0084 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.2629529Z triton_mm_953 0.0086 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:19.2630695Z triton_mm_954 0.0087 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:01:19.2631725Z triton_mm_962 0.0087 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.2632738Z triton_mm_961 0.0088 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.2634003Z triton_mm_966 0.0088 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.2635224Z triton_mm_967 0.0088 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:19.2636364Z triton_mm_964 0.0092 ms 89.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:19.2637260Z SingleProcess AUTOTUNE benchmarking takes 0.2356 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:19.4960890Z Autotune Choices Stats: 2025-09-07T10:01:19.4961904Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_978", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.0080960001796484, "best_triton_pos": 0} 2025-09-07T10:01:19.5049207Z AUTOTUNE addmm(3800x12, 3800x256, 256x12) 2025-09-07T10:01:19.5049516Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:19.5049841Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:19.5050715Z triton_mm_978 0.0081 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.5051755Z triton_mm_972 0.0082 ms 98.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.5052745Z triton_mm_971 0.0083 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.5053704Z triton_mm_975 0.0083 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.5054760Z triton_mm_970 0.0085 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:01:19.5055662Z triton_mm_983 0.0085 ms 94.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:19.5056557Z triton_mm_969 0.0087 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:19.5057451Z triton_mm_982 0.0087 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.5058343Z triton_mm_977 0.0088 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.5059228Z triton_mm_980 0.0089 ms 91.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:19.5060008Z SingleProcess AUTOTUNE benchmarking takes 0.2419 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:19.7358951Z Autotune Choices Stats: 2025-09-07T10:01:19.7359913Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_1001", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.00723200011998415, "best_triton_pos": 0} 2025-09-07T10:01:19.7553660Z AUTOTUNE addmm(950x3, 950x256, 256x3) 2025-09-07T10:01:19.7553939Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:19.7554289Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:19.7555080Z triton_mm_1001 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.7556478Z triton_mm_995 0.0074 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.7557451Z triton_mm_993 0.0076 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:01:19.7558408Z triton_mm_992 0.0077 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:19.7559375Z triton_mm_994 0.0078 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.7560491Z triton_mm_998 0.0078 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.7561458Z triton_mm_1006 0.0079 ms 91.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:19.7562419Z triton_mm_1000 0.0079 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.7563375Z triton_mm_1005 0.0079 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.7564340Z triton_mm_999 0.0087 ms 83.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.7565164Z SingleProcess AUTOTUNE benchmarking takes 0.2470 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:19.9831050Z Autotune Choices Stats: 2025-09-07T10:01:19.9832141Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_1011", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.00723200011998415, "best_triton_pos": 0} 2025-09-07T10:01:19.9916710Z AUTOTUNE addmm(950x12, 950x256, 256x12) 2025-09-07T10:01:19.9917032Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:19.9917386Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:19.9918224Z triton_mm_1011 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.9919407Z triton_mm_1017 0.0073 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.9920806Z triton_mm_1010 0.0075 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:19.9921969Z triton_mm_1009 0.0076 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:01:19.9923120Z triton_mm_1014 0.0076 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.9924408Z triton_mm_1022 0.0077 ms 94.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:19.9925583Z triton_mm_1021 0.0078 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:19.9926993Z triton_mm_1016 0.0079 ms 91.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:19.9928147Z triton_mm_1008 0.0080 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:19.9929307Z triton_mm_1019 0.0083 ms 86.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:19.9930446Z SingleProcess AUTOTUNE benchmarking takes 0.2359 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:20.1334543Z Autotune Choices Stats: 2025-09-07T10:01:20.1336021Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.013791999779641628, "best_triton_pos": 1, "best_triton_time": 0.053727999329566956, "best_triton_kernel": "triton_convolution2d_1027", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:01:20.1418932Z AUTOTUNE convolution(1x256x13x19, 256x256x3x3) 2025-09-07T10:01:20.1419266Z strides: [63232, 1, 4864, 256], [2304, 1, 768, 256] 2025-09-07T10:01:20.1419579Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:20.1419858Z convolution 0.0138 ms 100.0% 2025-09-07T10:01:20.1420965Z triton_convolution2d_1027 0.0537 ms 25.7% 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 2025-09-07T10:01:20.1422281Z triton_convolution2d_1026 0.0715 ms 19.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:20.1423691Z triton_convolution2d_1029 0.0742 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=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:20.1425172Z triton_convolution2d_1028 0.0759 ms 18.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:01:20.1426520Z triton_convolution2d_1025 0.1023 ms 13.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:01:20.1427865Z triton_convolution2d_1024 0.1024 ms 13.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:20.1429218Z triton_convolution2d_1023 0.1083 ms 12.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:01:20.1430392Z SingleProcess AUTOTUNE benchmarking takes 0.1498 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:01:20.3727167Z Autotune Choices Stats: 2025-09-07T10:01:20.3728226Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_1040", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.0071680000983178616, "best_triton_pos": 0} 2025-09-07T10:01:20.3815011Z AUTOTUNE addmm(247x3, 247x256, 256x3) 2025-09-07T10:01:20.3815348Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:20.3815808Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:20.3816688Z triton_mm_1040 0.0072 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:20.3817722Z triton_mm_1034 0.0073 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:20.3818769Z triton_mm_1031 0.0074 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:20.3819771Z triton_mm_1032 0.0074 ms 96.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:01:20.3821098Z triton_mm_1037 0.0075 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:20.3822087Z triton_mm_1033 0.0075 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:20.3823168Z triton_mm_1039 0.0078 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:20.3824168Z triton_mm_1044 0.0079 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:20.3825383Z triton_mm_1045 0.0079 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:20.3826429Z triton_mm_1038 0.0084 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:20.3827343Z SingleProcess AUTOTUNE benchmarking takes 0.2388 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:20.6167401Z Autotune Choices Stats: 2025-09-07T10:01:20.6168577Z {"num_choices": 18, "num_triton_choices": 16, "best_kernel": "triton_mm_1050", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.007007999811321497, "best_triton_pos": 0} 2025-09-07T10:01:20.6255450Z AUTOTUNE addmm(247x12, 247x256, 256x12) 2025-09-07T10:01:20.6255785Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:01:20.6256109Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:20.6256822Z triton_mm_1050 0.0070 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:20.6257866Z triton_mm_1056 0.0071 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:20.6258876Z triton_mm_1048 0.0073 ms 96.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=2 2025-09-07T10:01:20.6259866Z triton_mm_1049 0.0074 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:20.6261181Z triton_mm_1053 0.0074 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:20.6262191Z triton_mm_1060 0.0075 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:20.6263525Z triton_mm_1047 0.0076 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=2 2025-09-07T10:01:20.6264610Z triton_mm_1061 0.0076 ms 91.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:20.6265767Z triton_mm_1055 0.0077 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:20.6266807Z triton_mm_1058 0.0082 ms 85.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=16, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:20.6267723Z SingleProcess AUTOTUNE benchmarking takes 0.2436 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:01:20.6302563Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:01:20.6303376Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:01:20.6304023Z anchors = self.anchor_generator(images, features) 2025-09-07T10:01:20.6304795Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:01:20.6305486Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:01:20.6306195Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:01:20.6307046Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6307859Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:01:20.6308668Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6309038Z 2025-09-07T10:01:20.6309204Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:01:20.6309860Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:01:20.6310663Z anchors = self.anchor_generator(images, features) 2025-09-07T10:01:20.6311346Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:01:20.6312033Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:01:20.6312740Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:01:20.6313572Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6314387Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:01:20.6315190Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6315521Z 2025-09-07T10:01:20.6315669Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:01:20.6316160Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:01:20.6316650Z anchors = self.anchor_generator(images, features) 2025-09-07T10:01:20.6317410Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:01:20.6317940Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:01:20.6318481Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:01:20.6319384Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6320015Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:01:20.6320811Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6321094Z 2025-09-07T10:01:20.6321231Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:01:20.6321742Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:01:20.6322230Z anchors = self.anchor_generator(images, features) 2025-09-07T10:01:20.6322771Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:01:20.6323293Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:01:20.6323838Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:01:20.6324475Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6325111Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:01:20.6325724Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6326006Z 2025-09-07T10:01:20.6326134Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:01:20.6326638Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:01:20.6327122Z anchors = self.anchor_generator(images, features) 2025-09-07T10:01:20.6327621Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:01:20.6328156Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:01:20.6328688Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:01:20.6329316Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6329920Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:01:20.6330639Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:01:20.6330933Z 2025-09-07T10:01:20.6471382Z cudagraph partition into 2 partitions 2025-09-07T10:01:23.9143675Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T10:01:23.9144733Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T10:01:23.9145530Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] or: 2025-09-07T10:01:23.9146288Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T10:01:23.9147166Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] to include these operations in the captured graph. 2025-09-07T10:01:23.9147882Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:01:23.9149076Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break: from user code at: 2025-09-07T10:01:23.9151619Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T10:01:23.9153335Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T10:01:23.9154651Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T10:01:23.9155894Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T10:01:23.9156896Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T10:01:23.9157846Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T10:01:23.9158807Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T10:01:23.9159820Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T10:01:23.9160985Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T10:01:23.9161998Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T10:01:23.9163015Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T10:01:23.9164011Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T10:01:23.9164661Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:01:23.9165145Z W0907 10:01:23.913000 118496 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:01:24.1642644Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:01:24.1643430Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T10:01:24.1644201Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T10:01:24.1644527Z 2025-09-07T10:01:24.4171471Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:01:24.4172311Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T10:01:24.4173133Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T10:01:24.4173456Z 2025-09-07T10:01:31.2296204Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:01:31.2297570Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:01:31.2298250Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:01:31.2298732Z return fn(*args[2:], **kwargs) 2025-09-07T10:01:31.2299595Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:01:31.2300170Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:01:31.2301151Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:01:31.2301638Z v4 = masked_index(y_high, x_high) 2025-09-07T10:01:31.2302087Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:01:31.2302522Z return input[ 2025-09-07T10:01:31.2302626Z 2025-09-07T10:01:31.2302630Z 2025-09-07T10:01:34.6479607Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:01:34.6481468Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:01:34.6482338Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:01:34.6482980Z return fn(*args[2:], **kwargs) 2025-09-07T10:01:34.6483537Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:01:34.6484274Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:01:34.6485063Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:01:34.6485679Z v4 = masked_index(y_high, x_high) 2025-09-07T10:01:34.6486228Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:01:34.6486768Z return input[ 2025-09-07T10:01:34.6486900Z 2025-09-07T10:01:34.6486909Z 2025-09-07T10:01:38.2195238Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:01:38.2196643Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:01:38.2197500Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:01:38.2198147Z return fn(*args[2:], **kwargs) 2025-09-07T10:01:38.2198721Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:01:38.2199473Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:01:38.2200785Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:01:38.2201394Z v4 = masked_index(y_high, x_high) 2025-09-07T10:01:38.2201915Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:01:38.2202437Z return input[ 2025-09-07T10:01:38.2202566Z 2025-09-07T10:01:38.2202570Z 2025-09-07T10:01:40.4787078Z Autotune Choices Stats: 2025-09-07T10:01:40.4788892Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.050464000552892685, "best_triton_pos": 1, "best_triton_time": 0.05270399898290634, "best_triton_kernel": "triton_mm_1074", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:01:40.4879867Z AUTOTUNE mm(1000x12544, 12544x1024) 2025-09-07T10:01:40.4881683Z strides: [12544, 1], [1, 12544] 2025-09-07T10:01:40.4882252Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:40.4882535Z mm 0.0505 ms 100.0% 2025-09-07T10:01:40.4883153Z triton_mm_1074 0.0527 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:40.4884170Z triton_mm_1080 0.0718 ms 70.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:40.4885147Z triton_mm_1070 0.0769 ms 65.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:40.4886132Z triton_mm_1073 0.0957 ms 52.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:40.4887101Z triton_mm_1069 0.0980 ms 51.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:40.4888064Z triton_mm_1079 0.1039 ms 48.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:40.4889028Z triton_mm_1072 0.1183 ms 42.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:40.4889990Z triton_mm_1076 0.1190 ms 42.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:40.4891175Z triton_mm_1066 0.1227 ms 41.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:40.4891962Z SingleProcess AUTOTUNE benchmarking takes 0.6038 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:01:41.6502151Z Autotune Choices Stats: 2025-09-07T10:01:41.6503583Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01104000024497509, "best_triton_pos": 1, "best_triton_time": 0.011296000331640244, "best_triton_kernel": "triton_mm_1093", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:01:41.6589727Z AUTOTUNE mm(1000x1024, 1024x1024) 2025-09-07T10:01:41.6590015Z strides: [1024, 1], [1, 1024] 2025-09-07T10:01:41.6590501Z dtypes: torch.float16, torch.float16 2025-09-07T10:01:41.6590843Z mm 0.0110 ms 100.0% 2025-09-07T10:01:41.6591535Z triton_mm_1093 0.0113 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:41.6592654Z triton_mm_1099 0.0133 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:41.6593722Z triton_mm_1092 0.0137 ms 80.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:41.6594775Z triton_mm_1088 0.0138 ms 79.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:41.6596151Z triton_mm_1089 0.0138 ms 79.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:41.6597209Z triton_mm_1098 0.0147 ms 75.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:41.6598609Z triton_mm_1091 0.0153 ms 72.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:41.6599671Z triton_mm_1095 0.0154 ms 71.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:41.6600904Z triton_mm_1094 0.0185 ms 59.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:41.6601756Z SingleProcess AUTOTUNE benchmarking takes 0.2535 seconds and 0.5531 seconds precompiling for 20 choices 2025-09-07T10:01:43.4669709Z Autotune Choices Stats: 2025-09-07T10:01:43.4671175Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_1104", "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": 0.010048000141978264, "best_triton_pos": 0} 2025-09-07T10:01:43.4755752Z AUTOTUNE addmm(1000x91, 1000x1024, 1024x91) 2025-09-07T10:01:43.4756170Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:01:43.4756478Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:43.4757202Z triton_mm_1104 0.0100 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:43.4758248Z triton_mm_1108 0.0109 ms 92.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:43.4759236Z triton_mm_1112 0.0127 ms 79.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:43.4760373Z triton_mm_1103 0.0129 ms 78.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:43.4761370Z triton_mm_1102 0.0132 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:43.4762335Z triton_mm_1107 0.0134 ms 75.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:43.4763246Z triton_mm_1101 0.0137 ms 73.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:01:43.4764154Z triton_mm_1111 0.0142 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 2025-09-07T10:01:43.4765064Z triton_mm_1118 0.0154 ms 65.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:43.4765961Z triton_mm_1110 0.0158 ms 63.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:43.4766747Z SingleProcess AUTOTUNE benchmarking takes 0.2714 seconds and 0.3530 seconds precompiling for 21 choices 2025-09-07T10:01:43.7360058Z Autotune Choices Stats: 2025-09-07T10:01:43.7361209Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_1127", "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": 0.010495999827980995, "best_triton_pos": 0} 2025-09-07T10:01:43.7446242Z AUTOTUNE addmm(1000x364, 1000x1024, 1024x364) 2025-09-07T10:01:43.7446888Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:01:43.7447214Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:01:43.7447949Z triton_mm_1127 0.0105 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:43.7448983Z triton_mm_1131 0.0121 ms 86.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:01:43.7449968Z triton_mm_1126 0.0132 ms 79.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:01:43.7451171Z triton_mm_1123 0.0132 ms 79.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:01:43.7452207Z triton_mm_1130 0.0140 ms 75.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:01:43.7453128Z triton_mm_1137 0.0141 ms 74.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:43.7454030Z triton_mm_1120 0.0141 ms 74.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:01:43.7454925Z triton_mm_1122 0.0149 ms 70.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:01:43.7455818Z triton_mm_1129 0.0153 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 2025-09-07T10:01:43.7456728Z triton_mm_1133 0.0153 ms 68.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:01:43.7457506Z SingleProcess AUTOTUNE benchmarking takes 0.2685 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:01:55.7843124Z W0907 10:01:55.783000 118496 site-packages/torch/fx/experimental/symbolic_shapes.py:2396] [30/4] RecursionError in sympy.xreplace(Eq(Mod(2*s29, s93), 0), {s29: evaluate_static_shape_0 + 1, s93: evaluate_static_shape_1 + 1}) 2025-09-07T10:01:56.7298700Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:01:56.7299791Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:01:56.7300905Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:01:56.7301408Z return fn(*args[2:], **kwargs) 2025-09-07T10:01:56.7301860Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:01:56.7302449Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:01:56.7303162Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:01:56.7303947Z v4 = masked_index(y_high, x_high) 2025-09-07T10:01:56.7304393Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:01:56.7304839Z return input[ 2025-09-07T10:01:56.7305101Z 2025-09-07T10:01:56.7305105Z 2025-09-07T10:02:02.3583813Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:02:02.3585133Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:02:02.3585958Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:02:02.3586621Z return fn(*args[2:], **kwargs) 2025-09-07T10:02:02.3587247Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:02.3587939Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:02.3588685Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:02.3589270Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:02.3589781Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:02.3590648Z return input[ 2025-09-07T10:02:02.3590780Z 2025-09-07T10:02:02.3590783Z 2025-09-07T10:02:09.7224859Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:02:09.7226196Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:02:09.7227015Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:02:09.7227609Z return fn(*args[2:], **kwargs) 2025-09-07T10:02:09.7228170Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:09.7228963Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:09.7229760Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:09.7230507Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:09.7231031Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:09.7231550Z return input[ 2025-09-07T10:02:09.7231681Z 2025-09-07T10:02:09.7231685Z 2025-09-07T10:02:12.9006140Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:02:12.9007600Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:02:12.9008465Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:02:12.9009087Z return fn(*args[2:], **kwargs) 2025-09-07T10:02:12.9009661Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:12.9010513Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:12.9011523Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:12.9012065Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:12.9012549Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:12.9013195Z return input[ 2025-09-07T10:02:12.9013318Z 2025-09-07T10:02:12.9013322Z 2025-09-07T10:02:13.9545816Z Autotune Choices Stats: 2025-09-07T10:02:13.9547395Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.01414399966597557, "best_triton_pos": 1, "best_triton_time": 0.0530879981815815, "best_triton_kernel": "triton_convolution2d_1142", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:02:13.9711305Z AUTOTUNE convolution(4x256x14x14, 256x256x3x3) 2025-09-07T10:02:13.9711724Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T10:02:13.9712084Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:13.9712404Z convolution 0.0141 ms 100.0% 2025-09-07T10:02:13.9713323Z triton_convolution2d_1142 0.0531 ms 26.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:02:13.9714837Z triton_convolution2d_1141 0.0695 ms 20.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:02:13.9716330Z triton_convolution2d_1144 0.0711 ms 19.9% 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 2025-09-07T10:02:13.9717813Z triton_convolution2d_1143 0.0734 ms 19.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:02:13.9719296Z triton_convolution2d_1139 0.0908 ms 15.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:02:13.9721051Z triton_convolution2d_1138 0.1037 ms 13.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:02:13.9722417Z triton_convolution2d_1140 0.1846 ms 7.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:02:13.9723485Z SingleProcess AUTOTUNE benchmarking takes 0.1814 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T10:02:15.1948763Z Autotune Choices Stats: 2025-09-07T10:02:15.1949868Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_1174", "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": 0.009184000082314014, "best_triton_pos": 0} 2025-09-07T10:02:15.2981487Z AUTOTUNE addmm(3136x91, 3136x256, 256x91) 2025-09-07T10:02:15.2981764Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:02:15.2982050Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:02:15.2982778Z triton_mm_1174 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 2025-09-07T10:02:15.2983690Z triton_mm_1173 0.0094 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:02:15.2984843Z triton_mm_1167 0.0096 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:02:15.2986002Z triton_mm_1169 0.0099 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:15.2986978Z triton_mm_1177 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 2025-09-07T10:02:15.2987867Z triton_mm_1168 0.0103 ms 89.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:15.2988755Z triton_mm_1178 0.0104 ms 88.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:15.2989652Z triton_mm_1176 0.0107 ms 86.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:15.2990852Z triton_mm_1180 0.0107 ms 85.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:15.2991698Z triton_mm_1170 0.0109 ms 84.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:15.2992441Z SingleProcess AUTOTUNE benchmarking takes 0.3723 seconds and 0.9440 seconds precompiling for 21 choices 2025-09-07T10:02:20.1595278Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 418, in torch_dynamo_resume_in_paste_mask_in_image_at_410 2025-09-07T10:02:20.1596618Z mask = F.interpolate(mask, size=(h, w), mode="bilinear", align_corners=False) 2025-09-07T10:02:20.1596942Z 2025-09-07T10:02:20.1596945Z 2025-09-07T10:02:21.0457109Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 418, in torch_dynamo_resume_in_paste_mask_in_image_at_410 2025-09-07T10:02:21.0458331Z mask = F.interpolate(mask, size=(h, w), mode="bilinear", align_corners=False) 2025-09-07T10:02:21.0458630Z 2025-09-07T10:02:21.0458635Z 2025-09-07T10:02:22.4491142Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 823, in torch_dynamo_resume_in_forward_at_806 2025-09-07T10:02:22.4492460Z masks_probs = maskrcnn_inference(mask_logits, labels) 2025-09-07T10:02:22.4493131Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 79, in maskrcnn_inference 2025-09-07T10:02:22.4493746Z mask_prob = mask_prob[index, labels][:, None] 2025-09-07T10:02:22.4493947Z 2025-09-07T10:02:22.4493962Z 2025-09-07T10:02:27.0804044Z Autotune Choices Stats: 2025-09-07T10:02:27.0805879Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.04499199986457825, "best_triton_pos": 1, "best_triton_time": 0.04822399839758873, "best_triton_kernel": "triton_mm_1334", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:02:27.1267961Z AUTOTUNE mm(1024x1000, 1000x12544) 2025-09-07T10:02:27.1268776Z strides: [1, 1024], [12544, 1] 2025-09-07T10:02:27.1269148Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:27.1269551Z mm 0.0450 ms 100.0% 2025-09-07T10:02:27.1270938Z triton_mm_1334 0.0482 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.1273072Z triton_mm_1335 0.0514 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.1274571Z triton_mm_1336 0.0617 ms 72.9% 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 2025-09-07T10:02:27.1276097Z triton_mm_1327 0.0626 ms 71.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.1277605Z triton_mm_1331 0.0645 ms 69.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.1279086Z triton_mm_1329 0.0667 ms 67.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.1280831Z triton_mm_1332 0.0694 ms 64.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:27.1282346Z triton_mm_1328 0.0697 ms 64.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:27.1283841Z triton_mm_1330 0.0809 ms 55.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:27.1285150Z SingleProcess AUTOTUNE benchmarking takes 0.4448 seconds and 0.8754 seconds precompiling for 20 choices 2025-09-07T10:02:27.5458450Z Autotune Choices Stats: 2025-09-07T10:02:27.5460666Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010975999757647514, "best_triton_pos": 1, "best_triton_time": 0.011455999687314034, "best_triton_kernel": "triton_mm_1292", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:02:27.5777506Z AUTOTUNE mm(1024x1000, 1000x1024) 2025-09-07T10:02:27.5777921Z strides: [1, 1024], [1024, 1] 2025-09-07T10:02:27.5778297Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:27.5778677Z mm 0.0110 ms 100.0% 2025-09-07T10:02:27.5779558Z triton_mm_1292 0.0115 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:27.5781296Z triton_mm_1298 0.0136 ms 80.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:27.5782855Z triton_mm_1291 0.0141 ms 78.0% 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 2025-09-07T10:02:27.5784328Z triton_mm_1288 0.0142 ms 77.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:27.5785777Z triton_mm_1287 0.0144 ms 76.4% 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 2025-09-07T10:02:27.5787230Z triton_mm_1294 0.0149 ms 73.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:27.5788988Z triton_mm_1290 0.0151 ms 72.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:27.5791042Z triton_mm_1297 0.0153 ms 71.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.5792709Z triton_mm_1289 0.0183 ms 60.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.5794003Z SingleProcess AUTOTUNE benchmarking takes 0.2433 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:02:27.7889703Z Autotune Choices Stats: 2025-09-07T10:02:27.7891749Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1253", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.008128000423312187, "best_triton_pos": 0} 2025-09-07T10:02:27.8043150Z AUTOTUNE mm(1000x91, 91x1024) 2025-09-07T10:02:27.8043562Z strides: [91, 1], [1024, 1] 2025-09-07T10:02:27.8043949Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:27.8044920Z triton_mm_1253 0.0081 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 2025-09-07T10:02:27.8046414Z triton_mm_1252 0.0083 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:27.8047872Z triton_mm_1254 0.0083 ms 98.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:27.8049371Z triton_mm_1249 0.0083 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:02:27.8051049Z triton_mm_1250 0.0084 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:27.8052555Z triton_mm_1251 0.0084 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.8054022Z triton_mm_1255 0.0087 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:27.8055492Z triton_mm_1244 0.0088 ms 92.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:27.8057023Z triton_mm_1256 0.0089 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:27.8058542Z triton_mm_1248 0.0092 ms 88.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:02:27.8059844Z SingleProcess AUTOTUNE benchmarking takes 0.2043 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:02:28.7305010Z Autotune Choices Stats: 2025-09-07T10:02:28.7306309Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011231999844312668, "best_triton_pos": 1, "best_triton_time": 0.011487999930977821, "best_triton_kernel": "triton_mm_1273", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:02:28.7698288Z AUTOTUNE mm(1000x1024, 1024x1024) 2025-09-07T10:02:28.7698552Z strides: [1024, 1], [1024, 1] 2025-09-07T10:02:28.7698782Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:28.7699009Z mm 0.0112 ms 100.0% 2025-09-07T10:02:28.7699937Z triton_mm_1273 0.0115 ms 97.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:28.7702089Z triton_mm_1279 0.0132 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:28.7703033Z triton_mm_1272 0.0133 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:28.7703870Z triton_mm_1268 0.0140 ms 80.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:02:28.7704772Z triton_mm_1269 0.0143 ms 78.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:28.7705667Z triton_mm_1271 0.0147 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:28.7706557Z triton_mm_1275 0.0149 ms 75.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:28.7707472Z triton_mm_1278 0.0151 ms 74.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:28.7708370Z triton_mm_1270 0.0179 ms 62.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:28.7709152Z SingleProcess AUTOTUNE benchmarking takes 0.2487 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:02:29.2030899Z Autotune Choices Stats: 2025-09-07T10:02:29.2032104Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1193", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.013311999849975109, "best_triton_pos": 0} 2025-09-07T10:02:29.2175422Z AUTOTUNE mm(364x1000, 1000x1024) 2025-09-07T10:02:29.2175741Z strides: [1, 364], [1024, 1] 2025-09-07T10:02:29.2176010Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:29.2176737Z triton_mm_1193 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 2025-09-07T10:02:29.2177838Z triton_mm_1192 0.0134 ms 99.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:02:29.2178917Z triton_mm_1196 0.0137 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:29.2179993Z triton_mm_1197 0.0141 ms 94.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:29.2181273Z triton_mm_1195 0.0145 ms 91.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:29.2182328Z triton_mm_1199 0.0149 ms 89.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:29.2183881Z triton_mm_1187 0.0157 ms 84.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:29.2185454Z triton_mm_1186 0.0162 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:02:29.2186531Z triton_mm_1202 0.0163 ms 81.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:29.2187600Z triton_mm_1188 0.0168 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:29.2188526Z SingleProcess AUTOTUNE benchmarking takes 0.2244 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:02:29.8223697Z Autotune Choices Stats: 2025-09-07T10:02:29.8225516Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01635199971497059, "best_triton_pos": 1, "best_triton_time": 0.019967999309301376, "best_triton_kernel": "triton_mm_1208", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T10:02:29.8325472Z AUTOTUNE mm(91x1000, 1000x1024) 2025-09-07T10:02:29.8325835Z strides: [1, 91], [1024, 1] 2025-09-07T10:02:29.8326182Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:29.8326542Z mm 0.0164 ms 100.0% 2025-09-07T10:02:29.8327380Z triton_mm_1208 0.0200 ms 81.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:29.8328793Z triton_mm_1205 0.0209 ms 78.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:02:29.8330187Z triton_mm_1211 0.0217 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:02:29.8332028Z triton_mm_1206 0.0230 ms 71.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:29.8333462Z triton_mm_1215 0.0241 ms 67.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:29.8334884Z triton_mm_1212 0.0252 ms 64.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:29.8336273Z triton_mm_1207 0.0286 ms 57.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:29.8337715Z triton_mm_1222 0.0305 ms 53.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:29.8339162Z triton_mm_1214 0.0309 ms 53.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:29.8340592Z SingleProcess AUTOTUNE benchmarking takes 0.4165 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:02:30.8602468Z Autotune Choices Stats: 2025-09-07T10:02:30.8603539Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1234", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.009664000011980534, "best_triton_pos": 0} 2025-09-07T10:02:30.8705493Z AUTOTUNE mm(1000x364, 364x1024) 2025-09-07T10:02:30.8705745Z strides: [364, 1], [1024, 1] 2025-09-07T10:02:30.8705977Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:30.8707094Z triton_mm_1234 0.0097 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 2025-09-07T10:02:30.8708059Z triton_mm_1233 0.0099 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:30.8708981Z triton_mm_1235 0.0099 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:30.8709902Z triton_mm_1237 0.0102 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:30.8710967Z triton_mm_1230 0.0109 ms 88.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:02:30.8711878Z triton_mm_1232 0.0111 ms 87.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:30.8712786Z triton_mm_1236 0.0114 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:30.8713688Z triton_mm_1240 0.0117 ms 82.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:30.8714606Z triton_mm_1239 0.0120 ms 80.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:30.8715522Z triton_mm_1231 0.0123 ms 78.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:02:31.2669621Z SingleProcess AUTOTUNE benchmarking takes 0.4206 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:02:31.2671033Z Autotune Choices Stats: 2025-09-07T10:02:31.2672549Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.044863998889923096, "best_triton_pos": 1, "best_triton_time": 0.05084799975156784, "best_triton_kernel": "triton_mm_1316", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:02:31.2776828Z AUTOTUNE mm(1000x1024, 1024x12544) 2025-09-07T10:02:31.2777223Z strides: [1024, 1], [12544, 1] 2025-09-07T10:02:31.2777536Z dtypes: torch.float16, torch.float16 2025-09-07T10:02:31.2777882Z mm 0.0449 ms 100.0% 2025-09-07T10:02:31.2778653Z triton_mm_1316 0.0508 ms 88.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:31.2779923Z triton_mm_1315 0.0510 ms 87.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:31.2781295Z triton_mm_1317 0.0571 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:02:31.2782510Z triton_mm_1310 0.0677 ms 66.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:31.2784436Z triton_mm_1308 0.0715 ms 62.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:31.2785974Z triton_mm_1309 0.0722 ms 62.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:31.2787331Z triton_mm_1313 0.0760 ms 59.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:02:31.2788548Z triton_mm_1311 0.0774 ms 57.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:02:31.2789791Z triton_mm_1312 0.0781 ms 57.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:02:31.2791152Z SingleProcess AUTOTUNE benchmarking takes 0.4065 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:02:33.6081447Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 256, in torch_dynamo_resume_in_roi_align_at_255 2025-09-07T10:02:33.6082742Z return _roi_align(input, rois, spatial_scale, output_size[0], output_size[1], sampling_ratio, aligned) 2025-09-07T10:02:33.6083537Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/polyfills/__init__.py", line 264, in getattr_and_trace 2025-09-07T10:02:33.6084122Z return fn(*args[2:], **kwargs) 2025-09-07T10:02:33.6084650Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:33.6085353Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:33.6086086Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:33.6086652Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:33.6087136Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:33.6087615Z return input[ 2025-09-07T10:02:33.6087734Z 2025-09-07T10:02:33.6087743Z 2025-09-07T10:02:38.1740115Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put_.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 114, in forward 2025-09-07T10:02:38.1741641Z features = self.backbone(images.tensors) 2025-09-07T10:02:38.1742320Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/backbone_utils.py", line 58, in forward 2025-09-07T10:02:38.1743033Z x = self.fpn(x) 2025-09-07T10:02:38.1743569Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/feature_pyramid_network.py", line 194, in forward 2025-09-07T10:02:38.1744280Z inner_top_down = F.interpolate(last_inner, size=feat_shape, mode="nearest") 2025-09-07T10:02:38.1744606Z 2025-09-07T10:02:38.1744628Z 2025-09-07T10:02:39.0285761Z W0907 10:02:39.027000 118496 site-packages/torch/_logging/_internal.py:1199] [51/0] Profiler function will be ignored 2025-09-07T10:02:49.2863577Z W0907 10:02:49.285000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T10:02:49.2864810Z W0907 10:02:49.285000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] function: 'torch_dynamo_resume_in_roi_align_at_255' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:255) 2025-09-07T10:02:49.2866580Z W0907 10:02:49.285000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] last reason: 30/7: tensor 'rois' requires_grad mismatch. expected requires_grad=1 2025-09-07T10:02:49.2867581Z W0907 10:02:49.285000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T10:02:49.2869204Z W0907 10:02:49.285000 118496 site-packages/torch/_dynamo/convert_frame.py:1358] [30/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T10:02:51.4235094Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:51.4236212Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:51.4237010Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:51.4237613Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:51.4238157Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:51.4238688Z return input[ 2025-09-07T10:02:51.4238809Z 2025-09-07T10:02:51.4238823Z 2025-09-07T10:02:53.3504505Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:53.3505540Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:53.3506227Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:53.3506756Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:53.3507227Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:53.3507684Z return input[ 2025-09-07T10:02:53.3507792Z 2025-09-07T10:02:53.3507796Z 2025-09-07T10:02:55.2579193Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:55.2580599Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:55.2581362Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:55.2581964Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:55.2582508Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:55.2583137Z return input[ 2025-09-07T10:02:55.2583263Z 2025-09-07T10:02:55.2583267Z 2025-09-07T10:02:57.1636130Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:02:57.1637292Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:02:57.1638063Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:02:57.1638664Z v4 = masked_index(y_high, x_high) 2025-09-07T10:02:57.1639209Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:02:57.1639725Z return input[ 2025-09-07T10:02:57.1639855Z 2025-09-07T10:02:57.1640547Z 2025-09-07T10:03:02.3263998Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:03:02.3265451Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:03:02.3267025Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:03:02.3267659Z v4 = masked_index(y_high, x_high) 2025-09-07T10:03:02.3268216Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:03:02.3268740Z return input[ 2025-09-07T10:03:02.3268884Z 2025-09-07T10:03:02.3268888Z 2025-09-07T10:03:06.4609795Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:03:06.4611490Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:03:06.4612311Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:03:06.4612969Z v4 = masked_index(y_high, x_high) 2025-09-07T10:03:06.4613553Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:03:06.4614118Z return input[ 2025-09-07T10:03:06.4614258Z 2025-09-07T10:03:06.4614262Z 2025-09-07T10:03:09.5993861Z skipping cudagraphs due to disabling cudagraphs due to incompatible op aten.index_put.default Found from File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 185, in _roi_align 2025-09-07T10:03:09.5995040Z val = _bilinear_interpolate(input, roi_batch_ind, y, x, ymask, xmask) # [K, C, PH, PW, IY, IX] 2025-09-07T10:03:09.5995939Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 84, in _bilinear_interpolate 2025-09-07T10:03:09.5996631Z v4 = masked_index(y_high, x_high) 2025-09-07T10:03:09.5997204Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py", line 74, in masked_index 2025-09-07T10:03:09.5997776Z return input[ 2025-09-07T10:03:09.5997915Z 2025-09-07T10:03:09.5997929Z 2025-09-07T10:03:18.7684986Z W0907 10:03:18.767000 118496 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T10:03:18.7927670Z W0907 10:03:18.792000 118496 site-packages/torch/_dynamo/utils.py:3060] Found nan in reference. Consider running in higher precision. 2025-09-07T10:03:18.8794853Z pass 2025-09-07T10:03:25.3465810Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:03:25.3466936Z import pynvml # type: ignore[import] 2025-09-07T10:03:27.8177880Z 2025-09-07T10:03:30.7064564Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:03:30.7064946Z loading model: 0it [00:02, ?it/s] 2025-09-07T10:03:30.7065264Z cuda train yolov3 2025-09-07T10:04:02.2947648Z Autotune Choices Stats: 2025-09-07T10:04:02.2949134Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "convolution", "best_time": 0.056703999638557434, "best_triton_pos": 1, "best_triton_time": 0.12585599720478058, "best_triton_kernel": "triton_convolution2d_2", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8"} 2025-09-07T10:04:02.3044513Z AUTOTUNE convolution(4x3x384x512, 32x3x3x3) 2025-09-07T10:04:02.3045397Z strides: [589824, 1, 1536, 3], [27, 1, 9, 3] 2025-09-07T10:04:02.3045711Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:02.3046001Z convolution 0.0567 ms 100.0% 2025-09-07T10:04:02.3046822Z triton_convolution2d_2 0.1259 ms 45.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:02.3048615Z triton_convolution2d_4 0.1515 ms 37.4% 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=8 2025-09-07T10:04:02.3049942Z triton_convolution2d_0 0.1692 ms 33.5% 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 2025-09-07T10:04:02.3051479Z triton_convolution2d_3 0.1761 ms 32.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:02.3052626Z triton_convolution2d_1 0.2108 ms 26.9% 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 2025-09-07T10:04:02.3053757Z triton_convolution2d_5 0.2368 ms 23.9% 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=8 2025-09-07T10:04:02.3054644Z SingleProcess AUTOTUNE benchmarking takes 0.2118 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T10:04:02.4467406Z Autotune Choices Stats: 2025-09-07T10:04:02.4469319Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.04249599948525429, "best_triton_pos": 1, "best_triton_time": 0.04966399818658829, "best_triton_kernel": "triton_convolution2d_9", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:04:02.4676217Z AUTOTUNE convolution(4x32x384x512, 64x32x3x3) 2025-09-07T10:04:02.4676688Z strides: [6291456, 1, 16384, 32], [288, 1, 96, 32] 2025-09-07T10:04:02.4677110Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:02.4677490Z convolution 0.0425 ms 100.0% 2025-09-07T10:04:02.4678525Z triton_convolution2d_9 0.0497 ms 85.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:02.4680376Z triton_convolution2d_12 0.0507 ms 83.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:02.4682071Z triton_convolution2d_10 0.0553 ms 76.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:02.4683757Z triton_convolution2d_11 0.0570 ms 74.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:02.4685441Z triton_convolution2d_7 0.0683 ms 62.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:02.4687131Z triton_convolution2d_6 0.1031 ms 41.2% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:02.4689042Z triton_convolution2d_8 0.1836 ms 23.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:02.4690525Z SingleProcess AUTOTUNE benchmarking takes 0.1618 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:02.7103319Z Autotune Choices Stats: 2025-09-07T10:04:02.7104684Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_28", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.01897599920630455, "best_triton_pos": 0} 2025-09-07T10:04:02.7757309Z AUTOTUNE mm(196608x64, 64x32) 2025-09-07T10:04:02.7757562Z strides: [64, 1], [1, 64] 2025-09-07T10:04:02.7757817Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:02.7758466Z triton_mm_28 0.0190 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:02.7759434Z triton_mm_20 0.0193 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:02.7760717Z triton_mm_24 0.0204 ms 93.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:02.7761674Z triton_mm_14 0.0205 ms 92.5% 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 2025-09-07T10:04:02.7762612Z triton_mm_23 0.0205 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:02.7763569Z triton_mm_26 0.0208 ms 91.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:02.7764517Z triton_mm_17 0.0210 ms 90.5% 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 2025-09-07T10:04:02.7765459Z triton_mm_22 0.0212 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:02.7766412Z triton_mm_29 0.0212 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:02.7767008Z mm 0.0219 ms 86.7% 2025-09-07T10:04:02.7767447Z SingleProcess AUTOTUNE benchmarking takes 0.3069 seconds and 0.0002 seconds precompiling for 18 choices 2025-09-07T10:04:02.9056112Z Autotune Choices Stats: 2025-09-07T10:04:02.9057501Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.034143999218940735, "best_triton_pos": 1, "best_triton_time": 0.039712000638246536, "best_triton_kernel": "triton_convolution2d_36", "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"} 2025-09-07T10:04:02.9147085Z AUTOTUNE convolution(4x32x192x256, 64x32x3x3) 2025-09-07T10:04:02.9147419Z strides: [1572864, 1, 8192, 32], [288, 1, 96, 32] 2025-09-07T10:04:02.9147732Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:02.9148042Z convolution 0.0341 ms 100.0% 2025-09-07T10:04:02.9148795Z triton_convolution2d_36 0.0397 ms 86.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:02.9150557Z triton_convolution2d_33 0.0402 ms 84.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:02.9152177Z triton_convolution2d_34 0.0465 ms 73.4% 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 2025-09-07T10:04:02.9153514Z triton_convolution2d_35 0.0488 ms 70.0% 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 2025-09-07T10:04:02.9154725Z triton_convolution2d_31 0.0581 ms 58.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:02.9155933Z triton_convolution2d_30 0.0992 ms 34.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:02.9157153Z triton_convolution2d_32 0.1252 ms 27.3% 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 2025-09-07T10:04:02.9158131Z SingleProcess AUTOTUNE benchmarking takes 0.1384 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:03.0712218Z Autotune Choices Stats: 2025-09-07T10:04:03.0713626Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.029600000008940697, "best_triton_pos": 1, "best_triton_time": 0.04064000025391579, "best_triton_kernel": "triton_convolution2d_42", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:04:03.0857975Z AUTOTUNE convolution(4x64x192x256, 128x64x3x3) 2025-09-07T10:04:03.0858339Z strides: [3145728, 1, 16384, 64], [576, 1, 192, 64] 2025-09-07T10:04:03.0858663Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:03.0858940Z convolution 0.0296 ms 100.0% 2025-09-07T10:04:03.0859701Z triton_convolution2d_42 0.0406 ms 72.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.0861358Z triton_convolution2d_40 0.0424 ms 69.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.0862598Z triton_convolution2d_41 0.0471 ms 62.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.0863803Z triton_convolution2d_43 0.0518 ms 57.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.0864932Z triton_convolution2d_37 0.0661 ms 44.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.0866062Z triton_convolution2d_38 0.0680 ms 43.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.0867183Z triton_convolution2d_39 0.1604 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 2025-09-07T10:04:03.0868321Z SingleProcess AUTOTUNE benchmarking takes 0.1697 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:03.3122935Z Autotune Choices Stats: 2025-09-07T10:04:03.3124210Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_55", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013151999562978745, "best_triton_pos": 0} 2025-09-07T10:04:03.3995371Z AUTOTUNE mm(49152x128, 128x64) 2025-09-07T10:04:03.3995649Z strides: [128, 1], [1, 128] 2025-09-07T10:04:03.3995901Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:03.3996551Z triton_mm_55 0.0132 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:03.3997543Z triton_mm_60 0.0132 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:03.3998503Z triton_mm_51 0.0134 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:03.3999468Z triton_mm_59 0.0136 ms 96.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.4000076Z mm 0.0137 ms 96.3% 2025-09-07T10:04:03.4000802Z triton_mm_58 0.0139 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:03.4001765Z triton_mm_56 0.0140 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:03.4002718Z triton_mm_50 0.0141 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.4003595Z triton_mm_52 0.0141 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:03.4004492Z triton_mm_57 0.0141 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:03.4005276Z SingleProcess AUTOTUNE benchmarking takes 0.3125 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T10:04:03.5255779Z Autotune Choices Stats: 2025-09-07T10:04:03.5257151Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.025567999109625816, "best_triton_pos": 1, "best_triton_time": 0.03311999887228012, "best_triton_kernel": "triton_convolution2d_67", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T10:04:03.5472109Z AUTOTUNE convolution(4x64x96x128, 128x64x3x3) 2025-09-07T10:04:03.5472429Z strides: [786432, 1, 8192, 64], [576, 1, 192, 64] 2025-09-07T10:04:03.5472725Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:03.5472988Z convolution 0.0256 ms 100.0% 2025-09-07T10:04:03.5473745Z triton_convolution2d_67 0.0331 ms 77.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.5474975Z triton_convolution2d_65 0.0337 ms 75.9% 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 2025-09-07T10:04:03.5476348Z triton_convolution2d_66 0.0413 ms 61.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.5477702Z triton_convolution2d_68 0.0416 ms 61.5% 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 2025-09-07T10:04:03.5478975Z triton_convolution2d_63 0.0547 ms 46.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.5480191Z triton_convolution2d_62 0.0610 ms 41.9% 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 2025-09-07T10:04:03.5481725Z triton_convolution2d_64 0.1400 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 2025-09-07T10:04:03.5482605Z SingleProcess AUTOTUNE benchmarking takes 0.1472 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:03.6846196Z Autotune Choices Stats: 2025-09-07T10:04:03.6847617Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.024159999564290047, "best_triton_pos": 1, "best_triton_time": 0.03711999952793121, "best_triton_kernel": "triton_convolution2d_98", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:04:03.7394794Z AUTOTUNE convolution(4x128x96x128, 256x128x3x3) 2025-09-07T10:04:03.7395136Z strides: [1572864, 1, 16384, 128], [1152, 1, 384, 128] 2025-09-07T10:04:03.7395435Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:03.7395715Z convolution 0.0242 ms 100.0% 2025-09-07T10:04:03.7396440Z triton_convolution2d_98 0.0371 ms 65.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.7397675Z triton_convolution2d_97 0.0411 ms 58.8% 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 2025-09-07T10:04:03.7398896Z triton_convolution2d_99 0.0432 ms 55.9% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.7400121Z triton_convolution2d_100 0.0454 ms 53.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:03.7401514Z triton_convolution2d_94 0.0572 ms 42.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:03.7402731Z triton_convolution2d_95 0.0580 ms 41.7% 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 2025-09-07T10:04:03.7403868Z triton_convolution2d_96 0.1959 ms 12.3% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:03.7404770Z SingleProcess AUTOTUNE benchmarking takes 0.1848 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:03.9776972Z Autotune Choices Stats: 2025-09-07T10:04:03.9778002Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_108", "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": 0.010623999871313572, "best_triton_pos": 0} 2025-09-07T10:04:04.0089067Z AUTOTUNE mm(12288x256, 256x128) 2025-09-07T10:04:04.0089538Z strides: [256, 1], [1, 256] 2025-09-07T10:04:04.0089915Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:04.0091193Z triton_mm_108 0.0106 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:04.0092572Z triton_mm_119 0.0107 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:04.0093479Z triton_mm_112 0.0109 ms 97.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.0094065Z mm 0.0109 ms 97.4% 2025-09-07T10:04:04.0094583Z triton_mm_115 0.0112 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:04.0095473Z triton_mm_114 0.0114 ms 93.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.0096357Z triton_mm_110 0.0114 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.0097235Z triton_mm_111 0.0114 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:04.0098135Z triton_mm_118 0.0115 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.0099033Z triton_mm_117 0.0121 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.0099820Z SingleProcess AUTOTUNE benchmarking takes 0.2681 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:04.1357319Z Autotune Choices Stats: 2025-09-07T10:04:04.1358687Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.022752000018954277, "best_triton_pos": 1, "best_triton_time": 0.033824000507593155, "best_triton_kernel": "triton_convolution2d_124", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:04:04.1475443Z AUTOTUNE convolution(4x128x48x64, 256x128x3x3) 2025-09-07T10:04:04.1475774Z strides: [393216, 1, 8192, 128], [1152, 1, 384, 128] 2025-09-07T10:04:04.1476074Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:04.1476354Z convolution 0.0228 ms 100.0% 2025-09-07T10:04:04.1477080Z triton_convolution2d_124 0.0338 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 2025-09-07T10:04:04.1478320Z triton_convolution2d_123 0.0385 ms 59.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:04.1479552Z triton_convolution2d_125 0.0395 ms 57.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:04.1481099Z triton_convolution2d_126 0.0416 ms 54.7% 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 2025-09-07T10:04:04.1482549Z triton_convolution2d_121 0.0545 ms 41.7% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:04.1483724Z triton_convolution2d_120 0.0548 ms 41.5% 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 2025-09-07T10:04:04.1484884Z triton_convolution2d_122 0.1815 ms 12.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:04.1485788Z SingleProcess AUTOTUNE benchmarking takes 0.1381 seconds and 0.0003 seconds precompiling for 8 choices 2025-09-07T10:04:04.3423836Z Autotune Choices Stats: 2025-09-07T10:04:04.3425191Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023584000766277313, "best_triton_pos": 1, "best_triton_time": 0.05641600117087364, "best_triton_kernel": "triton_convolution2d_313", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:04:04.4917356Z AUTOTUNE convolution(4x256x48x64, 512x256x3x3) 2025-09-07T10:04:04.4917704Z strides: [786432, 1, 16384, 256], [2304, 1, 768, 256] 2025-09-07T10:04:04.4918021Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:04.4918297Z convolution 0.0236 ms 100.0% 2025-09-07T10:04:04.4919031Z triton_convolution2d_313 0.0564 ms 41.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:04.4920458Z triton_convolution2d_312 0.0702 ms 33.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:04.4921718Z triton_convolution2d_314 0.0713 ms 33.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:04.4922959Z triton_convolution2d_315 0.0751 ms 31.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:04.4924100Z triton_convolution2d_309 0.1016 ms 23.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:04.4925238Z triton_convolution2d_310 0.1045 ms 22.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:04.4926380Z triton_convolution2d_311 0.1970 ms 12.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:04.4927274Z SingleProcess AUTOTUNE benchmarking takes 0.2999 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:04.7338955Z Autotune Choices Stats: 2025-09-07T10:04:04.7340195Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009088000282645226, "best_triton_pos": 1, "best_triton_time": 0.009472000412642956, "best_triton_kernel": "triton_mm_328", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:04:04.7446396Z AUTOTUNE mm(3072x512, 512x256) 2025-09-07T10:04:04.7446849Z strides: [512, 1], [1, 512] 2025-09-07T10:04:04.7447364Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:04.7447670Z mm 0.0091 ms 100.0% 2025-09-07T10:04:04.7448324Z triton_mm_328 0.0095 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:04.7449367Z triton_mm_323 0.0102 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:04.7450640Z triton_mm_327 0.0102 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.7451729Z triton_mm_334 0.0107 ms 85.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:04.7452698Z triton_mm_333 0.0109 ms 83.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:04.7453588Z triton_mm_326 0.0109 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 2025-09-07T10:04:04.7454476Z triton_mm_330 0.0110 ms 82.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:04.7455359Z triton_mm_324 0.0114 ms 80.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:04.7456243Z triton_mm_317 0.0121 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:04.7457026Z SingleProcess AUTOTUNE benchmarking takes 0.2515 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:04.8959990Z Autotune Choices Stats: 2025-09-07T10:04:04.8961609Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.022975999861955643, "best_triton_pos": 1, "best_triton_time": 0.05507199838757515, "best_triton_kernel": "triton_convolution2d_339", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:04:04.9068062Z AUTOTUNE convolution(4x256x24x32, 512x256x3x3) 2025-09-07T10:04:04.9068402Z strides: [196608, 1, 8192, 256], [2304, 1, 768, 256] 2025-09-07T10:04:04.9068723Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:04.9069016Z convolution 0.0230 ms 100.0% 2025-09-07T10:04:04.9069767Z triton_convolution2d_339 0.0551 ms 41.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:04.9071205Z triton_convolution2d_338 0.0686 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 2025-09-07T10:04:04.9072598Z triton_convolution2d_340 0.0695 ms 33.0% 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 2025-09-07T10:04:04.9073997Z triton_convolution2d_341 0.0748 ms 30.7% 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 2025-09-07T10:04:04.9075418Z triton_convolution2d_335 0.0998 ms 23.0% 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 2025-09-07T10:04:04.9076723Z triton_convolution2d_336 0.1018 ms 22.6% 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 2025-09-07T10:04:04.9077952Z triton_convolution2d_337 0.1925 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 2025-09-07T10:04:04.9078925Z SingleProcess AUTOTUNE benchmarking takes 0.1608 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:05.1603440Z Autotune Choices Stats: 2025-09-07T10:04:05.1604860Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023296000435948372, "best_triton_pos": 1, "best_triton_time": 0.11055999994277954, "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=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:04:05.1704239Z AUTOTUNE convolution(4x512x24x32, 1024x512x3x3) 2025-09-07T10:04:05.1704571Z strides: [393216, 1, 16384, 512], [4608, 1, 1536, 512] 2025-09-07T10:04:05.1704878Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:05.1705151Z convolution 0.0233 ms 100.0% 2025-09-07T10:04:05.1705893Z triton_convolution2d_528 0.1106 ms 21.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:05.1707139Z triton_convolution2d_529 0.1321 ms 17.6% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:05.1708382Z triton_convolution2d_527 0.1364 ms 17.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:05.1709610Z triton_convolution2d_530 0.1450 ms 16.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T10:04:05.1711158Z triton_convolution2d_524 0.1982 ms 11.8% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:05.1712557Z triton_convolution2d_525 0.2039 ms 11.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:05.1713783Z triton_convolution2d_526 0.3393 ms 6.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:05.1714757Z SingleProcess AUTOTUNE benchmarking takes 0.2133 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:05.4045685Z Autotune Choices Stats: 2025-09-07T10:04:05.4046813Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009375999681651592, "best_triton_pos": 1, "best_triton_time": 0.00940799992531538, "best_triton_kernel": "triton_mm_539", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T10:04:05.4149357Z AUTOTUNE mm(768x1024, 1024x512) 2025-09-07T10:04:05.4149626Z strides: [1024, 1], [1, 1024] 2025-09-07T10:04:05.4150055Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:05.4150738Z mm 0.0094 ms 100.0% 2025-09-07T10:04:05.4151366Z triton_mm_539 0.0094 ms 99.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:05.4152503Z triton_mm_543 0.0106 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:05.4153470Z triton_mm_535 0.0119 ms 79.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:05.4154420Z triton_mm_538 0.0120 ms 78.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:05.4155386Z triton_mm_549 0.0124 ms 75.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:05.4156351Z triton_mm_542 0.0124 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:05.4157299Z triton_mm_534 0.0136 ms 68.8% 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 2025-09-07T10:04:05.4158251Z triton_mm_548 0.0140 ms 67.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:05.4159223Z triton_mm_545 0.0140 ms 67.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:05.4160069Z SingleProcess AUTOTUNE benchmarking takes 0.2432 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:05.6181944Z Autotune Choices Stats: 2025-09-07T10:04:05.6183438Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02287999913096428, "best_triton_pos": 1, "best_triton_time": 0.10992000252008438, "best_triton_kernel": "triton_convolution2d_554", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T10:04:05.6292525Z AUTOTUNE convolution(4x512x12x16, 1024x512x3x3) 2025-09-07T10:04:05.6292908Z strides: [98304, 1, 8192, 512], [4608, 1, 1536, 512] 2025-09-07T10:04:05.6293226Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:05.6293506Z convolution 0.0229 ms 100.0% 2025-09-07T10:04:05.6294296Z triton_convolution2d_554 0.1099 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 2025-09-07T10:04:05.6295575Z triton_convolution2d_555 0.1319 ms 17.4% 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 2025-09-07T10:04:05.6296848Z triton_convolution2d_553 0.1351 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 2025-09-07T10:04:05.6298382Z triton_convolution2d_556 0.1442 ms 15.9% 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 2025-09-07T10:04:05.6299870Z triton_convolution2d_550 0.1971 ms 11.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:05.6301611Z triton_convolution2d_551 0.1986 ms 11.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T10:04:05.6303159Z triton_convolution2d_552 0.3290 ms 7.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T10:04:05.6304215Z SingleProcess AUTOTUNE benchmarking takes 0.2129 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T10:04:05.9065258Z Autotune Choices Stats: 2025-09-07T10:04:05.9066495Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010816000401973724, "best_triton_pos": 1, "best_triton_time": 0.012128000147640705, "best_triton_kernel": "triton_mm_688", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T10:04:05.9517761Z AUTOTUNE mm(768x2048, 2048x512) 2025-09-07T10:04:05.9518031Z strides: [2048, 1], [1, 2048] 2025-09-07T10:04:05.9518275Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:05.9518531Z mm 0.0108 ms 100.0% 2025-09-07T10:04:05.9519105Z triton_mm_688 0.0121 ms 89.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:05.9520093Z triton_mm_692 0.0137 ms 78.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:05.9521443Z triton_mm_684 0.0161 ms 67.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:05.9522436Z triton_mm_698 0.0177 ms 61.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:05.9523398Z triton_mm_687 0.0190 ms 57.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:05.9524287Z triton_mm_691 0.0193 ms 56.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:05.9525178Z triton_mm_681 0.0204 ms 53.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:05.9526066Z triton_mm_683 0.0212 ms 50.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:05.9526961Z triton_mm_690 0.0226 ms 47.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:05.9527740Z SingleProcess AUTOTUNE benchmarking takes 0.2889 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:06.3289920Z Autotune Choices Stats: 2025-09-07T10:04:06.3292378Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_736", "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": 0.009600000455975533, "best_triton_pos": 0} 2025-09-07T10:04:06.4434817Z AUTOTUNE addmm(768x255, 768x1024, 1024x255) 2025-09-07T10:04:06.4435133Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T10:04:06.4435439Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:04:06.4436548Z triton_mm_736 0.0096 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:06.4437527Z triton_mm_740 0.0102 ms 93.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:06.4438509Z triton_mm_735 0.0121 ms 79.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:06.4439479Z triton_mm_744 0.0122 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:06.4440737Z triton_mm_734 0.0127 ms 75.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:06.4441708Z triton_mm_739 0.0130 ms 74.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:06.4442679Z triton_mm_733 0.0132 ms 73.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:06.4443640Z triton_mm_743 0.0139 ms 69.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:06.4444599Z triton_mm_750 0.0153 ms 62.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:06.4445577Z triton_mm_742 0.0156 ms 61.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:06.4446417Z SingleProcess AUTOTUNE benchmarking takes 0.4790 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:04:06.6856927Z Autotune Choices Stats: 2025-09-07T10:04:06.6857937Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_755", "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": 0.008224000222980976, "best_triton_pos": 0} 2025-09-07T10:04:06.6967747Z AUTOTUNE mm(768x512, 512x256) 2025-09-07T10:04:06.6968015Z strides: [512, 1], [1, 512] 2025-09-07T10:04:06.6968284Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:06.6968980Z triton_mm_755 0.0082 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:06.6970021Z triton_mm_759 0.0085 ms 96.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:06.6970844Z mm 0.0087 ms 94.5% 2025-09-07T10:04:06.6971441Z triton_mm_763 0.0092 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:06.6972485Z triton_mm_754 0.0093 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:06.6973598Z triton_mm_758 0.0094 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:06.6974477Z triton_mm_753 0.0096 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 2025-09-07T10:04:06.6975656Z triton_mm_762 0.0097 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:06.6976560Z triton_mm_752 0.0098 ms 84.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:06.6977453Z triton_mm_761 0.0103 ms 80.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:06.6978242Z SingleProcess AUTOTUNE benchmarking takes 0.2527 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T10:04:06.9343467Z Autotune Choices Stats: 2025-09-07T10:04:06.9344666Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010143999941647053, "best_triton_pos": 1, "best_triton_time": 0.010751999914646149, "best_triton_kernel": "triton_mm_782", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T10:04:06.9483272Z AUTOTUNE mm(3072x768, 768x256) 2025-09-07T10:04:06.9483551Z strides: [768, 1], [1, 768] 2025-09-07T10:04:06.9483814Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:06.9484084Z mm 0.0101 ms 100.0% 2025-09-07T10:04:06.9484726Z triton_mm_782 0.0108 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:06.9485754Z triton_mm_788 0.0121 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:06.9486751Z triton_mm_777 0.0121 ms 83.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:06.9487759Z triton_mm_781 0.0121 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:06.9488762Z triton_mm_778 0.0128 ms 79.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:06.9489762Z triton_mm_787 0.0132 ms 76.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:06.9491127Z triton_mm_780 0.0134 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:06.9492124Z triton_mm_784 0.0134 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:06.9493146Z triton_mm_774 0.0147 ms 69.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:06.9493925Z SingleProcess AUTOTUNE benchmarking takes 0.2509 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:07.2299642Z Autotune Choices Stats: 2025-09-07T10:04:07.2300983Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_860", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.011264000087976456, "best_triton_pos": 0} 2025-09-07T10:04:07.2395710Z AUTOTUNE addmm(3072x255, 3072x512, 512x255) 2025-09-07T10:04:07.2395984Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T10:04:07.2396285Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:04:07.2397341Z triton_mm_860 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:07.2398325Z triton_mm_855 0.0117 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:07.2399291Z triton_mm_859 0.0118 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:07.2400383Z triton_mm_858 0.0125 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 2025-09-07T10:04:07.2401374Z triton_mm_862 0.0128 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:07.2402344Z triton_mm_849 0.0132 ms 85.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:07.2403306Z triton_mm_856 0.0133 ms 84.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:07.2404271Z triton_mm_866 0.0135 ms 83.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:07.2405235Z triton_mm_851 0.0136 ms 82.8% 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 2025-09-07T10:04:07.2406203Z triton_mm_865 0.0140 ms 80.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:07.2407042Z SingleProcess AUTOTUNE benchmarking takes 0.2708 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:04:07.4757377Z Autotune Choices Stats: 2025-09-07T10:04:07.4758354Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_875", "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": 0.007679999805986881, "best_triton_pos": 0} 2025-09-07T10:04:07.4852343Z AUTOTUNE mm(3072x256, 256x128) 2025-09-07T10:04:07.4852627Z strides: [256, 1], [1, 256] 2025-09-07T10:04:07.4852904Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:07.4853593Z triton_mm_875 0.0077 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T10:04:07.4854603Z triton_mm_874 0.0080 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:07.4855571Z triton_mm_878 0.0082 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:07.4856191Z mm 0.0084 ms 91.6% 2025-09-07T10:04:07.4856769Z triton_mm_879 0.0085 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:07.4857916Z triton_mm_870 0.0086 ms 89.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:07.4858881Z triton_mm_868 0.0086 ms 89.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:07.4860191Z triton_mm_881 0.0087 ms 88.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:07.4861342Z triton_mm_877 0.0088 ms 87.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:07.4862300Z triton_mm_869 0.0089 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:07.4863285Z SingleProcess AUTOTUNE benchmarking takes 0.2451 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:07.7173747Z Autotune Choices Stats: 2025-09-07T10:04:07.7174978Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011807999573647976, "best_triton_pos": 1, "best_triton_time": 0.01196799986064434, "best_triton_kernel": "triton_mm_897", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T10:04:07.7269349Z AUTOTUNE mm(12288x384, 384x128) 2025-09-07T10:04:07.7269606Z strides: [384, 1], [1, 384] 2025-09-07T10:04:07.7269891Z dtypes: torch.float16, torch.float16 2025-09-07T10:04:07.7270158Z mm 0.0118 ms 100.0% 2025-09-07T10:04:07.7271101Z triton_mm_897 0.0120 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:07.7272102Z triton_mm_904 0.0120 ms 98.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T10:04:07.7273233Z triton_mm_893 0.0122 ms 97.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:07.7274196Z triton_mm_903 0.0124 ms 95.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:07.7275160Z triton_mm_900 0.0130 ms 90.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:07.7276112Z triton_mm_896 0.0133 ms 88.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:07.7277068Z triton_mm_895 0.0136 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 2025-09-07T10:04:07.7278027Z triton_mm_899 0.0137 ms 86.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:07.7279005Z triton_mm_898 0.0141 ms 83.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:07.7279850Z SingleProcess AUTOTUNE benchmarking takes 0.2412 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T10:04:08.0121877Z Autotune Choices Stats: 2025-09-07T10:04:08.0122979Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_975", "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": 0.014751999638974667, "best_triton_pos": 0} 2025-09-07T10:04:08.0218580Z AUTOTUNE addmm(12288x255, 12288x256, 256x255) 2025-09-07T10:04:08.0218877Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T10:04:08.0219675Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T10:04:08.0220773Z triton_mm_975 0.0148 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:08.0221775Z triton_mm_981 0.0159 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:08.0222910Z triton_mm_973 0.0160 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:08.0223878Z triton_mm_978 0.0166 ms 88.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:08.0224859Z triton_mm_977 0.0167 ms 88.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:08.0225824Z triton_mm_970 0.0170 ms 86.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T10:04:08.0226774Z triton_mm_971 0.0171 ms 86.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T10:04:08.0227735Z triton_mm_980 0.0172 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T10:04:08.0228705Z triton_mm_974 0.0181 ms 81.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T10:04:08.0229678Z triton_mm_976 0.0196 ms 75.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T10:04:08.0230649Z SingleProcess AUTOTUNE benchmarking takes 0.2759 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T10:04:08.1222910Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:04:08.1223641Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:04:08.1224292Z pred = mod(*cloned_inputs) 2025-09-07T10:04:08.1224727Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T10:04:08.1225187Z return self.forward_once(x) 2025-09-07T10:04:08.1225629Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T10:04:08.1226096Z yolo_out.append(module(x, out)) 2025-09-07T10:04:08.1226526Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T10:04:08.1227016Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T10:04:08.1227520Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T10:04:08.1228021Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T10:04:08.1228239Z 2025-09-07T10:04:08.1228401Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:04:08.1229086Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:04:08.1229991Z pred = mod(*cloned_inputs) 2025-09-07T10:04:08.1230718Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T10:04:08.1231161Z return self.forward_once(x) 2025-09-07T10:04:08.1231609Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T10:04:08.1232071Z yolo_out.append(module(x, out)) 2025-09-07T10:04:08.1232827Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T10:04:08.1233373Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T10:04:08.1233839Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T10:04:08.1234316Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T10:04:08.1234528Z 2025-09-07T10:04:08.1234660Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:04:08.1235323Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 491, in torch_dynamo_resume_in_forward_and_backward_pass_at_486 2025-09-07T10:04:08.1235942Z pred = mod(*cloned_inputs) 2025-09-07T10:04:08.1236328Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T10:04:08.1236755Z return self.forward_once(x) 2025-09-07T10:04:08.1237169Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T10:04:08.1237622Z yolo_out.append(module(x, out)) 2025-09-07T10:04:08.1238026Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T10:04:08.1238480Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T10:04:08.1238944Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T10:04:08.1239412Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T10:04:08.1239616Z 2025-09-07T10:04:08.3517796Z cudagraph partition into 2 partitions 2025-09-07T10:04:46.3742997Z 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 2025-09-07T10:04:46.3744126Z pred = mod(*cloned_inputs) 2025-09-07T10:04:46.3744575Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T10:04:46.3745057Z return self.forward_once(x) 2025-09-07T10:04:46.3745521Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 374, in forward_once 2025-09-07T10:04:46.3745977Z x = module(x) 2025-09-07T10:04:46.3746109Z 2025-09-07T10:04:46.3746114Z 2025-09-07T10:04:49.1174441Z W0907 10:04:49.116000 133399 site-packages/torch/_logging/_internal.py:1199] [6/0] Profiler function will be ignored 2025-09-07T10:05:21.8535278Z 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 2025-09-07T10:05:21.8536532Z pred = mod(*cloned_inputs) 2025-09-07T10:05:21.8536989Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T10:05:21.8537457Z return self.forward_once(x) 2025-09-07T10:05:21.8537936Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 374, in forward_once 2025-09-07T10:05:21.8538378Z x = module(x) 2025-09-07T10:05:21.8538511Z 2025-09-07T10:05:21.8538516Z 2025-09-07T10:05:23.2412623Z pass 2025-09-07T10:05:29.4852373Z accuracy pass_rate=80.00% 2025-09-07T10:05:29.4865812Z calls_captured gmean=0.00x mean=874.200x 2025-09-07T10:05:29.4869862Z unique_graphs gmean=0.00x mean=6.333x 2025-09-07T10:05:29.4873443Z graph_breaks gmean=0.00x mean=8.600x 2025-09-07T10:05:29.4876850Z unique_graph_breaks gmean=0.00x mean=4.733x 2025-09-07T10:05:29.4880198Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T10:05:29.4883975Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T10:05:29.4887207Z cudagraph_skips gmean=0.00x mean=1.200x 2025-09-07T10:05:29.4888217Z compilation_latency mean=70.152 seconds 2025-09-07T10:05:30.3350725Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs_low_precision-true* ]] 2025-09-07T10:05:30.3352179Z + [[ training == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T10:05:30.3352475Z + for target in "${targets[@]}" 2025-09-07T10:05:30.3352734Z + target_flag=('--performance') 2025-09-07T10:05:30.3352977Z + local target_flag 2025-09-07T10:05:30.3353213Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T10:05:30.3353509Z + target_flag+=(--cold-start-latency) 2025-09-07T10:05:30.3354652Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *freezing-true* ]] 2025-09-07T10:05:30.3356675Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *default-true* ]] 2025-09-07T10:05:30.3358676Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --training --amp --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv 2025-09-07T10:05:30.8772761Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:05:30.8774075Z import pynvml # type: ignore[import] 2025-09-07T10:05:34.7098184Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T10:05:34.7099800Z import pynvml # type: ignore[import] 2025-09-07T10:05:37.1753336Z 2025-09-07T10:05:38.9111610Z loading model: 0it [00:00, ?it/s] 2025-09-07T10:05:38.9111848Z 2025-09-07T10:05:39.0206232Z Loading pipeline components...: 0% 0/6 [00:00 will be ignored 2025-09-07T10:10:17.2341048Z 2025-09-07T10:10:17.5213759Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:14:59.4966410Z 2025-09-07T10:14:59.6016108Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:17:25.2994594Z 2025-09-07T10:17:25.4112409Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:21:10.6279434Z 2025-09-07T10:21:11.0095662Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:23:39.3732991Z 2025-09-07T10:23:39.4959505Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:23:57.9875583Z 2025-09-07T10:23:58.0922143Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:24:51.7267099Z W0907 10:24:51.723000 188971 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T10:24:51.7268053Z W0907 10:24:51.723000 188971 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T10:24:51.7268999Z W0907 10:24:51.723000 188971 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T10:24:51.7269628Z W0907 10:24:51.723000 188971 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:24:51.7270086Z W0907 10:24:51.723000 188971 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:25:36.8653696Z W0907 10:25:36.864000 188971 site-packages/torch/_logging/_internal.py:1199] [50/0] Profiler function will be ignored 2025-09-07T10:25:48.1374967Z W0907 10:25:48.136000 188971 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T10:25:48.1376876Z W0907 10:25:48.136000 188971 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] function: 'roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:203) 2025-09-07T10:25:48.1378290Z W0907 10:25:48.136000 188971 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] last reason: 29/7: tensor 'boxes' requires_grad mismatch. expected requires_grad=1 2025-09-07T10:25:48.1379296Z W0907 10:25:48.136000 188971 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T10:25:48.1380680Z W0907 10:25:48.136000 188971 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T10:26:02.2899211Z 2025-09-07T10:26:02.4456545Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:27:51.7865295Z 2025-09-07T10:27:51.9538244Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:32:46.7668691Z 2025-09-07T10:32:47.2956968Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:37:32.6791540Z 2025-09-07T10:37:32.8189314Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:40:00.4033291Z 2025-09-07T10:40:00.5767891Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:43:51.5247653Z 2025-09-07T10:43:52.1543231Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:46:23.8766331Z 2025-09-07T10:46:24.0110700Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:46:42.3804711Z 2025-09-07T10:46:42.4845142Z running benchmark: 0% 0/30 [00:00 2025-09-07T10:47:33.4392494Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4392995Z 2025-09-07T10:47:33.4393226Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:47:33.4394132Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:47:33.4395018Z anchors = self.anchor_generator(images, features) 2025-09-07T10:47:33.4395947Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:47:33.4396881Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:47:33.4397834Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:47:33.4398981Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4400084Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:47:33.4401398Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4401896Z 2025-09-07T10:47:33.4402141Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:47:33.4403031Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:47:33.4403901Z anchors = self.anchor_generator(images, features) 2025-09-07T10:47:33.4404823Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:47:33.4405746Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:47:33.4406692Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:47:33.4407821Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4408926Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:47:33.4410016Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4410696Z 2025-09-07T10:47:33.4410949Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:47:33.4411839Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:47:33.4412700Z anchors = self.anchor_generator(images, features) 2025-09-07T10:47:33.4413611Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:47:33.4414537Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:47:33.4415697Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:47:33.4416844Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4418148Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:47:33.4419369Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4419874Z 2025-09-07T10:47:33.4420104Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T10:47:33.4421215Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T10:47:33.4422084Z anchors = self.anchor_generator(images, features) 2025-09-07T10:47:33.4423066Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T10:47:33.4424001Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T10:47:33.4424957Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T10:47:33.4426092Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4427216Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T10:47:33.4428306Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T10:47:33.4428811Z 2025-09-07T10:47:33.4572110Z cudagraph partition into 2 partitions 2025-09-07T10:47:36.6294696Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T10:47:36.6296273Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T10:47:36.6297429Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] or: 2025-09-07T10:47:36.6298529Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T10:47:36.6299928Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] to include these operations in the captured graph. 2025-09-07T10:47:36.6301563Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:47:36.6302694Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break: from user code at: 2025-09-07T10:47:36.6303873Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T10:47:36.6305251Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T10:47:36.6306478Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T10:47:36.6307616Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T10:47:36.6308692Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T10:47:36.6310087Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T10:47:36.6311260Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T10:47:36.6389839Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T10:47:36.6390958Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T10:47:36.6391949Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T10:47:36.6392974Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T10:47:36.6393959Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T10:47:36.6394617Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:47:36.6395112Z W0907 10:47:36.628000 248049 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T10:47:36.8846076Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:47:36.8846883Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T10:47:36.8847727Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T10:47:36.8848071Z 2025-09-07T10:47:40.4915780Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T10:47:40.4916568Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T10:47:40.4917334Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T10:47:40.4917676Z 2025-09-07T10:48:19.8672424Z W0907 10:48:19.866000 248049 site-packages/torch/_logging/_internal.py:1199] [50/0] Profiler function will be ignored 2025-09-07T10:48:31.2255272Z W0907 10:48:31.224000 248049 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T10:48:31.2257127Z W0907 10:48:31.224000 248049 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] function: 'roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:203) 2025-09-07T10:48:31.2258638Z W0907 10:48:31.224000 248049 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] last reason: 29/7: tensor 'boxes' requires_grad mismatch. expected requires_grad=1 2025-09-07T10:48:31.2259508Z W0907 10:48:31.224000 248049 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T10:48:31.2260809Z W0907 10:48:31.224000 248049 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T10:48:44.6518429Z 2025-09-07T10:48:44.7906396Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:50:36.7529621Z 2025-09-07T10:50:36.8594681Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T10:55:30.7759439Z 2025-09-07T10:55:31.3487263Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:00:23.0016992Z 2025-09-07T11:00:24.0619024Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:02:55.5486299Z 2025-09-07T11:02:56.3829524Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:06:53.9784016Z 2025-09-07T11:06:54.7306980Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:09:29.8914560Z 2025-09-07T11:09:30.0778293Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:09:49.3351546Z 2025-09-07T11:09:49.4436208Z running benchmark: 0% 0/30 [00:00 2025-09-07T11:10:45.3056784Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3057125Z 2025-09-07T11:10:45.3057286Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T11:10:45.3057936Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T11:10:45.3058532Z anchors = self.anchor_generator(images, features) 2025-09-07T11:10:45.3059156Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T11:10:45.3059878Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T11:10:45.3060623Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T11:10:45.3061326Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3062016Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T11:10:45.3062774Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3063085Z 2025-09-07T11:10:45.3063227Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T11:10:45.3063780Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T11:10:45.3064314Z anchors = self.anchor_generator(images, features) 2025-09-07T11:10:45.3064875Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T11:10:45.3065443Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T11:10:45.3066036Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T11:10:45.3066731Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3067416Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T11:10:45.3068091Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3068398Z 2025-09-07T11:10:45.3068543Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T11:10:45.3069093Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T11:10:45.3069638Z anchors = self.anchor_generator(images, features) 2025-09-07T11:10:45.3070349Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T11:10:45.3070905Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T11:10:45.3071449Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T11:10:45.3072192Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3072793Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T11:10:45.3073589Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3073866Z 2025-09-07T11:10:45.3073996Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T11:10:45.3074487Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T11:10:45.3074976Z anchors = self.anchor_generator(images, features) 2025-09-07T11:10:45.3075474Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T11:10:45.3075986Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T11:10:45.3076512Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T11:10:45.3077139Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3077762Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T11:10:45.3078350Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T11:10:45.3078621Z 2025-09-07T11:10:45.3243513Z cudagraph partition into 2 partitions 2025-09-07T11:10:48.4871409Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T11:10:48.4872412Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T11:10:48.4873202Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] or: 2025-09-07T11:10:48.4873934Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T11:10:48.4874836Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] to include these operations in the captured graph. 2025-09-07T11:10:48.4875556Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T11:10:48.4876214Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break: from user code at: 2025-09-07T11:10:48.4877501Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T11:10:48.4879061Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T11:10:48.4880497Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T11:10:48.4881711Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T11:10:48.4882697Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T11:10:48.4883670Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T11:10:48.4885165Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T11:10:48.4886442Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T11:10:48.4887587Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T11:10:48.4888597Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T11:10:48.4889610Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T11:10:48.4890763Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T11:10:48.4891400Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T11:10:48.4891863Z W0907 11:10:48.486000 308121 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T11:10:48.7357914Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T11:10:48.7358633Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T11:10:48.7359377Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T11:10:48.7359678Z 2025-09-07T11:10:51.0164376Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T11:10:51.0165226Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T11:10:51.0166005Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T11:10:51.0166321Z 2025-09-07T11:11:29.1417733Z W0907 11:11:29.140000 308121 site-packages/torch/_logging/_internal.py:1199] [50/0] Profiler function will be ignored 2025-09-07T11:11:40.4294702Z W0907 11:11:40.428000 308121 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T11:11:40.4296104Z W0907 11:11:40.428000 308121 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] function: 'roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:203) 2025-09-07T11:11:40.4297422Z W0907 11:11:40.428000 308121 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] last reason: 29/7: tensor 'boxes' requires_grad mismatch. expected requires_grad=1 2025-09-07T11:11:40.4298557Z W0907 11:11:40.428000 308121 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T11:11:40.4299793Z W0907 11:11:40.428000 308121 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T11:11:54.1454471Z 2025-09-07T11:11:54.2859601Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:13:46.5804092Z 2025-09-07T11:13:47.1059625Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:23:30.3893695Z 2025-09-07T11:23:30.6816667Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:32:45.9527332Z 2025-09-07T11:32:46.0964483Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:36:43.6583967Z 2025-09-07T11:36:43.7781068Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:43:18.8679328Z 2025-09-07T11:43:19.2416202Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:47:29.8039904Z 2025-09-07T11:47:29.9231162Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:47:54.5981614Z 2025-09-07T11:47:54.7053915Z running benchmark: 0% 0/30 [00:00 2025-09-07T11:49:13.1786511Z W0907 11:49:13.176000 371959 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T11:49:13.1787520Z W0907 11:49:13.176000 371959 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T11:49:13.1788498Z W0907 11:49:13.176000 371959 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T11:49:13.1789143Z W0907 11:49:13.176000 371959 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T11:49:13.1789626Z W0907 11:49:13.176000 371959 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T11:50:46.1838315Z W0907 11:50:46.182000 371959 site-packages/torch/_logging/_internal.py:1199] [50/0] Profiler function will be ignored 2025-09-07T11:51:03.9823670Z W0907 11:51:03.981000 371959 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T11:51:03.9825779Z W0907 11:51:03.981000 371959 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] function: 'roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:203) 2025-09-07T11:51:03.9827043Z W0907 11:51:03.981000 371959 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] last reason: 29/7: tensor 'boxes' requires_grad mismatch. expected requires_grad=1 2025-09-07T11:51:03.9828119Z W0907 11:51:03.981000 371959 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T11:51:03.9829334Z W0907 11:51:03.981000 371959 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T11:51:30.0769872Z 2025-09-07T11:51:30.2336728Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T11:54:25.5258845Z 2025-09-07T11:54:25.6665766Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:01:31.2062548Z 2025-09-07T12:01:31.7237669Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:07:37.7566761Z 2025-09-07T12:07:37.8573153Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:10:54.2438127Z 2025-09-07T12:10:54.4225939Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:16:02.3155967Z 2025-09-07T12:16:02.9823373Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:19:22.4077327Z 2025-09-07T12:19:22.6756550Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:19:42.2334250Z 2025-09-07T12:19:42.3384176Z running benchmark: 0% 0/30 [00:00 2025-09-07T12:21:19.0420880Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0421172Z 2025-09-07T12:21:19.0421309Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:21:19.0421809Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:21:19.0422292Z anchors = self.anchor_generator(images, features) 2025-09-07T12:21:19.0422800Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:21:19.0423393Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:21:19.0423930Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:21:19.0424555Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0425160Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:21:19.0425755Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0426029Z 2025-09-07T12:21:19.0426163Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:21:19.0426653Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:21:19.0427120Z anchors = self.anchor_generator(images, features) 2025-09-07T12:21:19.0427739Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:21:19.0428264Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:21:19.0428794Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:21:19.0429409Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0430010Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:21:19.0430744Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0431022Z 2025-09-07T12:21:19.0431147Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:21:19.0431649Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:21:19.0432121Z anchors = self.anchor_generator(images, features) 2025-09-07T12:21:19.0432612Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:21:19.0433208Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:21:19.0433729Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:21:19.0434343Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0435063Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:21:19.0435653Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0435927Z 2025-09-07T12:21:19.0436061Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:21:19.0436546Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:21:19.0437015Z anchors = self.anchor_generator(images, features) 2025-09-07T12:21:19.0437508Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:21:19.0437996Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:21:19.0438530Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:21:19.0439146Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0439746Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:21:19.0440463Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:21:19.0440738Z 2025-09-07T12:21:19.0588967Z cudagraph partition into 2 partitions 2025-09-07T12:21:23.3154858Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T12:21:23.3155881Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T12:21:23.3156640Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] or: 2025-09-07T12:21:23.3157381Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T12:21:23.3158249Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] to include these operations in the captured graph. 2025-09-07T12:21:23.3159451Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T12:21:23.3160137Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] Graph break: from user code at: 2025-09-07T12:21:23.3161767Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T12:21:23.3163182Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T12:21:23.3164416Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T12:21:23.3165562Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T12:21:23.3166629Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T12:21:23.3167779Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T12:21:23.3168959Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T12:21:23.3170193Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:21:23.3171390Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T12:21:23.3172359Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:21:23.3173320Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T12:21:23.3174244Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T12:21:23.3174861Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T12:21:23.3175318Z W0907 12:21:23.314000 517624 site-packages/torch/_dynamo/variables/tensor.py:1048] [17/0] 2025-09-07T12:21:23.5766866Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:21:23.5767753Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T12:21:23.5768630Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T12:21:23.5768980Z 2025-09-07T12:21:27.0857417Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:21:27.0858138Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T12:21:27.0858872Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T12:21:27.0859164Z 2025-09-07T12:21:33.4131649Z Autotune Choices Stats: 2025-09-07T12:21:33.4133138Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1074", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.05180799961090088, "best_triton_pos": 0} 2025-09-07T12:21:33.4216490Z AUTOTUNE mm(1000x12544, 12544x1024) 2025-09-07T12:21:33.4216790Z strides: [12544, 1], [1, 12544] 2025-09-07T12:21:33.4217026Z dtypes: torch.float16, torch.float16 2025-09-07T12:21:33.4217635Z triton_mm_1074 0.0518 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:21:33.4218229Z mm 0.0573 ms 90.4% 2025-09-07T12:21:33.4218776Z triton_mm_1080 0.0697 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:33.4219678Z triton_mm_1070 0.0760 ms 68.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:33.4220910Z triton_mm_1073 0.0953 ms 54.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:33.4222094Z triton_mm_1069 0.0968 ms 53.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:21:33.4223076Z triton_mm_1079 0.1029 ms 50.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:33.4224304Z triton_mm_1072 0.1180 ms 43.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:33.4225132Z triton_mm_1076 0.1186 ms 43.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:33.4225922Z triton_mm_1066 0.1205 ms 43.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:33.4226621Z SingleProcess AUTOTUNE benchmarking takes 0.5276 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T12:21:34.5666698Z Autotune Choices Stats: 2025-09-07T12:21:34.5668063Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011327999643981457, "best_triton_pos": 1, "best_triton_time": 0.011935999616980553, "best_triton_kernel": "triton_mm_1093", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T12:21:34.5798167Z AUTOTUNE mm(1000x1024, 1024x1024) 2025-09-07T12:21:34.5798444Z strides: [1024, 1], [1, 1024] 2025-09-07T12:21:34.5798722Z dtypes: torch.float16, torch.float16 2025-09-07T12:21:34.5799041Z mm 0.0113 ms 100.0% 2025-09-07T12:21:34.5799677Z triton_mm_1093 0.0119 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:21:34.5801110Z triton_mm_1099 0.0133 ms 84.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:34.5802182Z triton_mm_1092 0.0139 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:34.5803230Z triton_mm_1088 0.0140 ms 80.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:21:34.5804654Z triton_mm_1089 0.0140 ms 80.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:34.5805661Z triton_mm_1098 0.0152 ms 74.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:34.5806627Z triton_mm_1091 0.0154 ms 73.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:34.5807588Z triton_mm_1095 0.0156 ms 72.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:34.5808549Z triton_mm_1094 0.0186 ms 60.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:34.5809391Z SingleProcess AUTOTUNE benchmarking takes 0.2510 seconds and 0.5968 seconds precompiling for 20 choices 2025-09-07T12:21:36.3226177Z Autotune Choices Stats: 2025-09-07T12:21:36.3227895Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_1104", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, 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": 0.010015999898314476, "best_triton_pos": 0} 2025-09-07T12:21:36.3354062Z AUTOTUNE addmm(1000x91, 1000x1024, 1024x91) 2025-09-07T12:21:36.3362547Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T12:21:36.3362912Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:21:36.3364135Z triton_mm_1104 0.0100 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:36.3365143Z triton_mm_1108 0.0107 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:36.3366074Z triton_mm_1112 0.0125 ms 79.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:21:36.3366965Z triton_mm_1103 0.0129 ms 77.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:36.3367846Z triton_mm_1107 0.0131 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:21:36.3368735Z triton_mm_1101 0.0137 ms 73.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:21:36.3369618Z triton_mm_1102 0.0137 ms 73.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:36.3370821Z triton_mm_1111 0.0143 ms 70.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:36.3371729Z triton_mm_1118 0.0152 ms 66.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:36.3372635Z triton_mm_1110 0.0155 ms 64.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:36.3373413Z SingleProcess AUTOTUNE benchmarking takes 0.2647 seconds and 0.3364 seconds precompiling for 21 choices 2025-09-07T12:21:36.5808246Z Autotune Choices Stats: 2025-09-07T12:21:36.5810177Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_1127", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, 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": 0.010495999827980995, "best_triton_pos": 0} 2025-09-07T12:21:36.5935528Z AUTOTUNE addmm(1000x364, 1000x1024, 1024x364) 2025-09-07T12:21:36.5936044Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T12:21:36.5936567Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:21:36.5937722Z triton_mm_1127 0.0105 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:36.5939377Z triton_mm_1131 0.0121 ms 86.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:21:36.5941213Z triton_mm_1126 0.0129 ms 81.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:21:36.5942871Z triton_mm_1123 0.0131 ms 80.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:36.5944721Z triton_mm_1130 0.0137 ms 76.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:36.5945745Z triton_mm_1137 0.0139 ms 75.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:36.5946900Z triton_mm_1120 0.0141 ms 74.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:21:36.5947744Z triton_mm_1122 0.0145 ms 72.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:36.5948583Z triton_mm_1133 0.0151 ms 69.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:36.5949421Z triton_mm_1129 0.0152 ms 69.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:36.5950167Z SingleProcess AUTOTUNE benchmarking takes 0.2576 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T12:21:55.9248403Z Autotune Choices Stats: 2025-09-07T12:21:55.9251145Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.014175999909639359, "best_triton_pos": 1, "best_triton_time": 0.05244800075888634, "best_triton_kernel": "triton_convolution2d_1142", "best_triton_kernel_desc": "ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T12:21:55.9400899Z AUTOTUNE convolution(4x256x14x14, 256x256x3x3) 2025-09-07T12:21:55.9402186Z strides: [50176, 1, 3584, 256], [2304, 1, 768, 256] 2025-09-07T12:21:55.9402667Z dtypes: torch.float16, torch.float16 2025-09-07T12:21:55.9403085Z convolution 0.0142 ms 100.0% 2025-09-07T12:21:55.9404204Z triton_convolution2d_1142 0.0524 ms 27.0% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T12:21:55.9406100Z triton_convolution2d_1141 0.0687 ms 20.6% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T12:21:55.9408304Z triton_convolution2d_1144 0.0715 ms 19.8% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T12:21:55.9410179Z triton_convolution2d_1143 0.0740 ms 19.2% ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T12:21:55.9412065Z triton_convolution2d_1139 0.0906 ms 15.6% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T12:21:55.9413739Z triton_convolution2d_1138 0.1044 ms 13.6% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T12:21:55.9415399Z triton_convolution2d_1140 0.1902 ms 7.5% ALLOW_TF32=True, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T12:21:55.9416700Z SingleProcess AUTOTUNE benchmarking takes 0.1833 seconds and 0.0007 seconds precompiling for 8 choices 2025-09-07T12:21:57.1241870Z Autotune Choices Stats: 2025-09-07T12:21:57.1242970Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_1174", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, 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": 0.009088000282645226, "best_triton_pos": 0} 2025-09-07T12:21:57.1381416Z AUTOTUNE addmm(3136x91, 3136x256, 256x91) 2025-09-07T12:21:57.1382000Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T12:21:57.1382327Z dtypes: torch.float16, torch.float16, torch.float16 2025-09-07T12:21:57.1383175Z triton_mm_1174 0.0091 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:21:57.1384178Z triton_mm_1167 0.0097 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:21:57.1385179Z triton_mm_1177 0.0102 ms 89.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:57.1386167Z triton_mm_1178 0.0102 ms 89.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:21:57.1387143Z triton_mm_1168 0.0103 ms 88.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:57.1388101Z triton_mm_1176 0.0105 ms 86.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:57.1389057Z triton_mm_1180 0.0108 ms 84.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:21:57.1390097Z triton_mm_1175 0.0111 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:57.1391455Z triton_mm_1179 0.0116 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:21:57.1392433Z triton_mm_1184 0.0121 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:21:57.1393478Z SingleProcess AUTOTUNE benchmarking takes 0.2762 seconds and 0.9081 seconds precompiling for 21 choices 2025-09-07T12:22:11.5587353Z Autotune Choices Stats: 2025-09-07T12:22:11.5589349Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.04524800181388855, "best_triton_pos": 1, "best_triton_time": 0.04819199815392494, "best_triton_kernel": "triton_mm_1334", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T12:22:11.5722870Z AUTOTUNE mm(1024x1000, 1000x12544) 2025-09-07T12:22:11.5723141Z strides: [1, 1024], [12544, 1] 2025-09-07T12:22:11.5723405Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:11.5723682Z mm 0.0452 ms 100.0% 2025-09-07T12:22:11.5724434Z triton_mm_1334 0.0482 ms 93.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:11.5726191Z triton_mm_1335 0.0514 ms 88.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:11.5727679Z triton_mm_1336 0.0621 ms 72.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:11.5729638Z triton_mm_1327 0.0635 ms 71.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:11.5731581Z triton_mm_1331 0.0648 ms 69.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:11.5733236Z triton_mm_1329 0.0677 ms 66.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:11.5734819Z triton_mm_1332 0.0691 ms 65.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:11.5735772Z triton_mm_1328 0.0703 ms 64.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:11.5736710Z triton_mm_1330 0.0809 ms 56.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:11.5737517Z SingleProcess AUTOTUNE benchmarking takes 0.4081 seconds and 1.0603 seconds precompiling for 20 choices 2025-09-07T12:22:11.9891974Z Autotune Choices Stats: 2025-09-07T12:22:11.9893326Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011008000001311302, "best_triton_pos": 1, "best_triton_time": 0.011648000217974186, "best_triton_kernel": "triton_mm_1292", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T12:22:12.0024182Z AUTOTUNE mm(1024x1000, 1000x1024) 2025-09-07T12:22:12.0024493Z strides: [1, 1024], [1024, 1] 2025-09-07T12:22:12.0024758Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:12.0025033Z mm 0.0110 ms 100.0% 2025-09-07T12:22:12.0025667Z triton_mm_1292 0.0116 ms 94.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:12.0026682Z triton_mm_1298 0.0138 ms 79.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:12.0027961Z triton_mm_1291 0.0142 ms 77.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:12.0028950Z triton_mm_1288 0.0143 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:12.0029918Z triton_mm_1287 0.0145 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:22:12.0031319Z triton_mm_1290 0.0149 ms 73.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:12.0032293Z triton_mm_1294 0.0154 ms 71.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:12.0033285Z triton_mm_1297 0.0156 ms 70.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:12.0034351Z triton_mm_1289 0.0184 ms 59.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:12.0035401Z SingleProcess AUTOTUNE benchmarking takes 0.2213 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:12.2066380Z Autotune Choices Stats: 2025-09-07T12:22:12.2067635Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1253", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, 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", "best_time": 0.0080960001796484, "best_triton_pos": 0} 2025-09-07T12:22:12.2196320Z AUTOTUNE mm(1000x91, 91x1024) 2025-09-07T12:22:12.2196581Z strides: [91, 1], [1024, 1] 2025-09-07T12:22:12.2196823Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:12.2197487Z triton_mm_1253 0.0081 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:12.2198470Z triton_mm_1249 0.0084 ms 96.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:22:12.2199441Z triton_mm_1252 0.0084 ms 95.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:12.2200555Z triton_mm_1251 0.0085 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:12.2201536Z triton_mm_1254 0.0085 ms 95.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:12.2202513Z triton_mm_1250 0.0087 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:12.2203483Z triton_mm_1255 0.0088 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:12.2204448Z triton_mm_1244 0.0089 ms 90.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:22:12.2205410Z triton_mm_1256 0.0091 ms 89.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:12.2206463Z triton_mm_1248 0.0093 ms 86.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:22:12.2207256Z SingleProcess AUTOTUNE benchmarking takes 0.1962 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:13.1354391Z Autotune Choices Stats: 2025-09-07T12:22:13.1355786Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010495999827980995, "best_triton_pos": 1, "best_triton_time": 0.011807999573647976, "best_triton_kernel": "triton_mm_1273", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T12:22:13.1485033Z AUTOTUNE mm(1000x1024, 1024x1024) 2025-09-07T12:22:13.1485374Z strides: [1024, 1], [1024, 1] 2025-09-07T12:22:13.1485690Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:13.1486019Z mm 0.0105 ms 100.0% 2025-09-07T12:22:13.1486666Z triton_mm_1273 0.0118 ms 88.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:13.1487687Z triton_mm_1279 0.0134 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:22:13.1488982Z triton_mm_1272 0.0134 ms 78.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:13.1489944Z triton_mm_1268 0.0136 ms 77.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:22:13.1491737Z triton_mm_1269 0.0142 ms 74.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:13.1492733Z triton_mm_1271 0.0146 ms 71.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:13.1493711Z triton_mm_1275 0.0150 ms 70.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:13.1494736Z triton_mm_1278 0.0150 ms 70.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:13.1495704Z triton_mm_1270 0.0175 ms 60.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:13.1496489Z SingleProcess AUTOTUNE benchmarking takes 0.2180 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:13.5758676Z Autotune Choices Stats: 2025-09-07T12:22:13.5759724Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1193", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4", "best_time": 0.013151999562978745, "best_triton_pos": 0} 2025-09-07T12:22:13.5891835Z AUTOTUNE mm(364x1000, 1000x1024) 2025-09-07T12:22:13.5892123Z strides: [1, 364], [1024, 1] 2025-09-07T12:22:13.5892386Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:13.5893071Z triton_mm_1193 0.0132 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:13.5894116Z triton_mm_1192 0.0133 ms 98.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:22:13.5895526Z triton_mm_1196 0.0138 ms 95.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:13.5896435Z triton_mm_1195 0.0141 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:13.5897352Z triton_mm_1197 0.0141 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:13.5898251Z triton_mm_1199 0.0148 ms 89.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:13.5899147Z triton_mm_1187 0.0159 ms 82.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:22:13.5900038Z triton_mm_1186 0.0163 ms 80.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:22:13.5901110Z triton_mm_1202 0.0163 ms 80.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:13.5902132Z triton_mm_1203 0.0167 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:13.5903005Z SingleProcess AUTOTUNE benchmarking takes 0.2202 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:14.0115564Z Autotune Choices Stats: 2025-09-07T12:22:14.0117209Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.016287999227643013, "best_triton_pos": 1, "best_triton_time": 0.020128000527620316, "best_triton_kernel": "triton_mm_1208", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4"} 2025-09-07T12:22:14.0251810Z AUTOTUNE mm(91x1000, 1000x1024) 2025-09-07T12:22:14.0252093Z strides: [1, 91], [1024, 1] 2025-09-07T12:22:14.0252373Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:14.0252660Z mm 0.0163 ms 100.0% 2025-09-07T12:22:14.0253271Z triton_mm_1208 0.0201 ms 80.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:14.0254260Z triton_mm_1205 0.0209 ms 77.9% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T12:22:14.0255305Z triton_mm_1211 0.0218 ms 74.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:22:14.0256268Z triton_mm_1206 0.0229 ms 71.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:22:14.0257245Z triton_mm_1215 0.0239 ms 68.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:14.0258217Z triton_mm_1212 0.0252 ms 64.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:14.0259176Z triton_mm_1207 0.0287 ms 56.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:22:14.0260141Z triton_mm_1222 0.0301 ms 54.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:14.0261734Z triton_mm_1214 0.0310 ms 52.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:14.0262706Z SingleProcess AUTOTUNE benchmarking takes 0.2485 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:14.7934497Z Autotune Choices Stats: 2025-09-07T12:22:14.7935596Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_1234", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, 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", "best_time": 0.009440000168979168, "best_triton_pos": 0} 2025-09-07T12:22:14.8061907Z AUTOTUNE mm(1000x364, 364x1024) 2025-09-07T12:22:14.8062179Z strides: [364, 1], [1024, 1] 2025-09-07T12:22:14.8062446Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:14.8063202Z triton_mm_1234 0.0094 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:14.8064206Z triton_mm_1235 0.0098 ms 96.7% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:14.8065612Z triton_mm_1233 0.0098 ms 96.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:14.8066452Z triton_mm_1237 0.0100 ms 94.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:14.8067570Z triton_mm_1232 0.0107 ms 88.1% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:14.8068408Z triton_mm_1230 0.0108 ms 87.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T12:22:14.8069243Z triton_mm_1236 0.0111 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:14.8070088Z triton_mm_1240 0.0115 ms 82.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, 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 2025-09-07T12:22:14.8071214Z triton_mm_1239 0.0120 ms 78.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:14.8072076Z triton_mm_1231 0.0121 ms 78.2% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=False, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T12:22:14.8072805Z SingleProcess AUTOTUNE benchmarking takes 0.2036 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:15.1956521Z Autotune Choices Stats: 2025-09-07T12:22:15.1957754Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.04451199993491173, "best_triton_pos": 1, "best_triton_time": 0.05087999999523163, "best_triton_kernel": "triton_mm_1316", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4"} 2025-09-07T12:22:15.2082464Z AUTOTUNE mm(1000x1024, 1024x12544) 2025-09-07T12:22:15.2082750Z strides: [1024, 1], [12544, 1] 2025-09-07T12:22:15.2083016Z dtypes: torch.float16, torch.float16 2025-09-07T12:22:15.2083285Z mm 0.0445 ms 100.0% 2025-09-07T12:22:15.2083886Z triton_mm_1316 0.0509 ms 87.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:15.2085035Z triton_mm_1315 0.0521 ms 85.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:15.2086272Z triton_mm_1317 0.0573 ms 77.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T12:22:15.2087318Z triton_mm_1310 0.0681 ms 65.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:15.2088298Z triton_mm_1308 0.0713 ms 62.4% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:15.2089296Z triton_mm_1309 0.0718 ms 62.0% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:15.2090776Z triton_mm_1313 0.0760 ms 58.6% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T12:22:15.2091774Z triton_mm_1311 0.0774 ms 57.5% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T12:22:15.2092878Z triton_mm_1312 0.0777 ms 57.3% ACC_TYPE='tl.float32', ALLOW_TF32=True, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T12:22:15.2093970Z SingleProcess AUTOTUNE benchmarking takes 0.4016 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T12:22:23.6022417Z W0907 12:22:23.601000 517624 site-packages/torch/_logging/_internal.py:1199] [50/0] Profiler function will be ignored 2025-09-07T12:22:35.3845169Z W0907 12:22:35.383000 517624 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] torch._dynamo hit config.recompile_limit (8) 2025-09-07T12:22:35.3846475Z W0907 12:22:35.383000 517624 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] function: 'roi_align' (/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/roi_align.py:203) 2025-09-07T12:22:35.3847820Z W0907 12:22:35.383000 517624 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] last reason: 29/7: tensor 'boxes' requires_grad mismatch. expected requires_grad=1 2025-09-07T12:22:35.3848970Z W0907 12:22:35.383000 517624 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To log all recompilation reasons, use TORCH_LOGS="recompiles". 2025-09-07T12:22:35.3850643Z W0907 12:22:35.383000 517624 site-packages/torch/_dynamo/convert_frame.py:1358] [29/8] To diagnose recompilation issues, see https://pytorch.org/docs/main/torch.compiler_troubleshooting.html 2025-09-07T12:22:49.3614084Z 2025-09-07T12:22:49.5054379Z running benchmark: 0% 0/30 [00:00 will be ignored 2025-09-07T12:25:03.3368027Z 2025-09-07T12:25:03.4729815Z running benchmark: 0% 0/30 [00:00 2025-09-07T12:30:23.3772290Z W0907 12:30:23.374000 553796 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:30:23.3773253Z W0907 12:30:23.374000 553796 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T12:30:23.3774205Z W0907 12:30:23.374000 553796 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T12:30:23.3774834Z W0907 12:30:23.374000 553796 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:30:23.3775324Z W0907 12:30:23.374000 553796 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:30:31.2280675Z pass 2025-09-07T12:30:34.7735520Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:30:34.7736821Z import pynvml # type: ignore[import] 2025-09-07T12:30:37.2786568Z 2025-09-07T12:30:39.1259910Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:30:39.1261284Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:30:39.1357534Z cuda eval yolov3 2025-09-07T12:30:59.2354700Z pass 2025-09-07T12:31:02.1008083Z accuracy pass_rate=86.67% 2025-09-07T12:31:02.1013113Z calls_captured gmean=0.00x mean=386.933x 2025-09-07T12:31:02.1016390Z unique_graphs gmean=0.00x mean=2.333x 2025-09-07T12:31:02.1019392Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T12:31:02.1031282Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T12:31:02.1034586Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:31:02.1037998Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:31:02.1041657Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T12:31:02.1042733Z compilation_latency mean=12.115 seconds 2025-09-07T12:31:02.8982270Z + [[ training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-maxautotune-true-freeze_autotune_cudagraphs-true-cudagraphs_low_precision-true == *cudagraphs-true* ]] 2025-09-07T12:31:02.8986037Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T12:31:03.4608329Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:31:03.4619815Z import pynvml # type: ignore[import] 2025-09-07T12:31:07.1552330Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:31:07.1553556Z import pynvml # type: ignore[import] 2025-09-07T12:31:09.6400693Z 2025-09-07T12:31:11.2842754Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:31:11.2843035Z 2025-09-07T12:31:11.5135983Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T12:36:19.4197995Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4198338Z 2025-09-07T12:36:19.4198491Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:36:19.4199093Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:36:19.4199678Z anchors = self.anchor_generator(images, features) 2025-09-07T12:36:19.4200457Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:36:19.4201093Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:36:19.4201750Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:36:19.4202519Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4203257Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:36:19.4204026Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4204360Z 2025-09-07T12:36:19.4204513Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:36:19.4205118Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:36:19.4205707Z anchors = self.anchor_generator(images, features) 2025-09-07T12:36:19.4206326Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:36:19.4206944Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:36:19.4207705Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:36:19.4208333Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4208934Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:36:19.4209530Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4209797Z 2025-09-07T12:36:19.4209927Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:36:19.4210543Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:36:19.4211025Z anchors = self.anchor_generator(images, features) 2025-09-07T12:36:19.4211546Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:36:19.4212051Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:36:19.4212586Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:36:19.4213319Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4213931Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:36:19.4214532Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4214889Z 2025-09-07T12:36:19.4215107Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T12:36:19.4215618Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T12:36:19.4216104Z anchors = self.anchor_generator(images, features) 2025-09-07T12:36:19.4216624Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T12:36:19.4217136Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T12:36:19.4217669Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T12:36:19.4218300Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4218894Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T12:36:19.4219494Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T12:36:19.4219767Z 2025-09-07T12:36:19.4387969Z cudagraph partition into 2 partitions 2025-09-07T12:36:20.7373279Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T12:36:20.7374902Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T12:36:20.7376148Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] or: 2025-09-07T12:36:20.7377389Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T12:36:20.7378211Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] to include these operations in the captured graph. 2025-09-07T12:36:20.7378867Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:36:20.7379450Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break: from user code at: 2025-09-07T12:36:20.7381179Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T12:36:20.7382493Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T12:36:20.7383723Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T12:36:20.7384778Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T12:36:20.7385775Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T12:36:20.7386707Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T12:36:20.7387814Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T12:36:20.7388766Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:36:20.7389999Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T12:36:20.7391079Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:36:20.7392020Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T12:36:20.7392955Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T12:36:20.7393574Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:36:20.7394034Z W0907 12:36:20.736000 558516 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:36:31.9870807Z pass 2025-09-07T12:36:35.6712459Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:36:35.6713660Z import pynvml # type: ignore[import] 2025-09-07T12:36:38.1641325Z 2025-09-07T12:36:40.1877757Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:36:40.1878116Z loading model: 0it [00:02, ?it/s] 2025-09-07T12:36:40.1969890Z cuda eval yolov3 2025-09-07T12:36:52.2574484Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:36:52.2575137Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T12:36:52.2575710Z return mod(*inputs) 2025-09-07T12:36:52.2576123Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T12:36:52.2576510Z return self.forward_once(x) 2025-09-07T12:36:52.2576893Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T12:36:52.2577295Z yolo_out.append(module(x, out)) 2025-09-07T12:36:52.2578008Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T12:36:52.2578427Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T12:36:52.2578861Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T12:36:52.2579299Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T12:36:52.2579487Z 2025-09-07T12:36:52.2579615Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:36:52.2580081Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T12:36:52.2588441Z return mod(*inputs) 2025-09-07T12:36:52.2588845Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T12:36:52.2589224Z return self.forward_once(x) 2025-09-07T12:36:52.2589615Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T12:36:52.2590018Z yolo_out.append(module(x, out)) 2025-09-07T12:36:52.2590604Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T12:36:52.2591025Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T12:36:52.2591603Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T12:36:52.2592021Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T12:36:52.2592206Z 2025-09-07T12:36:52.2592330Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:36:52.2592770Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T12:36:52.2593327Z return mod(*inputs) 2025-09-07T12:36:52.2593764Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T12:36:52.2594137Z return self.forward_once(x) 2025-09-07T12:36:52.2594517Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T12:36:52.2594903Z yolo_out.append(module(x, out)) 2025-09-07T12:36:52.2595249Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T12:36:52.2595653Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T12:36:52.2596065Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T12:36:52.2596473Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T12:36:52.2596653Z 2025-09-07T12:36:52.3590502Z cudagraph partition into 2 partitions 2025-09-07T12:37:02.1123965Z pass 2025-09-07T12:37:04.8998653Z accuracy pass_rate=86.67% 2025-09-07T12:37:04.9010127Z calls_captured gmean=0.00x mean=378.067x 2025-09-07T12:37:04.9013582Z unique_graphs gmean=0.00x mean=2.267x 2025-09-07T12:37:04.9016884Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T12:37:04.9020343Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T12:37:04.9023918Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:37:04.9027136Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:37:04.9030738Z cudagraph_skips gmean=nanx mean=-0.400x 2025-09-07T12:37:04.9031987Z compilation_latency mean=12.260 seconds 2025-09-07T12:37:05.7039413Z + [[ 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* ]] 2025-09-07T12:37:05.7042408Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --dynamic-shapes --dynamic-batch-only --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T12:37:06.2416869Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:37:06.2418344Z import pynvml # type: ignore[import] 2025-09-07T12:37:09.9199208Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:37:09.9200479Z import pynvml # type: ignore[import] 2025-09-07T12:37:12.3675007Z 2025-09-07T12:37:14.1233444Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:37:14.1233683Z 2025-09-07T12:37:16.0238491Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T12:40:34.1826952Z W0907 12:40:34.180000 561856 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:40:34.1828030Z W0907 12:40:34.180000 561856 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T12:40:34.1829084Z W0907 12:40:34.180000 561856 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T12:40:34.1829779Z W0907 12:40:34.180000 561856 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:40:34.1830378Z W0907 12:40:34.180000 561856 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:40:38.9042573Z pass 2025-09-07T12:40:42.1339764Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:40:42.1341463Z import pynvml # type: ignore[import] 2025-09-07T12:40:44.6095051Z 2025-09-07T12:40:46.3792766Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:40:46.3793162Z loading model: 0it [00:01, ?it/s] 2025-09-07T12:40:46.3893519Z cuda eval yolov3 2025-09-07T12:40:56.4501459Z pass 2025-09-07T12:40:58.8442522Z accuracy pass_rate=86.67% 2025-09-07T12:40:58.8460949Z calls_captured gmean=0.00x mean=378.067x 2025-09-07T12:40:58.8466011Z unique_graphs gmean=0.00x mean=2.267x 2025-09-07T12:40:58.8470463Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T12:40:58.8474380Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T12:40:58.8478976Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:40:58.8482534Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:40:58.8486660Z cudagraph_skips gmean=nanx mean=-0.400x 2025-09-07T12:40:58.8488813Z compilation_latency mean=5.001 seconds 2025-09-07T12:41:00.1140916Z + [[ 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* ]] 2025-09-07T12:41:00.1142497Z + TORCHINDUCTOR_CPP_WRAPPER=1 2025-09-07T12:41:00.1143760Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T12:41:00.8411963Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:41:00.8413473Z import pynvml # type: ignore[import] 2025-09-07T12:41:05.8871812Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:41:05.8873739Z import pynvml # type: ignore[import] 2025-09-07T12:41:09.6291157Z 2025-09-07T12:41:11.4544585Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:41:11.4545025Z 2025-09-07T12:41:12.9331297Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T12:48:18.1310133Z W0907 12:48:18.128000 567236 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:48:18.1311305Z W0907 12:48:18.128000 567236 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T12:48:18.1312293Z W0907 12:48:18.128000 567236 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T12:48:18.1312906Z W0907 12:48:18.128000 567236 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:48:18.1313356Z W0907 12:48:18.128000 567236 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:48:34.5453350Z pass 2025-09-07T12:48:38.3231128Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:48:38.3232356Z import pynvml # type: ignore[import] 2025-09-07T12:48:40.8056428Z 2025-09-07T12:48:42.8798084Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:48:42.8799036Z loading model: 0it [00:02, ?it/s] 2025-09-07T12:48:42.8884449Z cuda eval yolov3 2025-09-07T12:49:11.0065404Z pass 2025-09-07T12:49:13.9188825Z accuracy pass_rate=86.67% 2025-09-07T12:49:13.9194264Z calls_captured gmean=0.00x mean=386.933x 2025-09-07T12:49:13.9197710Z unique_graphs gmean=0.00x mean=2.333x 2025-09-07T12:49:13.9201441Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T12:49:13.9212825Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T12:49:13.9216164Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:49:13.9219420Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:49:13.9223129Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T12:49:13.9224258Z compilation_latency mean=20.909 seconds 2025-09-07T12:49:14.7253312Z + [[ 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* ]] 2025-09-07T12:49:14.7255316Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T12:49:14.7257726Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 8 --freezing --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T12:49:15.2643692Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:49:15.2645102Z import pynvml # type: ignore[import] 2025-09-07T12:49:18.9478210Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:49:18.9479303Z import pynvml # type: ignore[import] 2025-09-07T12:49:21.4419527Z 2025-09-07T12:49:24.3214751Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:49:24.3215104Z 2025-09-07T12:49:24.8616211Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T12:54:59.0859039Z W0907 12:54:59.083000 575636 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T12:54:59.0860111Z W0907 12:54:59.083000 575636 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T12:54:59.0861201Z W0907 12:54:59.083000 575636 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T12:54:59.0861822Z W0907 12:54:59.083000 575636 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:54:59.0862289Z W0907 12:54:59.083000 575636 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T12:54:59.3325900Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:54:59.3326871Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T12:54:59.3327744Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T12:54:59.3328064Z 2025-09-07T12:54:59.6043723Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T12:54:59.6044900Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T12:54:59.6046030Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T12:54:59.6046482Z 2025-09-07T12:55:11.1407969Z pass 2025-09-07T12:55:14.8221543Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:55:14.8224167Z import pynvml # type: ignore[import] 2025-09-07T12:55:17.3646974Z 2025-09-07T12:55:19.4667651Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:55:19.4668042Z loading model: 0it [00:02, ?it/s] 2025-09-07T12:55:19.4765206Z cuda eval yolov3 2025-09-07T12:55:34.7018383Z cudagraph partition due to non gpu ops 2025-09-07T12:55:34.7018799Z cudagraph partition due to non gpu ops 2025-09-07T12:55:34.7019131Z cudagraph partition due to non gpu ops 2025-09-07T12:55:34.7700416Z cudagraph partition into 2 partitions 2025-09-07T12:55:49.9111289Z pass 2025-09-07T12:55:53.4892326Z accuracy pass_rate=86.67% 2025-09-07T12:55:53.4906513Z calls_captured gmean=0.00x mean=378.067x 2025-09-07T12:55:53.4909757Z unique_graphs gmean=0.00x mean=2.267x 2025-09-07T12:55:53.4914218Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T12:55:53.4917229Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T12:55:53.4921788Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T12:55:53.4924929Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T12:55:53.4928324Z cudagraph_skips gmean=nanx mean=-0.400x 2025-09-07T12:55:53.4929383Z compilation_latency mean=14.444 seconds 2025-09-07T12:55:54.8083188Z + [[ 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* ]] 2025-09-07T12:55:54.8085162Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T12:55:54.8085583Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T12:55:54.8087589Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 8 --freezing --output /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T12:55:55.5793618Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:55:55.5794677Z import pynvml # type: ignore[import] 2025-09-07T12:56:00.6308920Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T12:56:00.6311505Z import pynvml # type: ignore[import] 2025-09-07T12:56:03.5470944Z 2025-09-07T12:56:05.2702173Z loading model: 0it [00:00, ?it/s] 2025-09-07T12:56:05.2702438Z 2025-09-07T12:56:05.5517084Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T13:04:35.2485142Z W0907 13:04:35.245000 614825 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:04:35.2486080Z W0907 13:04:35.245000 614825 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T13:04:35.2487135Z W0907 13:04:35.245000 614825 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T13:04:35.2487760Z W0907 13:04:35.245000 614825 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:04:35.2488221Z W0907 13:04:35.245000 614825 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:04:35.4827527Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:04:35.4829028Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T13:04:35.4830841Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T13:04:35.4831175Z 2025-09-07T13:04:35.7152050Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:04:35.7152894Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T13:04:35.7153713Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T13:04:35.7154049Z 2025-09-07T13:04:46.4843808Z pass 2025-09-07T13:04:50.6544523Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:04:50.6545601Z import pynvml # type: ignore[import] 2025-09-07T13:04:53.1819952Z 2025-09-07T13:04:54.9665533Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:04:54.9665910Z loading model: 0it [00:01, ?it/s] 2025-09-07T13:04:54.9761011Z cuda eval yolov3 2025-09-07T13:05:17.9962875Z Autotune Choices Stats: 2025-09-07T13:05:17.9964543Z {"num_choices": 19, "num_triton_choices": 17, "best_kernel": "triton_mm_20", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8", "best_time": 0.02067199908196926, "best_triton_pos": 0} 2025-09-07T13:05:18.0554372Z AUTOTUNE addmm(196608x32, 196608x64, 64x32) 2025-09-07T13:05:18.0555105Z strides: [0, 1], [64, 1], [1, 64] 2025-09-07T13:05:18.0555440Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:18.0556143Z triton_mm_20 0.0207 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:18.0557121Z triton_mm_29 0.0212 ms 97.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:18.0558071Z triton_mm_17 0.0215 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:18.0559048Z triton_mm_23 0.0217 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.0560002Z triton_mm_24 0.0217 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:18.0561329Z triton_mm_26 0.0219 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:18.0562294Z triton_mm_28 0.0219 ms 94.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.0563262Z triton_mm_14 0.0227 ms 91.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T13:05:18.0564336Z triton_mm_22 0.0228 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:18.0565215Z triton_mm_25 0.0231 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.0565994Z SingleProcess AUTOTUNE benchmarking takes 0.4097 seconds and 0.0003 seconds precompiling for 19 choices 2025-09-07T13:05:18.5977291Z Autotune Choices Stats: 2025-09-07T13:05:18.5979289Z {"num_choices": 20, "num_triton_choices": 18, "best_kernel": "bias_addmm", "best_time": 0.013952000066637993, "best_triton_pos": 1, "best_triton_time": 0.014047999866306782, "best_triton_kernel": "triton_mm_60", "best_triton_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"} 2025-09-07T13:05:18.7186957Z AUTOTUNE addmm(49152x64, 49152x128, 128x64) 2025-09-07T13:05:18.7187464Z strides: [0, 1], [128, 1], [1, 128] 2025-09-07T13:05:18.7187989Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:18.7188544Z bias_addmm 0.0140 ms 100.0% 2025-09-07T13:05:18.7189576Z triton_mm_60 0.0140 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.7191546Z triton_mm_55 0.0142 ms 98.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.7193296Z triton_mm_51 0.0145 ms 96.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:18.7194454Z triton_mm_50 0.0146 ms 95.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T13:05:18.7195578Z triton_mm_57 0.0149 ms 93.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.7196545Z triton_mm_59 0.0150 ms 93.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T13:05:18.7197509Z triton_mm_58 0.0154 ms 90.8% 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 2025-09-07T13:05:18.7198459Z triton_mm_53 0.0155 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:18.7199418Z triton_mm_56 0.0163 ms 85.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:18.7200379Z SingleProcess AUTOTUNE benchmarking takes 0.3803 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:05:19.2657142Z Autotune Choices Stats: 2025-09-07T13:05:19.2658220Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_108", "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": 0.011359999887645245, "best_triton_pos": 0} 2025-09-07T13:05:19.2989034Z AUTOTUNE addmm(12288x128, 12288x256, 256x128) 2025-09-07T13:05:19.2989460Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T13:05:19.2989814Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:19.2990772Z triton_mm_108 0.0114 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 2025-09-07T13:05:19.2991725Z bias_addmm 0.0115 ms 98.9% 2025-09-07T13:05:19.2992342Z triton_mm_112 0.0115 ms 98.6% 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 2025-09-07T13:05:19.2993466Z triton_mm_118 0.0120 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:19.2994562Z triton_mm_115 0.0121 ms 93.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:19.2995524Z triton_mm_110 0.0122 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:19.2996492Z triton_mm_119 0.0122 ms 92.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:19.2997458Z triton_mm_114 0.0123 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:19.2998405Z triton_mm_111 0.0124 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 2025-09-07T13:05:19.2999384Z triton_mm_117 0.0128 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:19.3000401Z SingleProcess AUTOTUNE benchmarking takes 0.2979 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:19.9589124Z Autotune Choices Stats: 2025-09-07T13:05:19.9591934Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.012703999876976013, "best_triton_pos": 1, "best_triton_time": 0.013024000450968742, "best_triton_kernel": "triton_mm_893", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8"} 2025-09-07T13:05:20.1401664Z AUTOTUNE addmm(12288x128, 12288x384, 384x128) 2025-09-07T13:05:20.1402004Z strides: [0, 1], [384, 1], [1, 384] 2025-09-07T13:05:20.1402323Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:20.1402665Z bias_addmm 0.0127 ms 100.0% 2025-09-07T13:05:20.1403626Z triton_mm_893 0.0130 ms 97.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:20.1405344Z triton_mm_897 0.0131 ms 97.1% 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 2025-09-07T13:05:20.1407007Z triton_mm_904 0.0132 ms 95.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:20.1408619Z triton_mm_903 0.0136 ms 93.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:20.1410187Z triton_mm_896 0.0140 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:20.1412193Z triton_mm_900 0.0141 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 2025-09-07T13:05:20.1413808Z triton_mm_895 0.0146 ms 86.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:20.1414827Z triton_mm_899 0.0147 ms 86.5% 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 2025-09-07T13:05:20.1415686Z triton_mm_898 0.0150 ms 84.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:20.1416547Z SingleProcess AUTOTUNE benchmarking takes 0.4487 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:20.4785361Z Autotune Choices Stats: 2025-09-07T13:05:20.4787453Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.01065600011497736, "best_triton_pos": 1, "best_triton_time": 0.01071999967098236, "best_triton_kernel": "triton_mm_328", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T13:05:20.4960405Z AUTOTUNE addmm(3072x256, 3072x512, 512x256) 2025-09-07T13:05:20.4960704Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T13:05:20.4961027Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:20.4961349Z bias_addmm 0.0107 ms 100.0% 2025-09-07T13:05:20.4961978Z triton_mm_328 0.0107 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:20.4962999Z triton_mm_323 0.0112 ms 95.4% 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 2025-09-07T13:05:20.4964204Z triton_mm_327 0.0114 ms 93.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:20.4965440Z triton_mm_334 0.0123 ms 86.5% 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 2025-09-07T13:05:20.4966562Z triton_mm_333 0.0124 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:20.4967535Z triton_mm_324 0.0125 ms 84.9% 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 2025-09-07T13:05:20.4968484Z triton_mm_330 0.0126 ms 84.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:20.4969458Z triton_mm_326 0.0127 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:20.4970613Z triton_mm_317 0.0128 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 2025-09-07T13:05:20.4971482Z SingleProcess AUTOTUNE benchmarking takes 0.2972 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:21.1645657Z Autotune Choices Stats: 2025-09-07T13:05:21.1646774Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_782", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.011327999643981457, "best_triton_pos": 0} 2025-09-07T13:05:21.1805109Z AUTOTUNE addmm(3072x256, 3072x768, 768x256) 2025-09-07T13:05:21.1805417Z strides: [0, 1], [768, 1], [1, 768] 2025-09-07T13:05:21.1805750Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:21.1806895Z triton_mm_782 0.0113 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:21.1807907Z triton_mm_777 0.0128 ms 88.3% 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 2025-09-07T13:05:21.1808881Z triton_mm_781 0.0129 ms 88.1% 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 2025-09-07T13:05:21.1809999Z triton_mm_788 0.0133 ms 85.3% 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 2025-09-07T13:05:21.1811306Z triton_mm_778 0.0135 ms 84.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:21.1812291Z triton_mm_787 0.0139 ms 81.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:21.1813309Z triton_mm_780 0.0140 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 2025-09-07T13:05:21.1814251Z triton_mm_784 0.0141 ms 80.1% 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 2025-09-07T13:05:21.1814819Z addmm 0.0149 ms 75.8% 2025-09-07T13:05:21.1815354Z triton_mm_771 0.0153 ms 74.1% 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 2025-09-07T13:05:21.1816248Z SingleProcess AUTOTUNE benchmarking takes 0.2890 seconds and 0.0003 seconds precompiling for 21 choices 2025-09-07T13:05:21.5107363Z Autotune Choices Stats: 2025-09-07T13:05:21.5109470Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_539", "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": 0.009952000342309475, "best_triton_pos": 0} 2025-09-07T13:05:21.6815261Z AUTOTUNE addmm(768x512, 768x1024, 1024x512) 2025-09-07T13:05:21.6815812Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T13:05:21.6816411Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:21.6817592Z triton_mm_539 0.0100 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:21.6818648Z bias_addmm 0.0100 ms 99.0% 2025-09-07T13:05:21.6819648Z triton_mm_543 0.0112 ms 88.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:21.6821724Z triton_mm_538 0.0126 ms 78.7% 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 2025-09-07T13:05:21.6823430Z triton_mm_535 0.0127 ms 78.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:21.6824614Z triton_mm_542 0.0132 ms 75.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:21.6825485Z triton_mm_549 0.0134 ms 74.0% 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 2025-09-07T13:05:21.6826345Z triton_mm_532 0.0144 ms 69.1% 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 2025-09-07T13:05:21.6827168Z addmm 0.0145 ms 68.7% 2025-09-07T13:05:21.6827670Z triton_mm_534 0.0147 ms 67.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:21.6828408Z SingleProcess AUTOTUNE benchmarking takes 0.4423 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:22.2992303Z Autotune Choices Stats: 2025-09-07T13:05:22.2994022Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "bias_addmm", "best_time": 0.011615999974310398, "best_triton_pos": 1, "best_triton_time": 0.013088000006973743, "best_triton_kernel": "triton_mm_688", "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"} 2025-09-07T13:05:22.3908572Z AUTOTUNE addmm(768x512, 768x2048, 2048x512) 2025-09-07T13:05:22.3908912Z strides: [0, 1], [2048, 1], [1, 2048] 2025-09-07T13:05:22.3909256Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:22.3909600Z bias_addmm 0.0116 ms 100.0% 2025-09-07T13:05:22.3910624Z triton_mm_688 0.0131 ms 88.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:22.3911668Z triton_mm_692 0.0148 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:22.3912295Z addmm 0.0160 ms 72.7% 2025-09-07T13:05:22.3912896Z triton_mm_684 0.0180 ms 64.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:22.3914200Z triton_mm_698 0.0188 ms 61.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:22.3915318Z triton_mm_687 0.0199 ms 58.4% 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 2025-09-07T13:05:22.3916292Z triton_mm_691 0.0203 ms 57.3% 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 2025-09-07T13:05:22.3917260Z triton_mm_681 0.0215 ms 54.0% 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 2025-09-07T13:05:22.3918221Z triton_mm_683 0.0220 ms 52.8% 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 2025-09-07T13:05:22.3919069Z SingleProcess AUTOTUNE benchmarking takes 0.3711 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:23.2284666Z Autotune Choices Stats: 2025-09-07T13:05:23.2285885Z {"num_choices": 7, "num_triton_choices": 6, "best_kernel": "triton_convolution2d_2", "best_kernel_desc": "ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8", "best_time": 0.1273919939994812, "best_triton_pos": 0} 2025-09-07T13:05:23.2823112Z AUTOTUNE convolution(4x3x384x512, 32x3x3x3) 2025-09-07T13:05:23.2823670Z strides: [589824, 1, 1536, 3], [27, 1, 9, 3] 2025-09-07T13:05:23.2824169Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:23.2825454Z triton_convolution2d_2 0.1274 ms 100.0% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:05:23.2827266Z convolution 0.1430 ms 89.1% 2025-09-07T13:05:23.2828444Z triton_convolution2d_4 0.1508 ms 84.5% 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=8 2025-09-07T13:05:23.2830961Z triton_convolution2d_0 0.1683 ms 75.7% 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 2025-09-07T13:05:23.2833211Z triton_convolution2d_3 0.1750 ms 72.8% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=128, BLOCK_N=32, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:23.2835169Z triton_convolution2d_1 0.2133 ms 59.7% 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 2025-09-07T13:05:23.2836393Z triton_convolution2d_5 0.2387 ms 53.4% 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=8 2025-09-07T13:05:23.2837372Z SingleProcess AUTOTUNE benchmarking takes 0.2542 seconds and 0.0002 seconds precompiling for 7 choices 2025-09-07T13:05:23.4253667Z Autotune Choices Stats: 2025-09-07T13:05:23.4255886Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.04217600077390671, "best_triton_pos": 1, "best_triton_time": 0.04960000142455101, "best_triton_kernel": "triton_convolution2d_9", "best_triton_kernel_desc": "ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8"} 2025-09-07T13:05:23.4595512Z AUTOTUNE convolution(4x32x384x512, 64x32x3x3) 2025-09-07T13:05:23.4595831Z strides: [6291456, 1, 16384, 32], [288, 1, 96, 32] 2025-09-07T13:05:23.4596134Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:23.4596420Z convolution 0.0422 ms 100.0% 2025-09-07T13:05:23.4597331Z triton_convolution2d_9 0.0496 ms 85.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:23.4598576Z triton_convolution2d_12 0.0504 ms 83.7% 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 2025-09-07T13:05:23.4599796Z triton_convolution2d_10 0.0547 ms 77.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.4601327Z triton_convolution2d_11 0.0573 ms 73.5% 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=8 2025-09-07T13:05:23.4602544Z triton_convolution2d_7 0.0679 ms 62.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.4603743Z triton_convolution2d_6 0.1066 ms 39.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.4604969Z triton_convolution2d_8 0.1842 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=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:05:23.4605872Z SingleProcess AUTOTUNE benchmarking takes 0.1767 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:23.5921732Z Autotune Choices Stats: 2025-09-07T13:05:23.5923101Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.033695999532938004, "best_triton_pos": 1, "best_triton_time": 0.04016000032424927, "best_triton_kernel": "triton_convolution2d_36", "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"} 2025-09-07T13:05:23.6279432Z AUTOTUNE convolution(4x32x192x256, 64x32x3x3) 2025-09-07T13:05:23.6279731Z strides: [1572864, 1, 8192, 32], [288, 1, 96, 32] 2025-09-07T13:05:23.6280165Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:23.6280732Z convolution 0.0337 ms 100.0% 2025-09-07T13:05:23.6281430Z triton_convolution2d_36 0.0402 ms 83.9% 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 2025-09-07T13:05:23.6282582Z triton_convolution2d_33 0.0408 ms 82.5% 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 2025-09-07T13:05:23.6283716Z triton_convolution2d_34 0.0482 ms 69.9% 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 2025-09-07T13:05:23.6284842Z triton_convolution2d_35 0.0500 ms 67.5% 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 2025-09-07T13:05:23.6285965Z triton_convolution2d_31 0.0596 ms 56.5% 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 2025-09-07T13:05:23.6287184Z triton_convolution2d_30 0.1047 ms 32.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.6288396Z triton_convolution2d_32 0.1234 ms 27.3% 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 2025-09-07T13:05:23.6289300Z SingleProcess AUTOTUNE benchmarking takes 0.1676 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:23.7619350Z Autotune Choices Stats: 2025-09-07T13:05:23.7621961Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.030271999537944794, "best_triton_pos": 1, "best_triton_time": 0.04124800115823746, "best_triton_kernel": "triton_convolution2d_42", "best_triton_kernel_desc": "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"} 2025-09-07T13:05:23.7861722Z AUTOTUNE convolution(4x64x192x256, 128x64x3x3) 2025-09-07T13:05:23.7862257Z strides: [3145728, 1, 16384, 64], [576, 1, 192, 64] 2025-09-07T13:05:23.7862864Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:23.7863327Z convolution 0.0303 ms 100.0% 2025-09-07T13:05:23.7864535Z triton_convolution2d_42 0.0412 ms 73.4% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:23.7865831Z triton_convolution2d_40 0.0425 ms 71.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:23.7867082Z triton_convolution2d_41 0.0484 ms 62.5% 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 2025-09-07T13:05:23.7868492Z triton_convolution2d_43 0.0520 ms 58.3% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:23.7869711Z triton_convolution2d_37 0.0670 ms 45.2% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.7871208Z triton_convolution2d_38 0.0681 ms 44.5% 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 2025-09-07T13:05:23.7872447Z triton_convolution2d_39 0.1594 ms 19.0% 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 2025-09-07T13:05:23.7873429Z SingleProcess AUTOTUNE benchmarking takes 0.1574 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:23.9111687Z Autotune Choices Stats: 2025-09-07T13:05:23.9113955Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.02687999978661537, "best_triton_pos": 1, "best_triton_time": 0.03308799862861633, "best_triton_kernel": "triton_convolution2d_67", "best_triton_kernel_desc": "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"} 2025-09-07T13:05:23.9283341Z AUTOTUNE convolution(4x64x96x128, 128x64x3x3) 2025-09-07T13:05:23.9283665Z strides: [786432, 1, 8192, 64], [576, 1, 192, 64] 2025-09-07T13:05:23.9284171Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:23.9284739Z convolution 0.0269 ms 100.0% 2025-09-07T13:05:23.9286049Z triton_convolution2d_67 0.0331 ms 81.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:23.9288215Z triton_convolution2d_65 0.0333 ms 80.7% 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 2025-09-07T13:05:23.9290686Z triton_convolution2d_68 0.0401 ms 67.0% 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 2025-09-07T13:05:23.9292655Z triton_convolution2d_66 0.0409 ms 65.7% 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 2025-09-07T13:05:23.9294742Z triton_convolution2d_63 0.0541 ms 49.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.9295881Z triton_convolution2d_62 0.0610 ms 44.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:23.9296950Z triton_convolution2d_64 0.1388 ms 19.4% 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 2025-09-07T13:05:23.9297797Z SingleProcess AUTOTUNE benchmarking takes 0.1415 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:24.0658344Z Autotune Choices Stats: 2025-09-07T13:05:24.0660968Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.024320000782608986, "best_triton_pos": 1, "best_triton_time": 0.03728000074625015, "best_triton_kernel": "triton_convolution2d_98", "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"} 2025-09-07T13:05:24.2227965Z AUTOTUNE convolution(4x128x96x128, 256x128x3x3) 2025-09-07T13:05:24.2228518Z strides: [1572864, 1, 16384, 128], [1152, 1, 384, 128] 2025-09-07T13:05:24.2229019Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:24.2229467Z convolution 0.0243 ms 100.0% 2025-09-07T13:05:24.2231498Z triton_convolution2d_98 0.0373 ms 65.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.2233552Z triton_convolution2d_97 0.0416 ms 58.5% 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 2025-09-07T13:05:24.2235494Z triton_convolution2d_99 0.0430 ms 56.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.2236740Z triton_convolution2d_100 0.0455 ms 53.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.2237973Z triton_convolution2d_94 0.0577 ms 42.2% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.2239207Z triton_convolution2d_95 0.0584 ms 41.6% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.2240662Z triton_convolution2d_96 0.1962 ms 12.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:05:24.2241717Z SingleProcess AUTOTUNE benchmarking takes 0.2888 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:24.3528852Z Autotune Choices Stats: 2025-09-07T13:05:24.3531538Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.022816000506281853, "best_triton_pos": 1, "best_triton_time": 0.03497600182890892, "best_triton_kernel": "triton_convolution2d_124", "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"} 2025-09-07T13:05:24.4660660Z AUTOTUNE convolution(4x128x48x64, 256x128x3x3) 2025-09-07T13:05:24.4661219Z strides: [393216, 1, 8192, 128], [1152, 1, 384, 128] 2025-09-07T13:05:24.4661725Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:24.4662188Z convolution 0.0228 ms 100.0% 2025-09-07T13:05:24.4663543Z triton_convolution2d_124 0.0350 ms 65.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.4666378Z triton_convolution2d_123 0.0392 ms 58.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.4667468Z triton_convolution2d_125 0.0400 ms 57.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.4668693Z triton_convolution2d_126 0.0424 ms 53.8% 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 2025-09-07T13:05:24.4669765Z triton_convolution2d_120 0.0553 ms 41.3% 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 2025-09-07T13:05:24.4671077Z triton_convolution2d_121 0.0553 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 2025-09-07T13:05:24.4672156Z triton_convolution2d_122 0.1836 ms 12.4% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:05:24.4673023Z SingleProcess AUTOTUNE benchmarking takes 0.2423 seconds and 0.0004 seconds precompiling for 8 choices 2025-09-07T13:05:24.6543129Z Autotune Choices Stats: 2025-09-07T13:05:24.6545317Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.024064000695943832, "best_triton_pos": 1, "best_triton_time": 0.05708799883723259, "best_triton_kernel": "triton_convolution2d_313", "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"} 2025-09-07T13:05:24.7085560Z AUTOTUNE convolution(4x256x48x64, 512x256x3x3) 2025-09-07T13:05:24.7086092Z strides: [786432, 1, 16384, 256], [2304, 1, 768, 256] 2025-09-07T13:05:24.7086596Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:24.7087080Z convolution 0.0241 ms 100.0% 2025-09-07T13:05:24.7088515Z triton_convolution2d_313 0.0571 ms 42.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.7091251Z triton_convolution2d_312 0.0712 ms 33.8% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.7093254Z triton_convolution2d_314 0.0719 ms 33.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.7095212Z triton_convolution2d_315 0.0763 ms 31.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.7096278Z triton_convolution2d_309 0.1022 ms 23.5% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.7097342Z triton_convolution2d_310 0.1053 ms 22.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.7098408Z triton_convolution2d_311 0.1992 ms 12.1% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:05:24.7099255Z SingleProcess AUTOTUNE benchmarking takes 0.2082 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:24.8612077Z Autotune Choices Stats: 2025-09-07T13:05:24.8614285Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.022784000262618065, "best_triton_pos": 1, "best_triton_time": 0.05526399984955788, "best_triton_kernel": "triton_convolution2d_339", "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"} 2025-09-07T13:05:24.9918935Z AUTOTUNE convolution(4x256x24x32, 512x256x3x3) 2025-09-07T13:05:24.9919260Z strides: [196608, 1, 8192, 256], [2304, 1, 768, 256] 2025-09-07T13:05:24.9919562Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:24.9919839Z convolution 0.0228 ms 100.0% 2025-09-07T13:05:24.9920945Z triton_convolution2d_339 0.0553 ms 41.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:24.9922205Z triton_convolution2d_338 0.0695 ms 32.8% 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 2025-09-07T13:05:24.9923447Z triton_convolution2d_340 0.0698 ms 32.6% 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 2025-09-07T13:05:24.9924694Z triton_convolution2d_341 0.0754 ms 30.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=256, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:24.9925876Z triton_convolution2d_335 0.0992 ms 23.0% 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 2025-09-07T13:05:24.9927024Z triton_convolution2d_336 0.1025 ms 22.2% 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 2025-09-07T13:05:24.9928268Z triton_convolution2d_337 0.1909 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 2025-09-07T13:05:24.9929177Z SingleProcess AUTOTUNE benchmarking takes 0.2827 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:25.2327478Z Autotune Choices Stats: 2025-09-07T13:05:25.2329752Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023391999304294586, "best_triton_pos": 1, "best_triton_time": 0.11075200140476227, "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=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4"} 2025-09-07T13:05:25.2716459Z AUTOTUNE convolution(4x512x24x32, 1024x512x3x3) 2025-09-07T13:05:25.2716777Z strides: [393216, 1, 16384, 512], [4608, 1, 1536, 512] 2025-09-07T13:05:25.2717069Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:25.2717334Z convolution 0.0234 ms 100.0% 2025-09-07T13:05:25.2718010Z triton_convolution2d_528 0.1108 ms 21.1% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:25.2719155Z triton_convolution2d_529 0.1335 ms 17.5% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:25.2720499Z triton_convolution2d_527 0.1372 ms 17.0% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:25.2721677Z triton_convolution2d_530 0.1458 ms 16.0% 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 2025-09-07T13:05:25.2722976Z triton_convolution2d_524 0.1978 ms 11.8% 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=2, STRIDE_W=2, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:25.2724124Z triton_convolution2d_525 0.2041 ms 11.5% 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 2025-09-07T13:05:25.2725362Z triton_convolution2d_526 0.3384 ms 6.9% ALLOW_TF32=False, BLOCK_K=16, BLOCK_M=1024, BLOCK_N=16, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=2, STRIDE_W=2, UNROLL=False, num_stages=1, num_warps=8 2025-09-07T13:05:25.2726288Z SingleProcess AUTOTUNE benchmarking takes 0.2447 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:25.4773047Z Autotune Choices Stats: 2025-09-07T13:05:25.4775260Z {"num_choices": 8, "num_triton_choices": 7, "best_kernel": "convolution", "best_time": 0.023264000192284584, "best_triton_pos": 1, "best_triton_time": 0.10953599959611893, "best_triton_kernel": "triton_convolution2d_554", "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"} 2025-09-07T13:05:25.4978965Z AUTOTUNE convolution(4x512x12x16, 1024x512x3x3) 2025-09-07T13:05:25.4979501Z strides: [98304, 1, 8192, 512], [4608, 1, 1536, 512] 2025-09-07T13:05:25.4980026Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:05:25.4980938Z convolution 0.0233 ms 100.0% 2025-09-07T13:05:25.4982121Z triton_convolution2d_554 0.1095 ms 21.2% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=64, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=4 2025-09-07T13:05:25.4984524Z triton_convolution2d_555 0.1314 ms 17.7% ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=256, GROUPS=1, KERNEL_H=3, KERNEL_W=3, PADDING_H=1, PADDING_W=1, STRIDE_H=1, STRIDE_W=1, UNROLL=False, num_stages=2, num_warps=8 2025-09-07T13:05:25.4986083Z triton_convolution2d_553 0.1347 ms 17.3% 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 2025-09-07T13:05:25.4987225Z triton_convolution2d_556 0.1449 ms 16.1% 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 2025-09-07T13:05:25.4988355Z triton_convolution2d_550 0.1948 ms 11.9% 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 2025-09-07T13:05:25.4989481Z triton_convolution2d_551 0.1974 ms 11.8% 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 2025-09-07T13:05:25.4990751Z triton_convolution2d_552 0.3240 ms 7.2% 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 2025-09-07T13:05:25.4991654Z SingleProcess AUTOTUNE benchmarking takes 0.2254 seconds and 0.0002 seconds precompiling for 8 choices 2025-09-07T13:05:25.8087077Z Autotune Choices Stats: 2025-09-07T13:05:25.8088141Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_736", "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": 0.009824000298976898, "best_triton_pos": 0} 2025-09-07T13:05:25.8446814Z AUTOTUNE addmm(768x255, 768x1024, 1024x255) 2025-09-07T13:05:25.8447152Z strides: [0, 1], [1024, 1], [1, 1024] 2025-09-07T13:05:25.8447508Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:25.8448280Z triton_mm_736 0.0098 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 2025-09-07T13:05:25.8449300Z triton_mm_740 0.0107 ms 92.2% 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 2025-09-07T13:05:25.8450760Z triton_mm_744 0.0125 ms 78.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:25.8451787Z triton_mm_735 0.0125 ms 78.3% 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 2025-09-07T13:05:25.8452760Z triton_mm_734 0.0130 ms 75.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:25.8453710Z triton_mm_739 0.0132 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:25.8454703Z triton_mm_733 0.0132 ms 74.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T13:05:25.8455582Z triton_mm_743 0.0145 ms 67.8% 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 2025-09-07T13:05:25.8456417Z triton_mm_750 0.0155 ms 63.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:25.8457330Z triton_mm_746 0.0157 ms 62.5% 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 2025-09-07T13:05:25.8458144Z SingleProcess AUTOTUNE benchmarking takes 0.3119 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:26.1107891Z Autotune Choices Stats: 2025-09-07T13:05:26.1109470Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_755", "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": 0.008383999578654766, "best_triton_pos": 0} 2025-09-07T13:05:26.1888041Z AUTOTUNE addmm(768x256, 768x512, 512x256) 2025-09-07T13:05:26.1888509Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T13:05:26.1889047Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:26.1890203Z triton_mm_755 0.0084 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 2025-09-07T13:05:26.1892339Z triton_mm_759 0.0086 ms 97.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:26.1893339Z bias_addmm 0.0087 ms 96.3% 2025-09-07T13:05:26.1894310Z triton_mm_763 0.0093 ms 89.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:26.1895846Z triton_mm_754 0.0096 ms 87.3% 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 2025-09-07T13:05:26.1896743Z triton_mm_753 0.0098 ms 85.9% 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 2025-09-07T13:05:26.1897804Z triton_mm_758 0.0098 ms 85.9% 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 2025-09-07T13:05:26.1898705Z triton_mm_752 0.0100 ms 83.7% 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 2025-09-07T13:05:26.1899663Z triton_mm_762 0.0101 ms 82.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:26.1900680Z triton_mm_765 0.0110 ms 76.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:26.1901463Z SingleProcess AUTOTUNE benchmarking takes 0.3436 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:26.4702390Z Autotune Choices Stats: 2025-09-07T13:05:26.4704123Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_860", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4", "best_time": 0.012223999947309494, "best_triton_pos": 0} 2025-09-07T13:05:26.4873665Z AUTOTUNE addmm(3072x255, 3072x512, 512x255) 2025-09-07T13:05:26.4874116Z strides: [0, 1], [512, 1], [1, 512] 2025-09-07T13:05:26.4874687Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:26.4875888Z triton_mm_860 0.0122 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:26.4876882Z triton_mm_855 0.0123 ms 99.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:26.4877988Z triton_mm_859 0.0124 ms 98.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:26.4879040Z triton_mm_858 0.0134 ms 91.4% 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 2025-09-07T13:05:26.4880010Z triton_mm_862 0.0135 ms 90.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:26.4881285Z triton_mm_849 0.0136 ms 90.1% 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 2025-09-07T13:05:26.4882263Z triton_mm_866 0.0137 ms 89.3% 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 2025-09-07T13:05:26.4883236Z triton_mm_856 0.0139 ms 88.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:26.4884198Z triton_mm_851 0.0140 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:26.4885185Z triton_mm_865 0.0148 ms 82.5% 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 2025-09-07T13:05:26.4886032Z SingleProcess AUTOTUNE benchmarking takes 0.2828 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:26.7501782Z Autotune Choices Stats: 2025-09-07T13:05:26.7503509Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_875", "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": 0.008415999822318554, "best_triton_pos": 0} 2025-09-07T13:05:26.8121295Z AUTOTUNE addmm(3072x128, 3072x256, 256x128) 2025-09-07T13:05:26.8121584Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T13:05:26.8121895Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:26.8122603Z triton_mm_875 0.0084 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:05:26.8123689Z triton_mm_874 0.0089 ms 94.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:26.8124313Z bias_addmm 0.0090 ms 93.3% 2025-09-07T13:05:26.8124908Z triton_mm_879 0.0091 ms 92.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:26.8125907Z triton_mm_878 0.0093 ms 90.7% 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 2025-09-07T13:05:26.8126810Z triton_mm_868 0.0093 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T13:05:26.8127704Z triton_mm_870 0.0093 ms 90.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:26.8128590Z triton_mm_869 0.0097 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:05:26.8129542Z triton_mm_877 0.0097 ms 87.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:26.8130710Z triton_mm_881 0.0097 ms 86.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:26.8131587Z SingleProcess AUTOTUNE benchmarking takes 0.3243 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:27.0907296Z Autotune Choices Stats: 2025-09-07T13:05:27.0908322Z {"num_choices": 21, "num_triton_choices": 19, "best_kernel": "triton_mm_975", "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": 0.015072000212967396, "best_triton_pos": 0} 2025-09-07T13:05:27.2443627Z AUTOTUNE addmm(12288x255, 12288x256, 256x255) 2025-09-07T13:05:27.2444070Z strides: [0, 1], [256, 1], [1, 256] 2025-09-07T13:05:27.2444382Z dtypes: torch.bfloat16, torch.bfloat16, torch.bfloat16 2025-09-07T13:05:27.2445157Z triton_mm_975 0.0151 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 2025-09-07T13:05:27.2446891Z triton_mm_973 0.0164 ms 92.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:27.2448453Z triton_mm_981 0.0165 ms 91.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:27.2450035Z triton_mm_977 0.0168 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:27.2454765Z triton_mm_978 0.0168 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:05:27.2456452Z triton_mm_970 0.0175 ms 85.9% 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 2025-09-07T13:05:27.2457431Z triton_mm_971 0.0176 ms 85.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:05:27.2458482Z triton_mm_980 0.0179 ms 84.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:05:27.2459460Z triton_mm_974 0.0184 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 2025-09-07T13:05:27.2460571Z triton_mm_976 0.0203 ms 74.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:05:27.2461428Z SingleProcess AUTOTUNE benchmarking takes 0.4165 seconds and 0.0002 seconds precompiling for 21 choices 2025-09-07T13:05:27.2602086Z cudagraph partition due to non gpu ops 2025-09-07T13:05:27.2602402Z cudagraph partition due to non gpu ops 2025-09-07T13:05:27.2602688Z cudagraph partition due to non gpu ops 2025-09-07T13:05:27.3166707Z cudagraph partition into 2 partitions 2025-09-07T13:05:43.9573862Z pass 2025-09-07T13:05:47.1286259Z accuracy pass_rate=86.67% 2025-09-07T13:05:47.1299868Z calls_captured gmean=0.00x mean=378.067x 2025-09-07T13:05:47.1304078Z unique_graphs gmean=0.00x mean=2.267x 2025-09-07T13:05:47.1307726Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T13:05:47.1310837Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T13:05:47.1314220Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T13:05:47.1317570Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T13:05:47.1321345Z cudagraph_skips gmean=nanx mean=-0.400x 2025-09-07T13:05:47.1322384Z compilation_latency mean=27.084 seconds 2025-09-07T13:05:47.9679276Z + [[ 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* ]] 2025-09-07T13:05:47.9680705Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T13:05:47.9681030Z + [[ accuracy == \a\c\c\u\r\a\c\y ]] 2025-09-07T13:05:47.9682516Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T13:05:48.4642323Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:05:48.4643324Z import pynvml # type: ignore[import] 2025-09-07T13:05:52.0436375Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:05:52.0437477Z import pynvml # type: ignore[import] 2025-09-07T13:05:54.4615025Z 2025-09-07T13:05:56.1195166Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:05:56.1195391Z 2025-09-07T13:05:56.3174063Z Loading pipeline components...: 0% 0/6 [00:00", line 1, in 2025-09-07T13:13:07.0274937Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1593, in wrapped_fn 2025-09-07T13:13:07.0275405Z return tuple(flat_fn(*args)) 2025-09-07T13:13:07.0275899Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/utils.py", line 187, in flat_fn 2025-09-07T13:13:07.0276403Z tree_out = fn(*args, **kwargs) 2025-09-07T13:13:07.0276983Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/graph_capture_wrappers.py", line 1354, in functional_call 2025-09-07T13:13:07.0277545Z out = mod(*args[params_len:], **kwargs) 2025-09-07T13:13:07.0278028Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T13:13:07.0278534Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T13:13:07.0279060Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T13:13:07.0279675Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T13:13:07.0280168Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T13:13:07.0280742Z ret_val = forward(*args, **kwargs) 2025-09-07T13:13:07.0281153Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T13:13:07.0281688Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T13:13:07.0282185Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T13:13:07.0282713Z return self._call_impl(*args, **kwargs) 2025-09-07T13:13:07.0283227Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T13:13:07.0283688Z return forward_call(*args, **kwargs) 2025-09-07T13:13:07.0284120Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1906, in forward 2025-09-07T13:13:07.0284537Z tree_out = mod(*args, **kwargs) 2025-09-07T13:13:07.0284990Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T13:13:07.0285488Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T13:13:07.0286004Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T13:13:07.0286543Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T13:13:07.0287030Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T13:13:07.0287464Z ret_val = forward(*args, **kwargs) 2025-09-07T13:13:07.0287871Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T13:13:07.0288306Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T13:13:07.0288795Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T13:13:07.0289369Z return self._call_impl(*args, **kwargs) 2025-09-07T13:13:07.0289802Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T13:13:07.0290360Z return forward_call(*args, **kwargs) 2025-09-07T13:13:07.0290714Z File "/torchbench/torchbenchmark/models/tts_angular/model.py", line 73, in forward 2025-09-07T13:13:07.0291054Z d = self.layers(x) 2025-09-07T13:13:07.0291471Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T13:13:07.0292031Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T13:13:07.0292531Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T13:13:07.0293042Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T13:13:07.0293502Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T13:13:07.0293923Z ret_val = forward(*args, **kwargs) 2025-09-07T13:13:07.0294322Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T13:13:07.0294772Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T13:13:07.0295253Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T13:13:07.0295718Z return self._call_impl(*args, **kwargs) 2025-09-07T13:13:07.0296155Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T13:13:07.0296595Z return forward_call(*args, **kwargs) 2025-09-07T13:13:07.0297022Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py", line 250, in forward 2025-09-07T13:13:07.0297532Z input = module(input) 2025-09-07T13:13:07.0297955Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T13:13:07.0298438Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T13:13:07.0299006Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T13:13:07.0299530Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T13:13:07.0300000Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T13:13:07.0300565Z ret_val = forward(*args, **kwargs) 2025-09-07T13:13:07.0300973Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T13:13:07.0301410Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T13:13:07.0301884Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T13:13:07.0302344Z return self._call_impl(*args, **kwargs) 2025-09-07T13:13:07.0302849Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T13:13:07.0303285Z return forward_call(*args, **kwargs) 2025-09-07T13:13:07.0303638Z File "/torchbench/torchbenchmark/models/tts_angular/model.py", line 18, in forward 2025-09-07T13:13:07.0303983Z o, (_, _) = self.lstm(x) 2025-09-07T13:13:07.0304410Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T13:13:07.0304895Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T13:13:07.0305408Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T13:13:07.0305937Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T13:13:07.0306507Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T13:13:07.0306948Z ret_val = forward(*args, **kwargs) 2025-09-07T13:13:07.0307359Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T13:13:07.0307799Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T13:13:07.0308275Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T13:13:07.0308735Z return self._call_impl(*args, **kwargs) 2025-09-07T13:13:07.0309243Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T13:13:07.0309684Z return forward_call(*args, **kwargs) 2025-09-07T13:13:07.0310086Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 1046, in forward 2025-09-07T13:13:07.0310611Z self._update_flat_weights() 2025-09-07T13:13:07.0311052Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 393, in _update_flat_weights 2025-09-07T13:13:07.0311493Z self._init_flat_weights() 2025-09-07T13:13:07.0311906Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 215, in _init_flat_weights 2025-09-07T13:13:07.0312340Z self.flatten_parameters() 2025-09-07T13:13:07.0312741Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 255, in flatten_parameters 2025-09-07T13:13:07.0313172Z unique_data_ptrs = { 2025-09-07T13:13:07.0313546Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 256, in 2025-09-07T13:13:07.0313972Z p.data_ptr() # type: ignore[union-attr] 2025-09-07T13:13:07.0314486Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1409, in __torch_function__ 2025-09-07T13:13:07.0315074Z return func(*args, **kwargs) 2025-09-07T13:13:07.0315542Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1479, in __torch_function__ 2025-09-07T13:13:07.0316026Z return func(*args, **kwargs) 2025-09-07T13:13:07.0316544Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/non_strict_utils.py", line 1066, in __torch_function__ 2025-09-07T13:13:07.0317007Z return func(*args, **kwargs) 2025-09-07T13:13:07.0318100Z RuntimeError: Cannot access data pointer of Tensor (e.g. FakeTensor, FunctionalTensor). If you're using torch.compile/export/fx, it is likely that we are erroneously tracing into a custom kernel. To fix this, please wrap the custom kernel into an opaque custom op. Please see the following for details: https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-09-07T13:13:07.0319327Z TorchDynamo optimized model failed to run because of following error 2025-09-07T13:13:07.0458405Z fail_to_run 2025-09-07T13:13:08.6041615Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:13:08.6043196Z import pynvml # type: ignore[import] 2025-09-07T13:13:11.0398620Z 2025-09-07T13:13:13.1195855Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:13:13.1196195Z loading model: 0it [00:02, ?it/s] 2025-09-07T13:13:13.1204322Z cuda eval vgg16 2025-09-07T13:13:26.1235574Z pass 2025-09-07T13:13:28.9051645Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:13:28.9053266Z import pynvml # type: ignore[import] 2025-09-07T13:13:31.3390715Z 2025-09-07T13:13:33.0884554Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:13:33.0885137Z loading model: 0it [00:01, ?it/s] 2025-09-07T13:13:33.0975375Z cuda eval yolov3 2025-09-07T13:13:56.4325984Z pass 2025-09-07T13:13:59.3304534Z accuracy pass_rate=76.92% 2025-09-07T13:13:59.3309435Z calls_captured gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3312630Z unique_graphs gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3315606Z graph_breaks gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3318782Z unique_graph_breaks gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3323338Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3325841Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3328951Z cudagraph_skips gmean=0.00x mean=0.000x 2025-09-07T13:13:59.3330051Z compilation_latency mean=0.000 seconds 2025-09-07T13:14:00.1526661Z + [[ 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* ]] 2025-09-07T13:14:00.1528675Z + TORCHINDUCTOR_MAX_AUTOTUNE=1 2025-09-07T13:14:00.1531284Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv 2025-09-07T13:14:00.6502354Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:14:00.6503695Z import pynvml # type: ignore[import] 2025-09-07T13:14:04.1913888Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:14:04.1915012Z import pynvml # type: ignore[import] 2025-09-07T13:14:06.6232533Z 2025-09-07T13:14:08.4173153Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:14:08.4173527Z 2025-09-07T13:14:08.6128119Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T13:21:30.8213959Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8214258Z 2025-09-07T13:21:30.8214396Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:21:30.8214927Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:21:30.8215433Z anchors = self.anchor_generator(images, features) 2025-09-07T13:21:30.8215968Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:21:30.8216504Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:21:30.8217081Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:21:30.8217745Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8218386Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:21:30.8219140Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8219428Z 2025-09-07T13:21:30.8219559Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:21:30.8220086Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:21:30.8220753Z anchors = self.anchor_generator(images, features) 2025-09-07T13:21:30.8221415Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:21:30.8221968Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:21:30.8222510Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:21:30.8223155Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8223771Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:21:30.8224372Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8224639Z 2025-09-07T13:21:30.8224790Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:21:30.8225283Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:21:30.8225753Z anchors = self.anchor_generator(images, features) 2025-09-07T13:21:30.8226252Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:21:30.8226756Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:21:30.8227284Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:21:30.8227900Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8228573Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:21:30.8229161Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8229446Z 2025-09-07T13:21:30.8229572Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:21:30.8230063Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:21:30.8230664Z anchors = self.anchor_generator(images, features) 2025-09-07T13:21:30.8231245Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:21:30.8231775Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:21:30.8232313Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:21:30.8233042Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8233643Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:21:30.8234239Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:21:30.8234518Z 2025-09-07T13:21:30.8372984Z cudagraph partition into 2 partitions 2025-09-07T13:21:33.1267124Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T13:21:33.1268155Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T13:21:33.1268941Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] or: 2025-09-07T13:21:33.1270152Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T13:21:33.1271423Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] to include these operations in the captured graph. 2025-09-07T13:21:33.1272321Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:21:33.1273009Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break: from user code at: 2025-09-07T13:21:33.1274091Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T13:21:33.1275331Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T13:21:33.1276416Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T13:21:33.1277422Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T13:21:33.1278375Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T13:21:33.1279277Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T13:21:33.1280179Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T13:21:33.1281471Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:21:33.1282454Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T13:21:33.1283519Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:21:33.1284468Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T13:21:33.1285387Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T13:21:33.1286017Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:21:33.1286464Z W0907 13:21:33.126000 657227 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:21:43.9019981Z pass 2025-09-07T13:21:47.8432627Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:21:47.8433713Z import pynvml # type: ignore[import] 2025-09-07T13:21:50.2868961Z 2025-09-07T13:21:52.0616074Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:21:52.0616422Z loading model: 0it [00:01, ?it/s] 2025-09-07T13:21:52.0703185Z cuda eval yolov3 2025-09-07T13:22:09.2979511Z Autotune Choices Stats: 2025-09-07T13:22:09.2981780Z {"num_choices": 18, "num_triton_choices": 17, "best_kernel": "triton_mm_28", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.01961600035429001, "best_triton_pos": 0} 2025-09-07T13:22:09.3179368Z AUTOTUNE mm(196608x64, 64x32) 2025-09-07T13:22:09.3179830Z strides: [64, 1], [1, 64] 2025-09-07T13:22:09.3180558Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:09.3181692Z triton_mm_28 0.0196 ms 100.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:09.3183093Z triton_mm_20 0.0198 ms 99.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:22:09.3183948Z triton_mm_23 0.0207 ms 94.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:09.3184799Z triton_mm_24 0.0208 ms 94.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:09.3185631Z triton_mm_14 0.0209 ms 93.7% 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 2025-09-07T13:22:09.3186482Z triton_mm_17 0.0210 ms 93.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:22:09.3187332Z triton_mm_22 0.0216 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=4, num_warps=8 2025-09-07T13:22:09.3188178Z triton_mm_26 0.0216 ms 90.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:09.3189190Z triton_mm_29 0.0218 ms 90.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:09.3190048Z triton_mm_16 0.0223 ms 87.8% 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 2025-09-07T13:22:09.3191047Z SingleProcess AUTOTUNE benchmarking takes 0.2533 seconds and 0.0006 seconds precompiling for 18 choices 2025-09-07T13:22:09.8541257Z Autotune Choices Stats: 2025-09-07T13:22:09.8542305Z {"num_choices": 19, "num_triton_choices": 18, "best_kernel": "triton_mm_55", "best_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4", "best_time": 0.013248000293970108, "best_triton_pos": 0} 2025-09-07T13:22:09.8726777Z AUTOTUNE mm(49152x128, 128x64) 2025-09-07T13:22:09.8727039Z strides: [128, 1], [1, 128] 2025-09-07T13:22:09.8727290Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:09.8727943Z triton_mm_55 0.0132 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 2025-09-07T13:22:09.8728922Z triton_mm_60 0.0133 ms 99.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:09.8729896Z triton_mm_51 0.0136 ms 97.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:22:09.8731367Z triton_mm_50 0.0140 ms 95.0% 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 2025-09-07T13:22:09.8731979Z mm 0.0140 ms 94.5% 2025-09-07T13:22:09.8732538Z triton_mm_57 0.0143 ms 92.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:09.8733679Z triton_mm_52 0.0143 ms 92.6% 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 2025-09-07T13:22:09.8734638Z triton_mm_56 0.0143 ms 92.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:09.8735593Z triton_mm_58 0.0143 ms 92.4% 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 2025-09-07T13:22:09.8736545Z triton_mm_59 0.0144 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=8 2025-09-07T13:22:09.8737398Z SingleProcess AUTOTUNE benchmarking takes 0.2518 seconds and 0.0002 seconds precompiling for 19 choices 2025-09-07T13:22:10.4315365Z Autotune Choices Stats: 2025-09-07T13:22:10.4316464Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_112", "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": 0.01104000024497509, "best_triton_pos": 0} 2025-09-07T13:22:10.4501125Z AUTOTUNE mm(12288x256, 256x128) 2025-09-07T13:22:10.4501384Z strides: [256, 1], [1, 256] 2025-09-07T13:22:10.4501649Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:10.4502496Z triton_mm_112 0.0110 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 2025-09-07T13:22:10.4503899Z mm 0.0111 ms 99.4% 2025-09-07T13:22:10.4504755Z triton_mm_108 0.0111 ms 99.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:22:10.4506232Z triton_mm_119 0.0112 ms 98.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:10.4507919Z triton_mm_115 0.0116 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:10.4509374Z triton_mm_111 0.0116 ms 95.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:10.4511380Z triton_mm_114 0.0117 ms 94.5% 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 2025-09-07T13:22:10.4512857Z triton_mm_118 0.0120 ms 92.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:10.4513770Z triton_mm_110 0.0126 ms 87.6% 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 2025-09-07T13:22:10.4514612Z triton_mm_117 0.0128 ms 86.0% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:10.4515348Z SingleProcess AUTOTUNE benchmarking takes 0.2765 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T13:22:11.1709958Z Autotune Choices Stats: 2025-09-07T13:22:11.1712368Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.012000000104308128, "best_triton_pos": 1, "best_triton_time": 0.01228800043463707, "best_triton_kernel": "triton_mm_897", "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"} 2025-09-07T13:22:11.1892799Z AUTOTUNE mm(12288x384, 384x128) 2025-09-07T13:22:11.1893299Z strides: [384, 1], [1, 384] 2025-09-07T13:22:11.1893811Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:11.1894256Z mm 0.0120 ms 100.0% 2025-09-07T13:22:11.1895230Z triton_mm_897 0.0123 ms 97.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:11.1896806Z triton_mm_893 0.0123 ms 97.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:22:11.1898385Z triton_mm_904 0.0125 ms 95.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:11.1899959Z triton_mm_903 0.0130 ms 92.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:11.1901809Z triton_mm_900 0.0133 ms 89.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:11.1903349Z triton_mm_896 0.0134 ms 89.3% 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 2025-09-07T13:22:11.1904203Z triton_mm_899 0.0140 ms 86.0% 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 2025-09-07T13:22:11.1905189Z triton_mm_895 0.0140 ms 85.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:11.1906029Z triton_mm_898 0.0143 ms 83.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:11.1906766Z SingleProcess AUTOTUNE benchmarking takes 0.2633 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:22:11.5325828Z Autotune Choices Stats: 2025-09-07T13:22:11.5327443Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.010208000428974628, "best_triton_pos": 1, "best_triton_time": 0.010432000271975994, "best_triton_kernel": "triton_mm_328", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T13:22:11.5516817Z AUTOTUNE mm(3072x512, 512x256) 2025-09-07T13:22:11.5517091Z strides: [512, 1], [1, 512] 2025-09-07T13:22:11.5517372Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:11.5517650Z mm 0.0102 ms 100.0% 2025-09-07T13:22:11.5518275Z triton_mm_328 0.0104 ms 97.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:11.5519282Z triton_mm_327 0.0110 ms 92.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:11.5520673Z triton_mm_334 0.0111 ms 91.7% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:11.5521896Z triton_mm_323 0.0116 ms 88.4% 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 2025-09-07T13:22:11.5523082Z triton_mm_333 0.0116 ms 87.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:11.5524228Z triton_mm_330 0.0117 ms 86.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:11.5525197Z triton_mm_326 0.0119 ms 85.5% 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 2025-09-07T13:22:11.5526168Z triton_mm_324 0.0124 ms 82.2% 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 2025-09-07T13:22:11.5527137Z triton_mm_317 0.0130 ms 78.8% 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 2025-09-07T13:22:11.5527992Z SingleProcess AUTOTUNE benchmarking takes 0.2699 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:22:12.2547485Z Autotune Choices Stats: 2025-09-07T13:22:12.2548822Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.011168000288307667, "best_triton_pos": 1, "best_triton_time": 0.011231999844312668, "best_triton_kernel": "triton_mm_782", "best_triton_kernel_desc": "ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4"} 2025-09-07T13:22:12.2733688Z AUTOTUNE mm(3072x768, 768x256) 2025-09-07T13:22:12.2733984Z strides: [768, 1], [1, 768] 2025-09-07T13:22:12.2734245Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:12.2734541Z mm 0.0112 ms 100.0% 2025-09-07T13:22:12.2735181Z triton_mm_782 0.0112 ms 99.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:12.2736516Z triton_mm_777 0.0124 ms 89.9% 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 2025-09-07T13:22:12.2737490Z triton_mm_788 0.0125 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:12.2738581Z triton_mm_781 0.0128 ms 87.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:12.2739569Z triton_mm_778 0.0135 ms 82.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:22:12.2740918Z triton_mm_787 0.0138 ms 81.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:12.2741893Z triton_mm_784 0.0138 ms 80.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=128, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:12.2742908Z triton_mm_780 0.0139 ms 80.4% 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 2025-09-07T13:22:12.2743752Z triton_mm_771 0.0151 ms 74.1% 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 2025-09-07T13:22:12.2744487Z SingleProcess AUTOTUNE benchmarking takes 0.2542 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:22:12.6004194Z Autotune Choices Stats: 2025-09-07T13:22:12.6005623Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.009503999724984169, "best_triton_pos": 1, "best_triton_time": 0.009568000212311745, "best_triton_kernel": "triton_mm_539", "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"} 2025-09-07T13:22:12.6189715Z AUTOTUNE mm(768x1024, 1024x512) 2025-09-07T13:22:12.6189990Z strides: [1024, 1], [1, 1024] 2025-09-07T13:22:12.6190467Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:12.6190751Z mm 0.0095 ms 100.0% 2025-09-07T13:22:12.6191372Z triton_mm_539 0.0096 ms 99.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:22:12.6192376Z triton_mm_543 0.0108 ms 88.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:12.6193381Z triton_mm_535 0.0122 ms 78.0% 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 2025-09-07T13:22:12.6194305Z triton_mm_538 0.0122 ms 77.7% 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 2025-09-07T13:22:12.6195157Z triton_mm_542 0.0126 ms 75.2% 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 2025-09-07T13:22:12.6195998Z triton_mm_549 0.0128 ms 74.2% 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 2025-09-07T13:22:12.6196843Z triton_mm_548 0.0140 ms 67.8% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:12.6197818Z triton_mm_541 0.0141 ms 67.3% 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 2025-09-07T13:22:12.6198650Z triton_mm_532 0.0141 ms 67.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=32, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=2, num_warps=4 2025-09-07T13:22:12.6199385Z SingleProcess AUTOTUNE benchmarking takes 0.2567 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:22:13.2513206Z Autotune Choices Stats: 2025-09-07T13:22:13.2514879Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "mm", "best_time": 0.01119999960064888, "best_triton_pos": 1, "best_triton_time": 0.012671999633312225, "best_triton_kernel": "triton_mm_688", "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"} 2025-09-07T13:22:13.2699067Z AUTOTUNE mm(768x2048, 2048x512) 2025-09-07T13:22:13.2699346Z strides: [2048, 1], [1, 2048] 2025-09-07T13:22:13.2699626Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:13.2699899Z mm 0.0112 ms 100.0% 2025-09-07T13:22:13.2700987Z triton_mm_688 0.0127 ms 88.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:22:13.2702007Z triton_mm_692 0.0140 ms 79.9% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:13.2703032Z triton_mm_684 0.0166 ms 67.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:22:13.2704071Z triton_mm_698 0.0179 ms 62.5% 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 2025-09-07T13:22:13.2704920Z triton_mm_687 0.0194 ms 57.7% 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 2025-09-07T13:22:13.2705881Z triton_mm_691 0.0197 ms 56.8% 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 2025-09-07T13:22:13.2706729Z triton_mm_681 0.0209 ms 53.5% 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 2025-09-07T13:22:13.2707583Z triton_mm_697 0.0218 ms 51.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=128, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:13.2708438Z triton_mm_683 0.0219 ms 51.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:13.2709174Z SingleProcess AUTOTUNE benchmarking takes 0.2716 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:22:13.5749050Z Autotune Choices Stats: 2025-09-07T13:22:13.5750102Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_875", "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": 0.008063999935984612, "best_triton_pos": 0} 2025-09-07T13:22:13.5940630Z AUTOTUNE mm(3072x256, 256x128) 2025-09-07T13:22:13.5940897Z strides: [256, 1], [1, 256] 2025-09-07T13:22:13.5941164Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:13.5941851Z triton_mm_875 0.0081 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 2025-09-07T13:22:13.5943125Z triton_mm_874 0.0083 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=8 2025-09-07T13:22:13.5943770Z mm 0.0084 ms 96.6% 2025-09-07T13:22:13.5944351Z triton_mm_878 0.0088 ms 92.0% 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 2025-09-07T13:22:13.5945461Z triton_mm_870 0.0088 ms 91.3% 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 2025-09-07T13:22:13.5946436Z triton_mm_868 0.0089 ms 91.0% 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 2025-09-07T13:22:13.5947407Z triton_mm_877 0.0089 ms 90.6% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:13.5948381Z triton_mm_879 0.0089 ms 90.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:13.5949352Z triton_mm_869 0.0090 ms 89.4% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=32, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:13.5950507Z triton_mm_881 0.0091 ms 89.0% 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 2025-09-07T13:22:13.5951369Z SingleProcess AUTOTUNE benchmarking takes 0.2625 seconds and 0.0002 seconds precompiling for 20 choices 2025-09-07T13:22:14.1014290Z Autotune Choices Stats: 2025-09-07T13:22:14.1015330Z {"num_choices": 20, "num_triton_choices": 19, "best_kernel": "triton_mm_755", "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": 0.007872000336647034, "best_triton_pos": 0} 2025-09-07T13:22:14.1203012Z AUTOTUNE mm(768x512, 512x256) 2025-09-07T13:22:14.1203323Z strides: [512, 1], [1, 512] 2025-09-07T13:22:14.1203887Z dtypes: torch.bfloat16, torch.bfloat16 2025-09-07T13:22:14.1204547Z triton_mm_755 0.0079 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 2025-09-07T13:22:14.1205184Z mm 0.0083 ms 95.3% 2025-09-07T13:22:14.1205760Z triton_mm_759 0.0083 ms 95.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=4 2025-09-07T13:22:14.1206742Z triton_mm_763 0.0088 ms 89.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=128, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=4 2025-09-07T13:22:14.1207707Z triton_mm_754 0.0090 ms 87.2% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=32, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=5, num_warps=8 2025-09-07T13:22:14.1208660Z triton_mm_758 0.0091 ms 86.3% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=64, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=8 2025-09-07T13:22:14.1209603Z triton_mm_753 0.0093 ms 84.5% 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 2025-09-07T13:22:14.1210909Z triton_mm_752 0.0096 ms 81.7% 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 2025-09-07T13:22:14.1211875Z triton_mm_762 0.0097 ms 81.5% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=64, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=3, num_warps=4 2025-09-07T13:22:14.1212979Z triton_mm_761 0.0102 ms 77.1% ACC_TYPE='tl.float32', ALLOW_TF32=False, BLOCK_K=32, BLOCK_M=64, BLOCK_N=128, EVEN_K=True, GROUP_M=8, USE_FAST_ACCUM=False, num_stages=4, num_warps=8 2025-09-07T13:22:14.1213834Z SingleProcess AUTOTUNE benchmarking takes 0.2652 seconds and 0.0003 seconds precompiling for 20 choices 2025-09-07T13:22:15.1266819Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:22:15.1267441Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T13:22:15.1268266Z return mod(*inputs) 2025-09-07T13:22:15.1268693Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T13:22:15.1269164Z return self.forward_once(x) 2025-09-07T13:22:15.1269623Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T13:22:15.1270099Z yolo_out.append(module(x, out)) 2025-09-07T13:22:15.1270912Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T13:22:15.1271403Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T13:22:15.1271903Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T13:22:15.1272415Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T13:22:15.1272633Z 2025-09-07T13:22:15.1272781Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:22:15.1273326Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T13:22:15.1273954Z return mod(*inputs) 2025-09-07T13:22:15.1274299Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T13:22:15.1274664Z return self.forward_once(x) 2025-09-07T13:22:15.1275170Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T13:22:15.1275556Z yolo_out.append(module(x, out)) 2025-09-07T13:22:15.1275908Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T13:22:15.1276299Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T13:22:15.1276806Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T13:22:15.1277219Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T13:22:15.1277402Z 2025-09-07T13:22:15.1277517Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:22:15.1277962Z File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass 2025-09-07T13:22:15.1278348Z return mod(*inputs) 2025-09-07T13:22:15.1278672Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 309, in forward 2025-09-07T13:22:15.1279038Z return self.forward_once(x) 2025-09-07T13:22:15.1279398Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 372, in forward_once 2025-09-07T13:22:15.1279781Z yolo_out.append(module(x, out)) 2025-09-07T13:22:15.1280137Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 246, in forward 2025-09-07T13:22:15.1280657Z self.grid = self.create_grids((nx, ny), p.device) 2025-09-07T13:22:15.1281051Z File "/torchbench/torchbenchmark/models/yolov3/yolo_models.py", line 199, in create_grids 2025-09-07T13:22:15.1281453Z self.ng = torch.tensor(ng, dtype=torch.float) 2025-09-07T13:22:15.1281625Z 2025-09-07T13:22:15.2190377Z cudagraph partition into 2 partitions 2025-09-07T13:22:27.3577859Z pass 2025-09-07T13:22:30.4139985Z accuracy pass_rate=86.67% 2025-09-07T13:22:30.4152208Z calls_captured gmean=0.00x mean=378.067x 2025-09-07T13:22:30.4155688Z unique_graphs gmean=0.00x mean=2.267x 2025-09-07T13:22:30.4159066Z graph_breaks gmean=0.00x mean=1.600x 2025-09-07T13:22:30.4163287Z unique_graph_breaks gmean=0.00x mean=0.333x 2025-09-07T13:22:30.4166611Z autograd_captures gmean=0.00x mean=0.000x 2025-09-07T13:22:30.4169897Z autograd_compiles gmean=0.00x mean=0.000x 2025-09-07T13:22:30.4173545Z cudagraph_skips gmean=nanx mean=-0.400x 2025-09-07T13:22:30.4175120Z compilation_latency mean=22.106 seconds 2025-09-07T13:22:31.2391721Z + [[ 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* ]] 2025-09-07T13:22:31.2393815Z + [[ inference == \i\n\f\e\r\e\n\c\e ]] 2025-09-07T13:22:31.2396515Z + python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --quant --backend inductor --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv 2025-09-07T13:22:31.7288976Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:22:31.7290034Z import pynvml # type: ignore[import] 2025-09-07T13:22:34.1061327Z usage: torchbench.py 2025-09-07T13:22:34.1061737Z [-h] 2025-09-07T13:22:34.1062069Z [--filter FILTER] 2025-09-07T13:22:34.1062447Z [--exclude EXCLUDE] 2025-09-07T13:22:34.1062843Z [--exclude-exact EXCLUDE_EXACT] 2025-09-07T13:22:34.1063398Z [--total-partitions {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}] 2025-09-07T13:22:34.1063974Z [--partition-id PARTITION_ID] 2025-09-07T13:22:34.1064449Z [--devices DEVICES] 2025-09-07T13:22:34.1064827Z [--device-index DEVICE_INDEX] 2025-09-07T13:22:34.1065533Z [--repeat REPEAT] 2025-09-07T13:22:34.1065974Z [--iterations-per-run ITERATIONS_PER_RUN] 2025-09-07T13:22:34.1066479Z [--randomize-input] 2025-09-07T13:22:34.1066876Z [--threads THREADS] 2025-09-07T13:22:34.1067229Z [--nopython] 2025-09-07T13:22:34.1067533Z [--no-skip] 2025-09-07T13:22:34.1067860Z [--prims-nvfuser] 2025-09-07T13:22:34.1068226Z [--dump-raw-metrics] 2025-09-07T13:22:34.1068660Z [--log-operator-inputs] 2025-09-07T13:22:34.1069306Z [--channels-last] 2025-09-07T13:22:34.1069693Z [--batch-size BATCH_SIZE] 2025-09-07T13:22:34.1070025Z [--iterations ITERATIONS] 2025-09-07T13:22:34.1070479Z [--batch-size-file BATCH_SIZE_FILE] 2025-09-07T13:22:34.1070717Z [--cosine] 2025-09-07T13:22:34.1070878Z [--freezing] 2025-09-07T13:22:34.1071065Z [--inductor-config INDUCTOR_CONFIG] 2025-09-07T13:22:34.1071291Z [--ci] 2025-09-07T13:22:34.1071446Z [--dashboard] 2025-09-07T13:22:34.1071625Z [--skip-fp64-check] 2025-09-07T13:22:34.1071812Z [--fast] 2025-09-07T13:22:34.1071975Z [--only ONLY] 2025-09-07T13:22:34.1072149Z [--multiprocess] 2025-09-07T13:22:34.1072322Z [--ddp] 2025-09-07T13:22:34.1072481Z [--fsdp] 2025-09-07T13:22:34.1072669Z [--optimize-ddp-mode OPTIMIZE_DDP_MODE] 2025-09-07T13:22:34.1072973Z [--distributed-master-port DISTRIBUTED_MASTER_PORT] 2025-09-07T13:22:34.1073257Z [--dynamic-shapes] 2025-09-07T13:22:34.1073467Z [--propagate-real-tensors] 2025-09-07T13:22:34.1073692Z [--dynamic-batch-only] 2025-09-07T13:22:34.1073901Z [--specialize-int] 2025-09-07T13:22:34.1074089Z [--use-eval-mode] 2025-09-07T13:22:34.1074287Z [--skip-accuracy-check] 2025-09-07T13:22:34.1074580Z [--generate-aot-autograd-stats] 2025-09-07T13:22:34.1074819Z [--inductor-settings] 2025-09-07T13:22:34.1075018Z [--suppress-errors] 2025-09-07T13:22:34.1075214Z [--output OUTPUT] 2025-09-07T13:22:34.1075425Z [--output-directory OUTPUT_DIRECTORY] 2025-09-07T13:22:34.1075661Z [--disable-output] 2025-09-07T13:22:34.1075989Z [--baseline BASELINE] 2025-09-07T13:22:34.1076185Z [--part PART] 2025-09-07T13:22:34.1076376Z [--export-profiler-trace] 2025-09-07T13:22:34.1076623Z [--profiler-trace-name PROFILER_TRACE_NAME] 2025-09-07T13:22:34.1076873Z [--profile-details] 2025-09-07T13:22:34.1077075Z [--export-perfdoctor] 2025-09-07T13:22:34.1077288Z [--diff-branch DIFF_BRANCH] 2025-09-07T13:22:34.1077500Z [--tag TAG] 2025-09-07T13:22:34.1077659Z [--explain] 2025-09-07T13:22:34.1077823Z [--stats] 2025-09-07T13:22:34.1078006Z [--use-warm-peak-memory] 2025-09-07T13:22:34.1078311Z [--print-memory] 2025-09-07T13:22:34.1078508Z [--print-compilation-time] 2025-09-07T13:22:34.1078748Z [--print-dataframe-summary] 2025-09-07T13:22:34.1078975Z [--disable-cudagraphs] 2025-09-07T13:22:34.1079193Z [--disable-split-reductions] 2025-09-07T13:22:34.1079433Z [--disable-persistent-reductions] 2025-09-07T13:22:34.1079681Z [--disable-divisible-by-16] 2025-09-07T13:22:34.1079934Z [--inductor-compile-mode INDUCTOR_COMPILE_MODE] 2025-09-07T13:22:34.1080200Z [--print-graph-breaks] 2025-09-07T13:22:34.1080542Z [--log-graph-breaks] 2025-09-07T13:22:34.1080730Z [--trace-on-xla] 2025-09-07T13:22:34.1080916Z [--xla-tolerance XLA_TOLERANCE] 2025-09-07T13:22:34.1081128Z [--collect-outputs] 2025-09-07T13:22:34.1081328Z [--enable-activation-checkpointing] 2025-09-07T13:22:34.1081545Z [--timing] 2025-09-07T13:22:34.1081702Z [--progress] 2025-09-07T13:22:34.1081860Z [--timeout TIMEOUT] 2025-09-07T13:22:34.1082101Z [--per_process_memory_fraction PER_PROCESS_MEMORY_FRACTION] 2025-09-07T13:22:34.1082382Z [--no-translation-validation] 2025-09-07T13:22:34.1082586Z [--minify] 2025-09-07T13:22:34.1082753Z [--compiled-autograd] 2025-09-07T13:22:34.1083043Z [--profile_dynamo_cache_lookup] 2025-09-07T13:22:34.1083255Z [--snapshot-memory] 2025-09-07T13:22:34.1083440Z [--retain-output] 2025-09-07T13:22:34.1083620Z [--caching-precompile] 2025-09-07T13:22:34.1083849Z [--cold-start-latency | --warm-start-latency] 2025-09-07T13:22:34.1084084Z [--nnc] 2025-09-07T13:22:34.1084266Z [--float16 | --bfloat16 | --float32 | --amp] 2025-09-07T13:22:34.1084594Z [--amp-dtype {bfloat16,float16}] 2025-09-07T13:22:34.1084813Z [--verbose | --quiet] 2025-09-07T13:22:34.1087173Z [--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] 2025-09-07T13:22:34.1089568Z (--accuracy | --performance | --tolerance) 2025-09-07T13:22:34.1089814Z (--training | --inference) 2025-09-07T13:22:34.1090109Z torchbench.py: error: argument --quantization: expected one argument 2025-09-07T13:22:34.7042259Z + true 2025-09-07T13:22:34.7043344Z + cp /var/lib/jenkins/workspace/test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv /var/lib/jenkins/workspace/test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv 2025-09-07T13:22:34.7067199Z + for target in "${targets[@]}" 2025-09-07T13:22:34.7067444Z + target_flag=('--performance') 2025-09-07T13:22:34.7067661Z + local target_flag 2025-09-07T13:22:34.7068074Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]] 2025-09-07T13:22:34.7068343Z + target_flag+=(--cold-start-latency) 2025-09-07T13:22:34.7069340Z + [[ 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* ]] 2025-09-07T13:22:34.7071527Z + [[ 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* ]] 2025-09-07T13:22:34.7073446Z + python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cuda --total-partitions 9 --partition-id 8 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv 2025-09-07T13:22:35.1932810Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:22:35.1933843Z import pynvml # type: ignore[import] 2025-09-07T13:22:38.7146158Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T13:22:38.7147305Z import pynvml # type: ignore[import] 2025-09-07T13:22:41.1593871Z 2025-09-07T13:22:42.8397984Z loading model: 0it [00:00, ?it/s] 2025-09-07T13:22:42.8399000Z 2025-09-07T13:22:42.9510988Z Loading pipeline components...: 0% 0/6 [00:00 2025-09-07T13:28:53.3034974Z W0907 13:28:53.301000 680635 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:28:53.3036036Z W0907 13:28:53.301000 680635 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T13:28:53.3036950Z W0907 13:28:53.301000 680635 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T13:28:53.3037570Z W0907 13:28:53.301000 680635 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:28:53.3038028Z W0907 13:28:53.301000 680635 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:29:07.6942586Z 2025-09-07T13:29:07.7978185Z running benchmark: 0% 0/30 [00:00 2025-09-07T13:36:01.7181662Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7181958Z 2025-09-07T13:36:01.7182102Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:36:01.7182630Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:36:01.7183149Z anchors = self.anchor_generator(images, features) 2025-09-07T13:36:01.7183687Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:36:01.7184375Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:36:01.7184954Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:36:01.7185636Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7186431Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:36:01.7187078Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7187368Z 2025-09-07T13:36:01.7187506Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:36:01.7188037Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:36:01.7188542Z anchors = self.anchor_generator(images, features) 2025-09-07T13:36:01.7189091Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:36:01.7189644Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:36:01.7190335Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:36:01.7190990Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7191598Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:36:01.7192204Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7192483Z 2025-09-07T13:36:01.7192610Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:36:01.7193107Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:36:01.7193591Z anchors = self.anchor_generator(images, features) 2025-09-07T13:36:01.7194186Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:36:01.7194803Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:36:01.7195333Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:36:01.7195955Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7196555Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:36:01.7197217Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7197494Z 2025-09-07T13:36:01.7197618Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:36:01.7198123Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:36:01.7198601Z anchors = self.anchor_generator(images, features) 2025-09-07T13:36:01.7199098Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:36:01.7199596Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:36:01.7200131Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:36:01.7200876Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7201477Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:36:01.7202088Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:36:01.7202439Z 2025-09-07T13:36:01.7361944Z cudagraph partition into 2 partitions 2025-09-07T13:36:04.3845409Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T13:36:04.3846384Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T13:36:04.3847408Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] or: 2025-09-07T13:36:04.3848131Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T13:36:04.3849019Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] to include these operations in the captured graph. 2025-09-07T13:36:04.3849745Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:36:04.3850574Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break: from user code at: 2025-09-07T13:36:04.3851840Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T13:36:04.3853136Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T13:36:04.3854292Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T13:36:04.3855348Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T13:36:04.3856338Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T13:36:04.3857432Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T13:36:04.3858398Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T13:36:04.3859532Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:36:04.3860678Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T13:36:04.3861667Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:36:04.3862634Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T13:36:04.3863551Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T13:36:04.3864169Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:36:04.3864624Z W0907 13:36:04.383000 700436 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:36:04.6278084Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:36:04.6279599Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T13:36:04.6281529Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T13:36:04.6281909Z 2025-09-07T13:36:08.0615892Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:36:08.0617576Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T13:36:08.0618833Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T13:36:08.0619318Z 2025-09-07T13:36:14.5409829Z 2025-09-07T13:36:14.6577259Z running benchmark: 0% 0/30 [00:00 2025-09-07T13:43:21.7942356Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7942714Z 2025-09-07T13:43:21.7942880Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:43:21.7943509Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:43:21.7944292Z anchors = self.anchor_generator(images, features) 2025-09-07T13:43:21.7944940Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:43:21.7945593Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:43:21.7946288Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:43:21.7946956Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7947602Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:43:21.7948246Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7948539Z 2025-09-07T13:43:21.7948671Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:43:21.7949197Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:43:21.7949713Z anchors = self.anchor_generator(images, features) 2025-09-07T13:43:21.7950526Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:43:21.7951092Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:43:21.7951659Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:43:21.7952484Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7953141Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:43:21.7953810Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7954102Z 2025-09-07T13:43:21.7954240Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:43:21.7954855Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:43:21.7955373Z anchors = self.anchor_generator(images, features) 2025-09-07T13:43:21.7955918Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:43:21.7956450Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:43:21.7956983Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:43:21.7957601Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7958210Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:43:21.7958814Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7959083Z 2025-09-07T13:43:21.7959230Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T13:43:21.7959723Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T13:43:21.7960417Z anchors = self.anchor_generator(images, features) 2025-09-07T13:43:21.7960929Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T13:43:21.7961441Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T13:43:21.7961974Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T13:43:21.7962591Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7963259Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T13:43:21.7963860Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T13:43:21.7964145Z 2025-09-07T13:43:21.8124326Z cudagraph partition into 2 partitions 2025-09-07T13:43:24.4788703Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T13:43:24.4789747Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T13:43:24.4790735Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] or: 2025-09-07T13:43:24.4791465Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T13:43:24.4792347Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] to include these operations in the captured graph. 2025-09-07T13:43:24.4793080Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:43:24.4794234Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break: from user code at: 2025-09-07T13:43:24.4795640Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T13:43:24.4797365Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T13:43:24.4798508Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T13:43:24.4799559Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T13:43:24.4800707Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T13:43:24.4801662Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T13:43:24.4802621Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T13:43:24.4803643Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:43:24.4804669Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T13:43:24.4805815Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:43:24.4806837Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T13:43:24.4807807Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T13:43:24.4808542Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:43:24.4809007Z W0907 13:43:24.477000 720438 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:43:24.7254020Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:43:24.7254807Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T13:43:24.7255600Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T13:43:24.7255910Z 2025-09-07T13:43:26.9729501Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T13:43:26.9730568Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T13:43:26.9731358Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T13:43:26.9731671Z 2025-09-07T13:43:33.4439641Z 2025-09-07T13:43:33.5581690Z running benchmark: 0% 0/30 [00:00 2025-09-07T13:53:19.5793971Z W0907 13:53:19.576000 743197 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T13:53:19.5795071Z W0907 13:53:19.576000 743197 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T13:53:19.5796195Z W0907 13:53:19.576000 743197 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T13:53:19.5796860Z W0907 13:53:19.576000 743197 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:53:19.5797355Z W0907 13:53:19.576000 743197 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T13:53:44.2556023Z 2025-09-07T13:53:44.3721618Z running benchmark: 0% 0/30 [00:00 2025-09-07T14:01:13.9755292Z W0907 14:01:13.972000 762358 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T14:01:13.9756344Z W0907 14:01:13.972000 762358 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T14:01:13.9757267Z W0907 14:01:13.972000 762358 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T14:01:13.9757885Z W0907 14:01:13.972000 762358 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:01:13.9758338Z W0907 14:01:13.972000 762358 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:01:14.2129428Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T14:01:14.2130174Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T14:01:14.2131091Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T14:01:14.2131396Z 2025-09-07T14:01:17.9653848Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T14:01:17.9654863Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T14:01:17.9655706Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T14:01:17.9656025Z 2025-09-07T14:01:24.0402377Z 2025-09-07T14:01:24.1543237Z running benchmark: 0% 0/30 [00:00 2025-09-07T14:13:27.8651584Z W0907 14:13:27.862000 824620 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T14:13:27.8652673Z W0907 14:13:27.862000 824620 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T14:13:27.8653897Z W0907 14:13:27.862000 824620 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T14:13:27.8654656Z W0907 14:13:27.862000 824620 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:13:27.8655119Z W0907 14:13:27.862000 824620 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:13:28.1084538Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T14:13:28.1085308Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T14:13:28.1086114Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T14:13:28.1086442Z 2025-09-07T14:13:31.5530785Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T14:13:31.5531575Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T14:13:31.5532359Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T14:13:31.5532671Z 2025-09-07T14:13:37.8953490Z 2025-09-07T14:13:38.0126823Z running benchmark: 0% 0/30 [00:00 found. Please update your _register_pytree_node call with a `serialized_type_name` kwarg. 2025-09-07T14:16:11.3719852Z warmup_failed 2025-09-07T14:16:13.0078518Z Run failed with return code: 255 2025-09-07T14:16:13.0079008Z Output: None 2025-09-07T14:16:13.0079341Z Error: None 2025-09-07T14:16:13.4992849Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T14:16:13.4993970Z import pynvml # type: ignore[import] 2025-09-07T14:16:15.9339490Z 2025-09-07T14:16:18.1347840Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:16:18.1348421Z loading model: 0it [00:02, ?it/s] 2025-09-07T14:16:18.1404907Z cuda eval timm_efficientnet 2025-09-07T14:16:39.2523955Z 2025-09-07T14:16:40.2446937Z running benchmark: 0% 0/30 [00:00", line 1, in 2025-09-07T14:20:47.3398419Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1593, in wrapped_fn 2025-09-07T14:20:47.3398844Z return tuple(flat_fn(*args)) 2025-09-07T14:20:47.3399290Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/utils.py", line 187, in flat_fn 2025-09-07T14:20:47.3399737Z tree_out = fn(*args, **kwargs) 2025-09-07T14:20:47.3400454Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_functorch/_aot_autograd/graph_capture_wrappers.py", line 1354, in functional_call 2025-09-07T14:20:47.3401000Z out = mod(*args[params_len:], **kwargs) 2025-09-07T14:20:47.3401454Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T14:20:47.3401941Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T14:20:47.3402519Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T14:20:47.3403109Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T14:20:47.3403589Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T14:20:47.3404019Z ret_val = forward(*args, **kwargs) 2025-09-07T14:20:47.3404429Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T14:20:47.3404865Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T14:20:47.3405352Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:20:47.3405811Z return self._call_impl(*args, **kwargs) 2025-09-07T14:20:47.3406241Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:20:47.3406670Z return forward_call(*args, **kwargs) 2025-09-07T14:20:47.3407066Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/export/_trace.py", line 1906, in forward 2025-09-07T14:20:47.3407464Z tree_out = mod(*args, **kwargs) 2025-09-07T14:20:47.3407901Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T14:20:47.3408381Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T14:20:47.3408879Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T14:20:47.3409473Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T14:20:47.3409939Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T14:20:47.3410486Z ret_val = forward(*args, **kwargs) 2025-09-07T14:20:47.3410891Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T14:20:47.3411322Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T14:20:47.3411797Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:20:47.3412247Z return self._call_impl(*args, **kwargs) 2025-09-07T14:20:47.3412670Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:20:47.3413096Z return forward_call(*args, **kwargs) 2025-09-07T14:20:47.3413442Z File "/torchbench/torchbenchmark/models/tts_angular/model.py", line 73, in forward 2025-09-07T14:20:47.3413779Z d = self.layers(x) 2025-09-07T14:20:47.3414196Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T14:20:47.3414673Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T14:20:47.3415167Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T14:20:47.3415688Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T14:20:47.3416149Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T14:20:47.3416575Z ret_val = forward(*args, **kwargs) 2025-09-07T14:20:47.3416977Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T14:20:47.3417504Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T14:20:47.3417972Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:20:47.3418431Z return self._call_impl(*args, **kwargs) 2025-09-07T14:20:47.3418922Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:20:47.3419350Z return forward_call(*args, **kwargs) 2025-09-07T14:20:47.3419825Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/container.py", line 250, in forward 2025-09-07T14:20:47.3420365Z input = module(input) 2025-09-07T14:20:47.3420785Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T14:20:47.3421256Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T14:20:47.3421752Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T14:20:47.3422260Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T14:20:47.3422719Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T14:20:47.3423139Z ret_val = forward(*args, **kwargs) 2025-09-07T14:20:47.3423546Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T14:20:47.3423978Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T14:20:47.3424457Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:20:47.3424914Z return self._call_impl(*args, **kwargs) 2025-09-07T14:20:47.3425343Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:20:47.3425769Z return forward_call(*args, **kwargs) 2025-09-07T14:20:47.3426202Z File "/torchbench/torchbenchmark/models/tts_angular/model.py", line 18, in forward 2025-09-07T14:20:47.3426543Z o, (_, _) = self.lstm(x) 2025-09-07T14:20:47.3426980Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 843, in module_call_wrapper 2025-09-07T14:20:47.3427462Z return self.call_module(mod, forward, args, kwargs) 2025-09-07T14:20:47.3427958Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1997, in call_module 2025-09-07T14:20:47.3428483Z return Tracer.call_module(self, m, forward, args, kwargs) 2025-09-07T14:20:47.3428947Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 560, in call_module 2025-09-07T14:20:47.3429371Z ret_val = forward(*args, **kwargs) 2025-09-07T14:20:47.3429779Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/_symbolic_trace.py", line 836, in forward 2025-09-07T14:20:47.3430321Z return _orig_module_call(mod, *args, **kwargs) 2025-09-07T14:20:47.3430786Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl 2025-09-07T14:20:47.3431247Z return self._call_impl(*args, **kwargs) 2025-09-07T14:20:47.3431672Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl 2025-09-07T14:20:47.3432118Z return forward_call(*args, **kwargs) 2025-09-07T14:20:47.3432521Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 1046, in forward 2025-09-07T14:20:47.3432915Z self._update_flat_weights() 2025-09-07T14:20:47.3433340Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 393, in _update_flat_weights 2025-09-07T14:20:47.3433781Z self._init_flat_weights() 2025-09-07T14:20:47.3434387Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 215, in _init_flat_weights 2025-09-07T14:20:47.3434825Z self.flatten_parameters() 2025-09-07T14:20:47.3435231Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 255, in flatten_parameters 2025-09-07T14:20:47.3435658Z unique_data_ptrs = { 2025-09-07T14:20:47.3436100Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/nn/modules/rnn.py", line 256, in 2025-09-07T14:20:47.3436532Z p.data_ptr() # type: ignore[union-attr] 2025-09-07T14:20:47.3437101Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1409, in __torch_function__ 2025-09-07T14:20:47.3437593Z return func(*args, **kwargs) 2025-09-07T14:20:47.3438061Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/fx/experimental/proxy_tensor.py", line 1479, in __torch_function__ 2025-09-07T14:20:47.3438559Z return func(*args, **kwargs) 2025-09-07T14:20:47.3438999Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_export/non_strict_utils.py", line 1066, in __torch_function__ 2025-09-07T14:20:47.3439452Z return func(*args, **kwargs) 2025-09-07T14:20:47.3440659Z RuntimeError: Cannot access data pointer of Tensor (e.g. FakeTensor, FunctionalTensor). If you're using torch.compile/export/fx, it is likely that we are erroneously tracing into a custom kernel. To fix this, please wrap the custom kernel into an opaque custom op. Please see the following for details: https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-09-07T14:20:47.3441743Z warmup_failed 2025-09-07T14:20:48.3927924Z Run failed with return code: 255 2025-09-07T14:20:48.3928203Z Output: None 2025-09-07T14:20:48.3928384Z Error: None 2025-09-07T14:20:48.8793555Z /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you. 2025-09-07T14:20:48.8794848Z import pynvml # type: ignore[import] 2025-09-07T14:20:51.2977157Z 2025-09-07T14:20:53.4474103Z loading model: 0it [00:00, ?it/s] 2025-09-07T14:20:53.4474788Z loading model: 0it [00:02, ?it/s] 2025-09-07T14:20:53.4482263Z cuda eval vgg16 2025-09-07T14:21:07.4589622Z 2025-09-07T14:21:07.5590532Z running benchmark: 0% 0/30 [00:00 2025-09-07T14:32:23.8963246Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8963591Z 2025-09-07T14:32:23.8963753Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T14:32:23.8964370Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T14:32:23.8964964Z anchors = self.anchor_generator(images, features) 2025-09-07T14:32:23.8965583Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T14:32:23.8966217Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T14:32:23.8966886Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T14:32:23.8967685Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8968518Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T14:32:23.8969209Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8969521Z 2025-09-07T14:32:23.8969661Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T14:32:23.8970330Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T14:32:23.8970884Z anchors = self.anchor_generator(images, features) 2025-09-07T14:32:23.8971457Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T14:32:23.8972136Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T14:32:23.8972737Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T14:32:23.8973449Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8974142Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T14:32:23.8974903Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8975215Z 2025-09-07T14:32:23.8975359Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T14:32:23.8975908Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T14:32:23.8976525Z anchors = self.anchor_generator(images, features) 2025-09-07T14:32:23.8977096Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T14:32:23.8977729Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T14:32:23.8978339Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T14:32:23.8979038Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8979663Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T14:32:23.8980372Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8980656Z 2025-09-07T14:32:23.8980782Z cudagraph partition due to DeviceCopy ops. Found from : 2025-09-07T14:32:23.8981279Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/rpn.py", line 361, in forward 2025-09-07T14:32:23.8981748Z anchors = self.anchor_generator(images, features) 2025-09-07T14:32:23.8982241Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 130, in forward 2025-09-07T14:32:23.8982740Z cell_anchors = self.set_cell_anchors(dtype, device) 2025-09-07T14:32:23.8983262Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in set_cell_anchors 2025-09-07T14:32:23.8983882Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8984481Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/anchor_utils.py", line 77, in 2025-09-07T14:32:23.8985072Z return [cell_anchor.to(dtype=dtype, device=device) for cell_anchor in self.cell_anchors] 2025-09-07T14:32:23.8985343Z 2025-09-07T14:32:23.9135204Z cudagraph partition into 2 partitions 2025-09-07T14:32:27.4625329Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break from `Tensor.item()`, consider setting: 2025-09-07T14:32:27.4626943Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] torch._dynamo.config.capture_scalar_outputs = True 2025-09-07T14:32:27.4628179Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] or: 2025-09-07T14:32:27.4629459Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] env TORCHDYNAMO_CAPTURE_SCALAR_OUTPUTS=1 2025-09-07T14:32:27.4630874Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] to include these operations in the captured graph. 2025-09-07T14:32:27.4631561Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:32:27.4632196Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] Graph break: from user code at: 2025-09-07T14:32:27.4633744Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/generalized_rcnn.py", line 118, in torch_dynamo_resume_in_forward_at_117 2025-09-07T14:32:27.4635229Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] detections, detector_losses = self.roi_heads(features, proposals, images.image_sizes, targets) 2025-09-07T14:32:27.4636574Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/models/detection/roi_heads.py", line 763, in forward 2025-09-07T14:32:27.4637837Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] box_features = self.box_roi_pool(features, proposals, image_shapes) 2025-09-07T14:32:27.4639023Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 310, in forward 2025-09-07T14:32:27.4639944Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] self.scales, self.map_levels = _setup_scales( 2025-09-07T14:32:27.4640995Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in _setup_scales 2025-09-07T14:32:27.4641958Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T14:32:27.4642910Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 122, in 2025-09-07T14:32:27.4643857Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scales = [_infer_scale(feat, original_input_shape) for feat in features] 2025-09-07T14:32:27.4644814Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 104, in _infer_scale 2025-09-07T14:32:27.4645731Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] scale = 2 ** float(torch.tensor(approx_scale).log2().round()) 2025-09-07T14:32:27.4646356Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:32:27.4646815Z W0907 14:32:27.461000 913211 site-packages/torch/_dynamo/variables/tensor.py:1048] [12/0] 2025-09-07T14:32:27.7039897Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T14:32:27.7040911Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 125, in torch_dynamo_resume_in__setup_scales_at_122 2025-09-07T14:32:27.7041670Z lvl_min = -torch.log2(torch.tensor(scales[0], dtype=torch.float32)).item() 2025-09-07T14:32:27.7041975Z 2025-09-07T14:32:31.1217937Z cudagraph partition due to non gpu ops. Found from : 2025-09-07T14:32:31.1219217Z File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torchvision/ops/poolers.py", line 126, in torch_dynamo_resume_in__setup_scales_at_125 2025-09-07T14:32:31.1220991Z lvl_max = -torch.log2(torch.tensor(scales[-1], dtype=torch.float32)).item() 2025-09-07T14:32:31.1221279Z 2025-09-07T14:32:37.4032853Z 2025-09-07T14:32:37.5197220Z running benchmark: 0% 0/30 [00:00> $GITHUB_ENV 2025-09-07T14:33:37.5641307Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-09-07T14:33:37.5655753Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:33:37.5656028Z env: 2025-09-07T14:33:37.5656184Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:33:37.5656427Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:33:37.5656755Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:33:37.5657167Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:33:37.5657520Z ##[endgroup] 2025-09-07T14:33:37.5688441Z + [[ -n '' ]] 2025-09-07T14:33:37.5688724Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-09-07T14:33:37.8382990Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T14:33:38.5494055Z Collecting boto3==1.35.33 2025-09-07T14:33:38.6225367Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-09-07T14:33:38.6565417Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.1/139.1 KB 4.1 MB/s eta 0:00:00 2025-09-07T14:33:38.8022917Z Collecting psutil==7.0.0 2025-09-07T14:33:38.8145641Z 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) 2025-09-07T14:33:38.8363382Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 278.0/278.0 KB 13.4 MB/s eta 0:00:00 2025-09-07T14:33:38.8573290Z Collecting pynvml==12.0.0 2025-09-07T14:33:38.8687488Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-09-07T14:33:38.8978708Z Collecting jmespath<2.0.0,>=0.7.1 2025-09-07T14:33:38.9107660Z Downloading jmespath-1.0.1-py3-none-any.whl (20 kB) 2025-09-07T14:33:38.9464246Z Collecting s3transfer<0.11.0,>=0.10.0 2025-09-07T14:33:38.9584033Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-09-07T14:33:38.9658102Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83.2/83.2 KB 12.8 MB/s eta 0:00:00 2025-09-07T14:33:39.6873430Z Collecting botocore<1.36.0,>=1.35.33 2025-09-07T14:33:39.7006680Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-09-07T14:33:39.8227572Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.3/13.3 MB 112.4 MB/s eta 0:00:00 2025-09-07T14:33:39.8875393Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-09-07T14:33:39.8995002Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-09-07T14:33:39.9089873Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 47.5/47.5 KB 4.8 MB/s eta 0:00:00 2025-09-07T14:33:39.9156660Z 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) 2025-09-07T14:33:39.9163665Z 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) 2025-09-07T14:33:40.2467488Z Installing collected packages: nvidia-ml-py, pynvml, psutil, jmespath, botocore, s3transfer, boto3 2025-09-07T14:33:40.2468347Z Attempting uninstall: nvidia-ml-py 2025-09-07T14:33:40.2473327Z Found existing installation: nvidia-ml-py 11.525.84 2025-09-07T14:33:40.2509802Z Uninstalling nvidia-ml-py-11.525.84: 2025-09-07T14:33:40.2536918Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-09-07T14:33:40.3228125Z Attempting uninstall: psutil 2025-09-07T14:33:40.3234626Z Found existing installation: psutil 5.9.8 2025-09-07T14:33:40.3399038Z Uninstalling psutil-5.9.8: 2025-09-07T14:33:40.3407904Z Successfully uninstalled psutil-5.9.8 2025-09-07T14:33:41.0629324Z 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 2025-09-07T14:33:41.1552359Z + DEVICE_NAME= 2025-09-07T14:33:41.1552700Z + DEVICE_TYPE= 2025-09-07T14:33:41.1553044Z + command -v nvidia-smi 2025-09-07T14:33:41.1554064Z + python3 -mpip install torch==2.7.1 2025-09-07T14:33:41.1554648Z /usr/bin/nvidia-smi 2025-09-07T14:33:41.4256752Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T14:33:41.6436991Z Collecting torch==2.7.1 2025-09-07T14:33:41.7053136Z Downloading torch-2.7.1-cp310-cp310-manylinux_2_28_x86_64.whl (821.2 MB) 2025-09-07T14:33:54.6640576Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 821.2/821.2 MB 1.2 MB/s eta 0:00:00 2025-09-07T14:33:55.5425199Z Collecting nvidia-cublas-cu12==12.6.4.1 2025-09-07T14:33:55.5561973Z Downloading nvidia_cublas_cu12-12.6.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (393.1 MB) 2025-09-07T14:34:11.1819851Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 393.1/393.1 MB 2.9 MB/s eta 0:00:00 2025-09-07T14:34:11.5780497Z Collecting nvidia-cudnn-cu12==9.5.1.17 2025-09-07T14:34:11.5912646Z Downloading nvidia_cudnn_cu12-9.5.1.17-py3-none-manylinux_2_28_x86_64.whl (571.0 MB) 2025-09-07T14:34:36.6580576Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 571.0/571.0 MB 1.8 MB/s eta 0:00:00 2025-09-07T14:34:37.2166295Z Collecting nvidia-cusparse-cu12==12.5.4.2 2025-09-07T14:34:37.2290626Z Downloading nvidia_cusparse_cu12-12.5.4.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (216.6 MB) 2025-09-07T14:34:46.1061155Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 216.6/216.6 MB 5.5 MB/s eta 0:00:00 2025-09-07T14:34:46.7017136Z Collecting fsspec 2025-09-07T14:34:46.7145520Z Downloading fsspec-2025.9.0-py3-none-any.whl (199 kB) 2025-09-07T14:34:47.0525924Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 199.3/199.3 KB 563.3 kB/s eta 0:00:00 2025-09-07T14:34:47.3801755Z Collecting nvidia-cusparselt-cu12==0.6.3 2025-09-07T14:34:47.3923835Z Downloading nvidia_cusparselt_cu12-0.6.3-py3-none-manylinux2014_x86_64.whl (156.8 MB) 2025-09-07T14:34:51.3883374Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 156.8/156.8 MB 9.9 MB/s eta 0:00:00 2025-09-07T14:34:51.5360836Z Requirement already satisfied: typing-extensions>=4.10.0 in /home/charlie/.local/lib/python3.10/site-packages (from torch==2.7.1) (4.15.0) 2025-09-07T14:34:51.5940568Z Collecting networkx 2025-09-07T14:34:51.6065271Z Downloading networkx-3.4.2-py3-none-any.whl (1.7 MB) 2025-09-07T14:34:51.6447387Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.7/1.7 MB 47.6 MB/s eta 0:00:00 2025-09-07T14:34:51.6684078Z Collecting nvidia-cufile-cu12==1.11.1.6 2025-09-07T14:34:51.6983900Z Downloading nvidia_cufile_cu12-1.11.1.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (1.1 MB) 2025-09-07T14:34:51.7285397Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 39.8 MB/s eta 0:00:00 2025-09-07T14:34:51.7544463Z Collecting nvidia-cuda-cupti-cu12==12.6.80 2025-09-07T14:34:51.7672644Z Downloading nvidia_cuda_cupti_cu12-12.6.80-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (8.9 MB) 2025-09-07T14:34:51.9353053Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 8.9/8.9 MB 53.7 MB/s eta 0:00:00 2025-09-07T14:34:51.9806116Z Collecting sympy>=1.13.3 2025-09-07T14:34:51.9928237Z Downloading sympy-1.14.0-py3-none-any.whl (6.3 MB) 2025-09-07T14:34:52.1107179Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 6.3/6.3 MB 54.4 MB/s eta 0:00:00 2025-09-07T14:34:52.1488913Z Collecting nvidia-nccl-cu12==2.26.2 2025-09-07T14:34:52.1611481Z Downloading nvidia_nccl_cu12-2.26.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (201.3 MB) 2025-09-07T14:34:56.0559581Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 201.3/201.3 MB 7.8 MB/s eta 0:00:00 2025-09-07T14:34:56.2731039Z Collecting triton==3.3.1 2025-09-07T14:34:56.2857538Z Downloading triton-3.3.1-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (155.6 MB) 2025-09-07T14:34:58.7002847Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 155.6/155.6 MB 12.8 MB/s eta 0:00:00 2025-09-07T14:34:58.8745289Z Collecting nvidia-nvjitlink-cu12==12.6.85 2025-09-07T14:34:58.8874144Z Downloading nvidia_nvjitlink_cu12-12.6.85-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl (19.7 MB) 2025-09-07T14:34:59.1461141Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.7/19.7 MB 63.0 MB/s eta 0:00:00 2025-09-07T14:34:59.1922549Z Collecting nvidia-cusolver-cu12==11.7.1.2 2025-09-07T14:34:59.2050036Z Downloading nvidia_cusolver_cu12-11.7.1.2-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (158.2 MB) 2025-09-07T14:35:03.8288407Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 158.2/158.2 MB 8.8 MB/s eta 0:00:00 2025-09-07T14:35:04.0017985Z Collecting nvidia-cufft-cu12==11.3.0.4 2025-09-07T14:35:04.0152487Z Downloading nvidia_cufft_cu12-11.3.0.4-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (200.2 MB) 2025-09-07T14:35:12.9412365Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 200.2/200.2 MB 6.7 MB/s eta 0:00:00 2025-09-07T14:35:13.1632323Z Collecting jinja2 2025-09-07T14:35:13.1763154Z Downloading jinja2-3.1.6-py3-none-any.whl (134 kB) 2025-09-07T14:35:13.1854186Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.9/134.9 KB 18.2 MB/s eta 0:00:00 2025-09-07T14:35:13.2104013Z Collecting nvidia-cuda-runtime-cu12==12.6.77 2025-09-07T14:35:13.2232004Z Downloading nvidia_cuda_runtime_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (897 kB) 2025-09-07T14:35:13.2598803Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 897.7/897.7 KB 25.7 MB/s eta 0:00:00 2025-09-07T14:35:13.2858595Z Collecting nvidia-nvtx-cu12==12.6.77 2025-09-07T14:35:13.2983392Z Downloading nvidia_nvtx_cu12-12.6.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (89 kB) 2025-09-07T14:35:13.3063408Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 89.3/89.3 KB 12.8 MB/s eta 0:00:00 2025-09-07T14:35:13.3444861Z Collecting filelock 2025-09-07T14:35:13.3571347Z Downloading filelock-3.19.1-py3-none-any.whl (15 kB) 2025-09-07T14:35:13.3858347Z Collecting nvidia-cuda-nvrtc-cu12==12.6.77 2025-09-07T14:35:13.3985274Z Downloading nvidia_cuda_nvrtc_cu12-12.6.77-py3-none-manylinux2014_x86_64.whl (23.7 MB) 2025-09-07T14:35:14.1688495Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 23.7/23.7 MB 28.6 MB/s eta 0:00:00 2025-09-07T14:35:14.2169581Z Collecting nvidia-curand-cu12==10.3.7.77 2025-09-07T14:35:14.2295756Z Downloading nvidia_curand_cu12-10.3.7.77-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (56.3 MB) 2025-09-07T14:35:15.9189011Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 56.3/56.3 MB 19.1 MB/s eta 0:00:00 2025-09-07T14:35:15.9979494Z 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) 2025-09-07T14:35:16.0256393Z Collecting mpmath<1.4,>=1.1.0 2025-09-07T14:35:16.0377441Z Downloading mpmath-1.3.0-py3-none-any.whl (536 kB) 2025-09-07T14:35:16.0617777Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 536.2/536.2 KB 23.8 MB/s eta 0:00:00 2025-09-07T14:35:16.2462517Z Collecting MarkupSafe>=2.0 2025-09-07T14:35:16.2585466Z Downloading MarkupSafe-3.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (20 kB) 2025-09-07T14:35:16.5917376Z 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 2025-09-07T14:35:20.6677854Z WARNING: The scripts proton and proton-viewer are installed in '/home/charlie/.local/bin' which is not on PATH. 2025-09-07T14:35:20.6681287Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T14:35:24.1523100Z WARNING: The script isympy is installed in '/home/charlie/.local/bin' which is not on PATH. 2025-09-07T14:35:24.1523821Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T14:35:57.2016496Z WARNING: The scripts torchfrtrace and torchrun are installed in '/home/charlie/.local/bin' which is not on PATH. 2025-09-07T14:35:57.2017379Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T14:35:58.0905538Z 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 2025-09-07T14:35:58.7783504Z + echo DEVICE_NAME= 2025-09-07T14:35:58.7783922Z + echo DEVICE_TYPE= 2025-09-07T14:35:58.8032787Z ##[group]Run set -eux 2025-09-07T14:35:58.8033260Z set -eux 2025-09-07T14:35:58.8033452Z  2025-09-07T14:35:58.8033669Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-09-07T14:35:58.8033964Z  echo "Missing github-token input" 2025-09-07T14:35:58.8034199Z  exit 1 2025-09-07T14:35:58.8034351Z fi 2025-09-07T14:35:58.8048781Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:35:58.8049099Z env: 2025-09-07T14:35:58.8049294Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:35:58.8049565Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:35:58.8049931Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:35:58.8050565Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:35:58.8050934Z DEVICE_NAME: 2025-09-07T14:35:58.8051111Z DEVICE_TYPE: 2025-09-07T14:35:58.8051480Z GITHUB_TOKEN: *** 2025-09-07T14:35:58.8051656Z ##[endgroup] 2025-09-07T14:35:58.8528795Z + [[ -z *** ]] 2025-09-07T14:35:58.8965338Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-09-07T14:35:58.8965706Z with: 2025-09-07T14:35:58.8966061Z github-token: *** 2025-09-07T14:35:58.8966255Z env: 2025-09-07T14:35:58.8966434Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:35:58.8966709Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:35:58.8967078Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:35:58.8967701Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:35:58.8968105Z DEVICE_NAME: 2025-09-07T14:35:58.8968282Z DEVICE_TYPE: 2025-09-07T14:35:58.8968456Z ##[endgroup] 2025-09-07T14:35:59.0369578Z ##[group]Run set -eux 2025-09-07T14:35:59.0369807Z set -eux 2025-09-07T14:35:59.0370003Z  2025-09-07T14:35:59.0370608Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-09-07T14:35:59.0385470Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:35:59.0385882Z env: 2025-09-07T14:35:59.0386042Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:35:59.0386298Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:35:59.0386626Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:35:59.0387041Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:35:59.0387392Z DEVICE_NAME: 2025-09-07T14:35:59.0387562Z DEVICE_TYPE: 2025-09-07T14:35:59.0387842Z GITHUB_TOKEN: *** 2025-09-07T14:35:59.0388031Z ##[endgroup] 2025-09-07T14:35:59.0866291Z + python3 /home/charlie/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525296438 i-0b7d0f7dc0527ca9b-1003 2025-09-07T14:36:00.0460797Z setting job-id=49775781854 2025-09-07T14:36:00.0461681Z setting job-name=test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T14:36:00.0674128Z ##[group]Run set -eux 2025-09-07T14:36:00.0674346Z set -eux 2025-09-07T14:36:00.0674598Z  2025-09-07T14:36:00.0674754Z if [[ -n "" ]]; then 2025-09-07T14:36:00.0674965Z  source "" 2025-09-07T14:36:00.0675137Z fi 2025-09-07T14:36:00.0675292Z  2025-09-07T14:36:00.0675572Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-09-07T14:36:00.0675950Z  --schema-version "${SCHEMA_VERSION}" \ 2025-09-07T14:36:00.0676221Z  --repo "${REPO}" \ 2025-09-07T14:36:00.0676451Z  --head-branch "${HEAD_BRANCH}" \ 2025-09-07T14:36:00.0676704Z  --head-sha "${HEAD_SHA}" \ 2025-09-07T14:36:00.0677199Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-09-07T14:36:00.0677478Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-09-07T14:36:00.0677720Z  --job-id "${JOB_ID}" \ 2025-09-07T14:36:00.0677941Z  --job-name "${JOB_NAME}" 2025-09-07T14:36:00.0692254Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:00.0692548Z env: 2025-09-07T14:36:00.0692709Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:00.0692958Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:00.0693284Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:00.0693713Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:00.0694075Z DEVICE_NAME: 2025-09-07T14:36:00.0694249Z DEVICE_TYPE: 2025-09-07T14:36:00.0694414Z SCHEMA_VERSION: v3 2025-09-07T14:36:00.0694588Z REPO: pytorch/pytorch 2025-09-07T14:36:00.0694782Z HEAD_BRANCH: refs/heads/main 2025-09-07T14:36:00.0695017Z HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634 2025-09-07T14:36:00.0695266Z WORKFLOW_RUN_ID: 17525296438 2025-09-07T14:36:00.0695445Z RUN_ATTEMPT: 1 2025-09-07T14:36:00.0695605Z JOB_ID: 49775781854 2025-09-07T14:36:00.0695909Z JOB_NAME: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T14:36:00.0696250Z ##[endgroup] 2025-09-07T14:36:00.1170179Z + [[ -n '' ]] 2025-09-07T14:36:00.1171848Z + python3 /home/charlie/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha 93fb23d6fae7c4e82c4239a1033e522088742634 --workflow-id 17525296438 --run-attempt 1 --job-id 49775781854 --job-name 'test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)' 2025-09-07T14:36:00.1573570Z ##[group]Run set -eux 2025-09-07T14:36:00.1573785Z set -eux 2025-09-07T14:36:00.1573965Z  2025-09-07T14:36:00.1574151Z if [[ -n "" ]]; then 2025-09-07T14:36:00.1574350Z  source "" 2025-09-07T14:36:00.1574525Z fi 2025-09-07T14:36:00.1574680Z  2025-09-07T14:36:00.1574977Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-09-07T14:36:00.1588549Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:00.1588832Z env: 2025-09-07T14:36:00.1588997Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:00.1589249Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:00.1589587Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:00.1589996Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:00.1590521Z DEVICE_NAME: 2025-09-07T14:36:00.1590691Z DEVICE_TYPE: 2025-09-07T14:36:00.1590853Z ##[endgroup] 2025-09-07T14:36:00.2022640Z + [[ -n '' ]] 2025-09-07T14:36:00.2023237Z + python3 /home/charlie/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-09-07T14:36:00.9542401Z /home/charlie/.local/lib/python3.10/site-packages/torch/_subclasses/functional_tensor.py:276: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at /pytorch/torch/csrc/utils/tensor_numpy.cpp:81.) 2025-09-07T14:36:00.9544135Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-09-07T14:36:02.4394542Z ##[group]Run set -eux 2025-09-07T14:36:02.4394770Z set -eux 2025-09-07T14:36:02.4394946Z  2025-09-07T14:36:02.4395128Z # TODO (huydhn): Implement this part 2025-09-07T14:36:02.4395409Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-09-07T14:36:02.4409723Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:02.4410017Z env: 2025-09-07T14:36:02.4410185Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:02.4410593Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:02.4411184Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:02.4411616Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:02.4411972Z DEVICE_NAME: 2025-09-07T14:36:02.4412147Z DEVICE_TYPE: 2025-09-07T14:36:02.4412305Z ##[endgroup] 2025-09-07T14:36:02.4888380Z + echo 'dependencies={}' 2025-09-07T14:36:02.5334420Z ##[group]Run set -eux 2025-09-07T14:36:02.5334637Z set -eux 2025-09-07T14:36:02.5334819Z  2025-09-07T14:36:02.5334978Z if [[ -n "" ]]; then 2025-09-07T14:36:02.5335184Z  source "" 2025-09-07T14:36:02.5335369Z fi 2025-09-07T14:36:02.5335525Z  2025-09-07T14:36:02.5335724Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-09-07T14:36:02.5336059Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-09-07T14:36:02.5336426Z  # We don't want the job to fail if the directory doesn't exist 2025-09-07T14:36:02.5336727Z  exit 0 2025-09-07T14:36:02.5336896Z fi 2025-09-07T14:36:02.5337044Z  2025-09-07T14:36:02.5337216Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-09-07T14:36:02.5337578Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T14:36:02.5338003Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T14:36:02.5338320Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T14:36:02.5338581Z  --runners "${RUNNER_INFO}" \ 2025-09-07T14:36:02.5338840Z  --dependencies "${DEPENDENCIES}" \ 2025-09-07T14:36:02.5339086Z  --dry-run 2025-09-07T14:36:02.5339271Z else 2025-09-07T14:36:02.5339695Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-09-07T14:36:02.5340102Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-09-07T14:36:02.5340581Z  --metadata "${BENCHMARK_METADATA}" \ 2025-09-07T14:36:02.5340842Z  --runners "${RUNNER_INFO}" \ 2025-09-07T14:36:02.5341082Z  --dependencies "${DEPENDENCIES}" 2025-09-07T14:36:02.5341316Z fi 2025-09-07T14:36:02.5354186Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:02.5354688Z env: 2025-09-07T14:36:02.5354854Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:02.5355106Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:02.5355442Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:02.5355869Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:02.5356230Z DEVICE_NAME: 2025-09-07T14:36:02.5356396Z DEVICE_TYPE: 2025-09-07T14:36:02.5356587Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-09-07T14:36:02.5356816Z DRY_RUN: false 2025-09-07T14:36:02.5357736Z BENCHMARK_METADATA: {"timestamp": 1757255760, "schema_version": "v3", "name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525296438, "run_attempt": 1, "job_id": 49775781854} 2025-09-07T14:36:02.5359036Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 192, "avail_mem_in_gb": 1999, "extra_info": {"hostname": "5b251226417a"}, "name": "cuda", "type": "NVIDIA H100 80GB HBM3", "gpu_count": 1, "avail_gpu_mem_in_gb": 79}] 2025-09-07T14:36:02.5359594Z DEPENDENCIES: {} 2025-09-07T14:36:02.5359757Z ##[endgroup] 2025-09-07T14:36:02.5821332Z + [[ -n '' ]] 2025-09-07T14:36:02.5821548Z + [[ ! -d test/test-reports ]] 2025-09-07T14:36:02.5821766Z + [[ false == \t\r\u\e ]] 2025-09-07T14:36:02.5825954Z + python3 /home/charlie/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757255760, "schema_version": "v3", "name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525296438, "run_attempt": 1, "job_id": 49775781854}' --runners '[{"cpu_info": "x86_64", "cpu_count": 192, "avail_mem_in_gb": 1999, "extra_info": {"hostname": "5b251226417a"}, "name": "cuda", "type": "NVIDIA H100 80GB HBM3", "gpu_count": 1, "avail_gpu_mem_in_gb": 79}]' --dependencies '{}' 2025-09-07T14:36:02.7198478Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:02.7714661Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role 2025-09-07T14:36:03.0262805Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:03.1635874Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T14:36:03.2976563Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:03.4372046Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:03.5926083Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:03.7899320Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:03.9696580Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:04.1126486Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T14:36:04.2497883Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:04.4029118Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T14:36:04.5526344Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T14:36:04.6987312Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T14:36:04.8414019Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T14:36:05.0160133Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:05.2048495Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:05.4032019Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:05.5873114Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:05.8010797Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:05.9642190Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T14:36:06.1124197Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:06.2583941Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:06.4022777Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:06.5903463Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:06.8182052Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:06.9462768Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:07.1539015Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:07.3647935Z INFO:root:Upload test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:07.5312695Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:07.7530136Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:07.9028743Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:08.1453902Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:08.3103632Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T14:36:08.4792381Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:08.6145285Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:08.7583200Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json 2025-09-07T14:36:08.9286482Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json 2025-09-07T14:36:09.0718958Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json 2025-09-07T14:36:09.2108736Z INFO:root:Upload test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json 2025-09-07T14:36:09.3911855Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525296438/49775781854/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json 2025-09-07T14:36:09.6766050Z ##[group]Run cat test/**/*_toprint.log || true 2025-09-07T14:36:09.6766396Z cat test/**/*_toprint.log || true 2025-09-07T14:36:09.6780911Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:09.6781202Z env: 2025-09-07T14:36:09.6781371Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:09.6781624Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:09.6781960Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:09.6782397Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:09.6782752Z DEVICE_NAME: 2025-09-07T14:36:09.6782924Z DEVICE_TYPE: 2025-09-07T14:36:09.6783077Z ##[endgroup] 2025-09-07T14:36:09.7343251Z cat: 'test/**/*_toprint.log': No such file or directory 2025-09-07T14:36:09.7694055Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-09-07T14:36:09.7694391Z kill "$MONITOR_SCRIPT_PID" 2025-09-07T14:36:09.7708764Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:09.7709054Z env: 2025-09-07T14:36:09.7709217Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:09.7709478Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:09.7709829Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:09.7710394Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:09.7710915Z DEVICE_NAME: 2025-09-07T14:36:09.7711090Z DEVICE_TYPE: 2025-09-07T14:36:09.7711277Z MONITOR_SCRIPT_PID: 8471 2025-09-07T14:36:09.7711468Z ##[endgroup] 2025-09-07T14:36:09.8274861Z Prepare all required actions 2025-09-07T14:36:09.8275286Z Getting action download info 2025-09-07T14:36:10.0005754Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-09-07T14:36:10.7629232Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-09-07T14:36:12.2725183Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-09-07T14:36:12.2725448Z with: 2025-09-07T14:36:12.2725747Z file-suffix: test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T14:36:12.2726097Z s3-bucket: gha-artifacts 2025-09-07T14:36:12.2726300Z env: 2025-09-07T14:36:12.2726462Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:12.2726717Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:12.2727065Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:12.2727524Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:12.2727886Z DEVICE_NAME: 2025-09-07T14:36:12.2728049Z DEVICE_TYPE: 2025-09-07T14:36:12.2728206Z ##[endgroup] 2025-09-07T14:36:12.4182616Z ##[group]Run # Remove any previous test jsons if they exist 2025-09-07T14:36:12.4183431Z # Remove any previous test jsons if they exist 2025-09-07T14:36:12.4184076Z rm -f test-jsons-*.zip 2025-09-07T14:36:12.4184849Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-09-07T14:36:12.4201259Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:12.4201533Z env: 2025-09-07T14:36:12.4201705Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:12.4201942Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:12.4202263Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:12.4202668Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:12.4203024Z DEVICE_NAME: 2025-09-07T14:36:12.4203178Z DEVICE_TYPE: 2025-09-07T14:36:12.4203478Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T14:36:12.4203807Z ##[endgroup] 2025-09-07T14:36:12.4839513Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.4865368Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.4891353Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.4917419Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.4943495Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.5051757Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.5174444Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.5203334Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.5227265Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.5265648Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.5304006Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.5331033Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.5356859Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.5395065Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.5520432Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.5579922Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.5684519Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.5784536Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.5823103Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.5861437Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.5887143Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.5913076Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.5951743Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.6096783Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.6122760Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.6230091Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.6353393Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.6392492Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.6515466Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.6553604Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.6659592Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.6697808Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.6736094Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.6758422Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.6784627Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.6822582Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.6848045Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.6874661Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.json (deflated 99%) 2025-09-07T14:36:12.6913684Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.json (deflated 99%) 2025-09-07T14:36:12.7029610Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.json (deflated 99%) 2025-09-07T14:36:12.7519861Z ##[group]Run # Remove any previous test reports if they exist 2025-09-07T14:36:12.7520373Z # Remove any previous test reports if they exist 2025-09-07T14:36:12.7520678Z rm -f test-reports-*.zip 2025-09-07T14:36:12.7521023Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-09-07T14:36:12.7535279Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:12.7535597Z env: 2025-09-07T14:36:12.7535760Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:12.7536015Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:12.7536354Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:12.7536766Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:12.7537152Z DEVICE_NAME: 2025-09-07T14:36:12.7537315Z DEVICE_TYPE: 2025-09-07T14:36:12.7537617Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T14:36:12.7537966Z ##[endgroup] 2025-09-07T14:36:12.8018927Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 52%) 2025-09-07T14:36:12.8019935Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_performance.csv (deflated 52%) 2025-09-07T14:36:12.8021034Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 59%) 2025-09-07T14:36:12.8021908Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 52%) 2025-09-07T14:36:12.8022868Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T14:36:12.8023811Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 59%) 2025-09-07T14:36:12.8024536Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 59%) 2025-09-07T14:36:12.8025313Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T14:36:12.8026092Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 54%) 2025-09-07T14:36:12.8027354Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T14:36:12.8028150Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 58%) 2025-09-07T14:36:12.8030616Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T14:36:12.8031482Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T14:36:12.8032190Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 68%) 2025-09-07T14:36:12.8032868Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T14:36:12.8034230Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T14:36:12.8035204Z adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 60%) 2025-09-07T14:36:12.8036059Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 51%) 2025-09-07T14:36:12.8036720Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance.csv (deflated 51%) 2025-09-07T14:36:12.8037350Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T14:36:12.8038709Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T14:36:12.8039443Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 52%) 2025-09-07T14:36:12.8040689Z adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T14:36:12.8041443Z adding: test/test-reports/inductor_cudagraphs_low_precision_torchbench_quant_inference_cuda_h100_accuracy.csv (deflated 59%) 2025-09-07T14:36:12.8042143Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cuda_h100_performance.csv (deflated 52%) 2025-09-07T14:36:12.8042791Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 57%) 2025-09-07T14:36:12.8044540Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T14:36:12.8045255Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv (deflated 51%) 2025-09-07T14:36:12.8047417Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T14:36:12.8049652Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T14:36:12.8050495Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 58%) 2025-09-07T14:36:12.8053218Z adding: test/test-reports/inductor_max_autotune_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T14:36:12.8053908Z adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 59%) 2025-09-07T14:36:12.8054545Z adding: test/test-reports/inductor_cpp_wrapper_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 58%) 2025-09-07T14:36:12.8055179Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_performance.csv (deflated 50%) 2025-09-07T14:36:12.8055886Z adding: test/test-reports/inductor_with_cudagraphs_freezing_autotune_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 58%) 2025-09-07T14:36:12.8057308Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 51%) 2025-09-07T14:36:12.8059533Z adding: test/test-reports/inductor_no_cudagraphs_torchbench_amp_training_cuda_h100_performance_compilation_metrics.csv (deflated 50%) 2025-09-07T14:36:12.8060405Z adding: test/test-reports/inductor_with_cudagraphs_freezing_torchbench_bfloat16_inference_cuda_h100_accuracy.csv (deflated 58%) 2025-09-07T14:36:12.8061089Z adding: test/test-reports/inductor_with_cudagraphs_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 57%) 2025-09-07T14:36:12.8063168Z adding: test/test-reports/inductor_max_autotune_torchbench_bfloat16_inference_cuda_h100_performance_compilation_metrics.csv (deflated 52%) 2025-09-07T14:36:12.8063872Z adding: test/test-reports/inductor_dynamic_torchbench_amp_training_cuda_h100_accuracy.csv (deflated 57%) 2025-09-07T14:36:12.8454015Z ##[group]Run # Remove any previous usage logs if they exist 2025-09-07T14:36:12.8454395Z # Remove any previous usage logs if they exist 2025-09-07T14:36:12.8454688Z rm -f logs-*.zip 2025-09-07T14:36:12.8455185Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true 2025-09-07T14:36:12.8455587Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true 2025-09-07T14:36:12.8468945Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:12.8469246Z env: 2025-09-07T14:36:12.8469524Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:12.8469780Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:12.8470112Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:12.8470695Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:12.8471075Z DEVICE_NAME: 2025-09-07T14:36:12.8471247Z DEVICE_TYPE: 2025-09-07T14:36:12.8471543Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T14:36:12.8471883Z ##[endgroup] 2025-09-07T14:36:12.9151853Z adding: usage_log.txt (deflated 91%) 2025-09-07T14:36:12.9174971Z 2025-09-07T14:36:12.9175353Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip) 2025-09-07T14:36:12.9356529Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-09-07T14:36:12.9356919Z # Remove any previous debugging artifacts if they exist 2025-09-07T14:36:12.9357232Z rm -f debug-*.zip 2025-09-07T14:36:12.9357447Z if [ -d 'test/debug' ]; then 2025-09-07T14:36:12.9357706Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-09-07T14:36:12.9357957Z fi 2025-09-07T14:36:12.9371282Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:12.9371573Z env: 2025-09-07T14:36:12.9371727Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:12.9371989Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:12.9372332Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:12.9372758Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:12.9373114Z DEVICE_NAME: 2025-09-07T14:36:12.9373280Z DEVICE_TYPE: 2025-09-07T14:36:12.9373564Z FILE_SUFFIX: test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854 2025-09-07T14:36:12.9373896Z ##[endgroup] 2025-09-07T14:36:13.2122224Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T14:36:13.2122492Z with: 2025-09-07T14:36:13.2122664Z s3-bucket: gha-artifacts 2025-09-07T14:36:13.2122915Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:13.2123178Z retention-days: 14 2025-09-07T14:36:13.2123376Z if-no-files-found: warn 2025-09-07T14:36:13.2123604Z path: test-jsons-*.zip 2025-09-07T14:36:13.2123822Z name: artifact 2025-09-07T14:36:13.2124009Z region: us-east-1 2025-09-07T14:36:13.2124196Z env: 2025-09-07T14:36:13.2124380Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:13.2124652Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:13.2125018Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:13.2125497Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:13.2125897Z DEVICE_NAME: 2025-09-07T14:36:13.2126076Z DEVICE_TYPE: 2025-09-07T14:36:13.2126247Z ##[endgroup] 2025-09-07T14:36:13.5103594Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T14:36:13.5103968Z With the provided path, there will be 1 file uploaded 2025-09-07T14:36:13.5104318Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:13.5112707Z Starting upload of test-jsons-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:13.9401336Z Finished upload of test-jsons-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:13.9777580Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T14:36:13.9777845Z with: 2025-09-07T14:36:13.9778010Z s3-bucket: gha-artifacts 2025-09-07T14:36:13.9778252Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:13.9778755Z retention-days: 14 2025-09-07T14:36:13.9778952Z if-no-files-found: error 2025-09-07T14:36:13.9779155Z path: test-reports-*.zip 2025-09-07T14:36:13.9779345Z name: artifact 2025-09-07T14:36:13.9779507Z region: us-east-1 2025-09-07T14:36:13.9779673Z env: 2025-09-07T14:36:13.9779825Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:13.9780186Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:13.9780717Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:13.9781155Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:13.9781516Z DEVICE_NAME: 2025-09-07T14:36:13.9781682Z DEVICE_TYPE: 2025-09-07T14:36:13.9781854Z ##[endgroup] 2025-09-07T14:36:14.2802978Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T14:36:14.2803354Z With the provided path, there will be 1 file uploaded 2025-09-07T14:36:14.2803749Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:14.2812014Z Starting upload of test-reports-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:14.4456163Z Finished upload of test-reports-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:14.5056587Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T14:36:14.5056868Z with: 2025-09-07T14:36:14.5057039Z s3-bucket: gha-artifacts 2025-09-07T14:36:14.5057291Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:14.5057553Z retention-days: 14 2025-09-07T14:36:14.5057752Z if-no-files-found: ignore 2025-09-07T14:36:14.5057963Z path: logs-*.zip 2025-09-07T14:36:14.5058141Z name: artifact 2025-09-07T14:36:14.5058312Z region: us-east-1 2025-09-07T14:36:14.5058495Z env: 2025-09-07T14:36:14.5058657Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:14.5058914Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:14.5059268Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:14.5059715Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:14.5060103Z DEVICE_NAME: 2025-09-07T14:36:14.5060483Z DEVICE_TYPE: 2025-09-07T14:36:14.5060671Z ##[endgroup] 2025-09-07T14:36:14.8065210Z NOTE: s3-prefix specified, ignoring name parameter 2025-09-07T14:36:14.8065611Z With the provided path, there will be 1 file uploaded 2025-09-07T14:36:14.8065999Z Uploading to s3 prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:14.8074073Z Starting upload of logs-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:14.9796393Z Finished upload of logs-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:15.0335756Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-09-07T14:36:15.0336027Z with: 2025-09-07T14:36:15.0336207Z s3-bucket: gha-artifacts 2025-09-07T14:36:15.0336452Z s3-prefix: pytorch/pytorch/17525296438/1/artifact 2025-09-07T14:36:15.0336739Z retention-days: 14 2025-09-07T14:36:15.0336932Z if-no-files-found: ignore 2025-09-07T14:36:15.0337142Z path: debug-*.zip 2025-09-07T14:36:15.0337320Z name: artifact 2025-09-07T14:36:15.0337495Z region: us-east-1 2025-09-07T14:36:15.0337669Z env: 2025-09-07T14:36:15.0337829Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:15.0338097Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:15.0338466Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:15.0338920Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:15.0339301Z DEVICE_NAME: 2025-09-07T14:36:15.0339477Z DEVICE_TYPE: 2025-09-07T14:36:15.0339652Z ##[endgroup] 2025-09-07T14:36:15.3216715Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-09-07T14:36:15.3692641Z ##[group]Run # shellcheck disable=SC2156 2025-09-07T14:36:15.3692990Z # shellcheck disable=SC2156 2025-09-07T14:36:15.3693472Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-09-07T14:36:15.3708116Z shell: /usr/bin/bash -e {0} 2025-09-07T14:36:15.3708332Z env: 2025-09-07T14:36:15.3708497Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:15.3708927Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:15.3709286Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:15.3709724Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:15.3710091Z DEVICE_NAME: 2025-09-07T14:36:15.3710437Z DEVICE_TYPE: 2025-09-07T14:36:15.3710599Z ##[endgroup] 2025-09-07T14:36:16.1429468Z Prepare all required actions 2025-09-07T14:36:16.1429813Z Getting action download info 2025-09-07T14:36:16.3120481Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-09-07T14:36:16.3120770Z with: 2025-09-07T14:36:16.3120938Z job_id: 49775781854 2025-09-07T14:36:16.3121248Z job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T14:36:16.3121619Z workflow_name: inductor-perf-nightly-h100 2025-09-07T14:36:16.3121864Z workflow_run_id: 17525296438 2025-09-07T14:36:16.3122068Z workflow_attempt: 1 2025-09-07T14:36:16.3122253Z env: 2025-09-07T14:36:16.3122398Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:16.3122636Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:16.3122957Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:16.3123368Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:16.3123716Z DEVICE_NAME: 2025-09-07T14:36:16.3123897Z DEVICE_TYPE: 2025-09-07T14:36:16.3124055Z ##[endgroup] 2025-09-07T14:36:16.4080833Z ##[group]Run echo "workflow_id: 17525296438" 2025-09-07T14:36:16.4081108Z echo "workflow_id: 17525296438" 2025-09-07T14:36:16.4081351Z echo "workflow_attempt: 1" 2025-09-07T14:36:16.4081635Z echo "workflow_Name: inductor-perf-nightly-h100" 2025-09-07T14:36:16.4081919Z echo "job_id: 49775781854" 2025-09-07T14:36:16.4082298Z echo "job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)" 2025-09-07T14:36:16.4082693Z echo "artifact_prefix: " 2025-09-07T14:36:16.4082926Z python3 --version 2025-09-07T14:36:16.4096749Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:16.4097035Z env: 2025-09-07T14:36:16.4097191Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:16.4097441Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:16.4097779Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:16.4098214Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:16.4098575Z DEVICE_NAME: 2025-09-07T14:36:16.4098735Z DEVICE_TYPE: 2025-09-07T14:36:16.4098892Z ##[endgroup] 2025-09-07T14:36:16.4573072Z workflow_id: 17525296438 2025-09-07T14:36:16.4573322Z workflow_attempt: 1 2025-09-07T14:36:16.4573562Z workflow_Name: inductor-perf-nightly-h100 2025-09-07T14:36:16.4573835Z job_id: 49775781854 2025-09-07T14:36:16.4574185Z job_name: test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100) 2025-09-07T14:36:16.4574584Z artifact_prefix: 2025-09-07T14:36:16.4589624Z Python 3.10.12 2025-09-07T14:36:16.5020756Z ##[group]Run nick-fields/retry@v3.0.0 2025-09-07T14:36:16.5021007Z with: 2025-09-07T14:36:16.5021162Z shell: bash 2025-09-07T14:36:16.5021331Z timeout_minutes: 5 2025-09-07T14:36:16.5021513Z max_attempts: 5 2025-09-07T14:36:16.5021706Z retry_wait_seconds: 30 2025-09-07T14:36:16.5022140Z 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 2025-09-07T14:36:16.5022757Z polling_interval_seconds: 1 2025-09-07T14:36:16.5022973Z warning_on_retry: true 2025-09-07T14:36:16.5023166Z continue_on_error: false 2025-09-07T14:36:16.5023352Z env: 2025-09-07T14:36:16.5023520Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:16.5023763Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:16.5024104Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:16.5024545Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:16.5025048Z DEVICE_NAME: 2025-09-07T14:36:16.5025217Z DEVICE_TYPE: 2025-09-07T14:36:16.5025377Z ##[endgroup] 2025-09-07T14:36:17.0076106Z Defaulting to user installation because normal site-packages is not writeable 2025-09-07T14:36:17.4268961Z Collecting python-dateutil==2.8.2 2025-09-07T14:36:17.4842924Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-09-07T14:36:17.9031910Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 247.7/247.7 KB 571.4 kB/s eta 0:00:00 2025-09-07T14:36:18.8357770Z Collecting boto3==1.35.42 2025-09-07T14:36:18.8478805Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-09-07T14:36:19.1022934Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 139.2/139.2 KB 511.6 kB/s eta 0:00:00 2025-09-07T14:36:19.7391596Z Collecting pandas==2.1.3 2025-09-07T14:36:19.7522813Z Downloading pandas-2.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-09-07T14:36:20.7259731Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.3/12.3 MB 12.2 MB/s eta 0:00:00 2025-09-07T14:36:20.7630418Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/charlie/.local/lib/python3.10/site-packages (0.6.7) 2025-09-07T14:36:20.7646405Z Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil==2.8.2) (1.16.0) 2025-09-07T14:36:20.7691122Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/charlie/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.0.1) 2025-09-07T14:36:20.7695927Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/charlie/.local/lib/python3.10/site-packages (from boto3==1.35.42) (0.10.4) 2025-09-07T14:36:20.7700411Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/charlie/.local/lib/python3.10/site-packages (from boto3==1.35.42) (1.35.99) 2025-09-07T14:36:21.2837762Z Collecting pytz>=2020.1 2025-09-07T14:36:21.2942349Z Downloading pytz-2025.2-py2.py3-none-any.whl (509 kB) 2025-09-07T14:36:21.6229217Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 509.2/509.2 KB 1.5 MB/s eta 0:00:00 2025-09-07T14:36:22.4310828Z Collecting numpy<2,>=1.22.4 2025-09-07T14:36:22.4419701Z Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-09-07T14:36:23.3067586Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 18.2/18.2 MB 13.1 MB/s eta 0:00:00 2025-09-07T14:36:23.7183533Z Collecting tzdata>=2022.1 2025-09-07T14:36:23.7295190Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-09-07T14:36:24.1528841Z ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 347.8/347.8 KB 801.7 kB/s eta 0:00:00 2025-09-07T14:36:24.1619722Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/charlie/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-09-07T14:36:24.1624638Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/charlie/.local/lib/python3.10/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-09-07T14:36:24.1677741Z 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) 2025-09-07T14:36:24.1780668Z Requirement already satisfied: packaging>=17.0 in /home/charlie/.local/lib/python3.10/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-09-07T14:36:24.1878393Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/charlie/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-09-07T14:36:24.1883350Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/charlie/.local/lib/python3.10/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0) 2025-09-07T14:36:24.4630723Z Installing collected packages: pytz, tzdata, python-dateutil, numpy, pandas, boto3 2025-09-07T14:36:27.7191598Z WARNING: The script f2py is installed in '/home/charlie/.local/bin' which is not on PATH. 2025-09-07T14:36:27.7192820Z Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. 2025-09-07T14:36:31.4452589Z Attempting uninstall: boto3 2025-09-07T14:36:31.4459050Z Found existing installation: boto3 1.35.33 2025-09-07T14:36:31.4679529Z Uninstalling boto3-1.35.33: 2025-09-07T14:36:31.4700762Z Successfully uninstalled boto3-1.35.33 2025-09-07T14:36:32.1008046Z Successfully installed boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 pytz-2025.2 tzdata-2025.2 2025-09-07T14:36:32.7445568Z Command completed after 1 attempt(s). 2025-09-07T14:36:32.7520024Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T14:36:32.7520825Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-09-07T14:36:32.7521196Z  --workflow-run-id "17525296438" \ 2025-09-07T14:36:32.7521494Z  --workflow-name "inductor-perf-nightly-h100" \ 2025-09-07T14:36:32.7521816Z  --workflow-run-attempt "1" \ 2025-09-07T14:36:32.7522058Z  --job-id "49775781854" \ 2025-09-07T14:36:32.7522433Z  --job-name "test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)" \ 2025-09-07T14:36:32.7522822Z  --local-path "" \ 2025-09-07T14:36:32.7523040Z  --artifact-prefix "" 2025-09-07T14:36:32.7537569Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-09-07T14:36:32.7537872Z env: 2025-09-07T14:36:32.7538037Z GIT_DEFAULT_BRANCH: main 2025-09-07T14:36:32.7538289Z GPU_FLAG: --gpus all -e NVIDIA_DRIVER_CAPABILITIES=all 2025-09-07T14:36:32.7538615Z SCCACHE_SERVER_PORT_DOCKER_FLAG: -e SCCACHE_SERVER_PORT=5229 2025-09-07T14:36:32.7539023Z DOCKER_CONTAINER_ID: 541a5a68225e58de7d31aad35a9c825ab613ffaa6afc79c6734535438423992f 2025-09-07T14:36:32.7539379Z DEVICE_NAME: 2025-09-07T14:36:32.7539547Z DEVICE_TYPE: 2025-09-07T14:36:32.7539713Z ##[endgroup] 2025-09-07T14:36:36.1617381Z repo: pytorch/pytorch 2025-09-07T14:36:36.1617949Z Search for test log in s3 bucket: ossci-utilization 2025-09-07T14:36:36.1618832Z Downloading logs-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:36.1620008Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf_cuda_h100-9-9-linux.aws.h100_49775781854.zip 2025-09-07T14:36:36.1621433Z Converted Log Model: UtilizationMetadata: 2025-09-07T14:36:36.1623501Z UtilizationMetadata(level='metadata', workflow_id='17525296438', job_id='49775781854', workflow_name='inductor-perf-nightly-h100', job_name='test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757232944, gpu_count=1, cpu_count=192, gpu_type='pynvml', error=None) 2025-09-07T14:36:36.1625645Z [Db Segments] detected pytest cmd: 4, generated segments: 4 2025-09-07T14:36:36.1626212Z [db model] Peek db timeseries 2025-09-07T14:36:36.1626583Z :{ 2025-09-07T14:36:36.1626870Z "created_at": 1757255795, 2025-09-07T14:36:36.1627748Z "type": "utilization", 2025-09-07T14:36:36.1628105Z "tags": [ 2025-09-07T14:36:36.1628391Z "record" 2025-09-07T14:36:36.1628685Z ], 2025-09-07T14:36:36.1629002Z "time_stamp": 1757232944, 2025-09-07T14:36:36.1629393Z "repo": "pytorch/pytorch", 2025-09-07T14:36:36.1629774Z "workflow_id": 17525296438, 2025-09-07T14:36:36.1630157Z "run_attempt": 1, 2025-09-07T14:36:36.1630668Z "job_id": 49775781854, 2025-09-07T14:36:36.1631052Z "workflow_name": "inductor-perf-nightly-h100", 2025-09-07T14:36:36.1631457Z "job_name": "test-weekly / test (inductor_torchbench_perf_cuda_h100, 9, 9, linux.aws.h100)", 2025-09-07T14:36:36.1631804Z "json_data": "{}" 2025-09-07T14:36:36.1631970Z } 2025-09-07T14:36:36.1632330Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525296438/1/49775781854/metadata 2025-09-07T14:36:36.1632981Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525296438/1/49775781854/metadata 2025-09-07T14:36:36.1633661Z Writing 1519 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525296438/1/49775781854/time_series 2025-09-07T14:36:36.1634429Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525296438/1/49775781854/time_series 2025-09-07T14:36:36.2546056Z Post job cleanup. 2025-09-07T14:36:36.2579956Z Post job cleanup. 2025-09-07T14:36:36.3493020Z [command]/usr/bin/git version 2025-09-07T14:36:36.3531772Z git version 2.50.1 2025-09-07T14:36:36.3571435Z Temporarily overriding HOME='/home/charlie/_work/_temp/0ce19506-7dec-4dbc-8b62-7891c486f24d' before making global git config changes 2025-09-07T14:36:36.3572142Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T14:36:36.3575959Z [command]/usr/bin/git config --global --add safe.directory /home/charlie/_work/pytorch/pytorch 2025-09-07T14:36:36.3611556Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T14:36:36.3654443Z [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' || :" 2025-09-07T14:36:36.3934945Z Entering 'android/libs/fbjni' 2025-09-07T14:36:36.3987933Z Entering 'third_party/FP16' 2025-09-07T14:36:36.4039296Z Entering 'third_party/FXdiv' 2025-09-07T14:36:36.4089758Z Entering 'third_party/NNPACK' 2025-09-07T14:36:36.4141819Z Entering 'third_party/NVTX' 2025-09-07T14:36:36.4194443Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T14:36:36.4246090Z Entering 'third_party/XNNPACK' 2025-09-07T14:36:36.4311448Z Entering 'third_party/aiter' 2025-09-07T14:36:36.4362100Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T14:36:36.4419469Z Entering 'third_party/benchmark' 2025-09-07T14:36:36.4469144Z Entering 'third_party/composable_kernel' 2025-09-07T14:36:36.4527075Z Entering 'third_party/cpp-httplib' 2025-09-07T14:36:36.4577585Z Entering 'third_party/cpuinfo' 2025-09-07T14:36:36.4628971Z Entering 'third_party/cudnn_frontend' 2025-09-07T14:36:36.4680719Z Entering 'third_party/cutlass' 2025-09-07T14:36:36.4737824Z Entering 'third_party/fbgemm' 2025-09-07T14:36:36.4789644Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T14:36:36.4836952Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T14:36:36.4889584Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T14:36:36.4937408Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T14:36:36.4993836Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T14:36:36.5039246Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T14:36:36.5084493Z Entering 'third_party/fbgemm/external/json' 2025-09-07T14:36:36.5134510Z Entering 'third_party/flash-attention' 2025-09-07T14:36:36.5184775Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T14:36:36.5238576Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T14:36:36.5296671Z Entering 'third_party/flatbuffers' 2025-09-07T14:36:36.5349735Z Entering 'third_party/fmt' 2025-09-07T14:36:36.5399878Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T14:36:36.5451560Z Entering 'third_party/gloo' 2025-09-07T14:36:36.5502128Z Entering 'third_party/googletest' 2025-09-07T14:36:36.5554341Z Entering 'third_party/ideep' 2025-09-07T14:36:36.5603534Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T14:36:36.5659969Z Entering 'third_party/ittapi' 2025-09-07T14:36:36.5710420Z Entering 'third_party/kineto' 2025-09-07T14:36:36.5759652Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T14:36:36.5806777Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T14:36:36.5855940Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T14:36:36.5903053Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T14:36:36.5949547Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T14:36:36.5995631Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T14:36:36.6047185Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T14:36:36.6094236Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T14:36:36.6141032Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T14:36:36.6187988Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T14:36:36.6238506Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T14:36:36.6284834Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T14:36:36.6335608Z Entering 'third_party/kleidiai' 2025-09-07T14:36:36.6387206Z Entering 'third_party/mimalloc' 2025-09-07T14:36:36.6437960Z Entering 'third_party/nlohmann' 2025-09-07T14:36:36.6488873Z Entering 'third_party/onnx' 2025-09-07T14:36:36.6554494Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T14:36:36.6607141Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T14:36:36.6658220Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T14:36:36.6704951Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T14:36:36.6752721Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T14:36:36.6800155Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T14:36:36.6848387Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T14:36:36.6894871Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T14:36:36.6940129Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T14:36:36.6985598Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T14:36:36.7036144Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T14:36:36.7086661Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T14:36:36.7153277Z Entering 'third_party/pocketfft' 2025-09-07T14:36:36.7203731Z Entering 'third_party/protobuf' 2025-09-07T14:36:36.7255488Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T14:36:36.7302542Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T14:36:36.7351762Z Entering 'third_party/psimd' 2025-09-07T14:36:36.7401751Z Entering 'third_party/pthreadpool' 2025-09-07T14:36:36.7453080Z Entering 'third_party/pybind11' 2025-09-07T14:36:36.7503010Z Entering 'third_party/python-peachpy' 2025-09-07T14:36:36.7551658Z Entering 'third_party/sleef' 2025-09-07T14:36:36.7602002Z Entering 'third_party/tensorpipe' 2025-09-07T14:36:36.7651124Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T14:36:36.7698302Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T14:36:36.7744011Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T14:36:36.7791999Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T14:36:36.7837719Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T14:36:36.7913441Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T14:36:36.7937992Z http.https://github.com/.extraheader 2025-09-07T14:36:36.7947438Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader 2025-09-07T14:36:36.7980983Z [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' || :" 2025-09-07T14:36:36.8244001Z Entering 'android/libs/fbjni' 2025-09-07T14:36:36.8272033Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8307840Z Entering 'third_party/FP16' 2025-09-07T14:36:36.8335261Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8369756Z Entering 'third_party/FXdiv' 2025-09-07T14:36:36.8397371Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8434499Z Entering 'third_party/NNPACK' 2025-09-07T14:36:36.8462173Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8498985Z Entering 'third_party/NVTX' 2025-09-07T14:36:36.8528148Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8565550Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T14:36:36.8592757Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8629733Z Entering 'third_party/XNNPACK' 2025-09-07T14:36:36.8656811Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8705597Z Entering 'third_party/aiter' 2025-09-07T14:36:36.8732957Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8769379Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T14:36:36.8796446Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8841999Z Entering 'third_party/benchmark' 2025-09-07T14:36:36.8869902Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8907322Z Entering 'third_party/composable_kernel' 2025-09-07T14:36:36.8935986Z http.https://github.com/.extraheader 2025-09-07T14:36:36.8979925Z Entering 'third_party/cpp-httplib' 2025-09-07T14:36:36.9008071Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9045593Z Entering 'third_party/cpuinfo' 2025-09-07T14:36:36.9073677Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9111036Z Entering 'third_party/cudnn_frontend' 2025-09-07T14:36:36.9139838Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9176426Z Entering 'third_party/cutlass' 2025-09-07T14:36:36.9203854Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9249132Z Entering 'third_party/fbgemm' 2025-09-07T14:36:36.9278081Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9317003Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T14:36:36.9343518Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9379270Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T14:36:36.9407170Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9451008Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T14:36:36.9478138Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9514764Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T14:36:36.9540655Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9585551Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T14:36:36.9611603Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9647414Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T14:36:36.9673003Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9708033Z Entering 'third_party/fbgemm/external/json' 2025-09-07T14:36:36.9733756Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9773704Z Entering 'third_party/flash-attention' 2025-09-07T14:36:36.9801998Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9836918Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T14:36:36.9864437Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9906181Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T14:36:36.9932763Z http.https://github.com/.extraheader 2025-09-07T14:36:36.9979208Z Entering 'third_party/flatbuffers' 2025-09-07T14:36:37.0007487Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0045621Z Entering 'third_party/fmt' 2025-09-07T14:36:37.0074301Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0111413Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T14:36:37.0139976Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0177350Z Entering 'third_party/gloo' 2025-09-07T14:36:37.0204806Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0242455Z Entering 'third_party/googletest' 2025-09-07T14:36:37.0270129Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0306139Z Entering 'third_party/ideep' 2025-09-07T14:36:37.0334804Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0369390Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T14:36:37.0396579Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0440452Z Entering 'third_party/ittapi' 2025-09-07T14:36:37.0468888Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0506104Z Entering 'third_party/kineto' 2025-09-07T14:36:37.0534358Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0569679Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T14:36:37.0598690Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0634641Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T14:36:37.0662519Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0701486Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T14:36:37.0728962Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0765052Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T14:36:37.0791683Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0828097Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T14:36:37.0855088Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0889907Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T14:36:37.0916701Z http.https://github.com/.extraheader 2025-09-07T14:36:37.0956797Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T14:36:37.0983969Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1020440Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T14:36:37.1047198Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1083271Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T14:36:37.1109707Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1146867Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T14:36:37.1173516Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1213113Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T14:36:37.1239641Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1275569Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T14:36:37.1302352Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1341045Z Entering 'third_party/kleidiai' 2025-09-07T14:36:37.1369150Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1404939Z Entering 'third_party/mimalloc' 2025-09-07T14:36:37.1432945Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1469442Z Entering 'third_party/nlohmann' 2025-09-07T14:36:37.1497496Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1533825Z Entering 'third_party/onnx' 2025-09-07T14:36:37.1561423Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1613056Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T14:36:37.1640731Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1681189Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T14:36:37.1709921Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1747422Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T14:36:37.1774787Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1810501Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T14:36:37.1836419Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1872721Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T14:36:37.1898427Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1934370Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T14:36:37.1959950Z http.https://github.com/.extraheader 2025-09-07T14:36:37.1997665Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T14:36:37.2023266Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2058577Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T14:36:37.2085595Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2120764Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T14:36:37.2147388Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2181219Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T14:36:37.2207337Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2246603Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T14:36:37.2273431Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2312351Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T14:36:37.2338236Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2393646Z Entering 'third_party/pocketfft' 2025-09-07T14:36:37.2422143Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2456687Z Entering 'third_party/protobuf' 2025-09-07T14:36:37.2484356Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2521263Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T14:36:37.2547702Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2584475Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T14:36:37.2609925Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2649023Z Entering 'third_party/psimd' 2025-09-07T14:36:37.2677153Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2713639Z Entering 'third_party/pthreadpool' 2025-09-07T14:36:37.2741706Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2776618Z Entering 'third_party/pybind11' 2025-09-07T14:36:37.2804447Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2840519Z Entering 'third_party/python-peachpy' 2025-09-07T14:36:37.2869058Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2906560Z Entering 'third_party/sleef' 2025-09-07T14:36:37.2934734Z http.https://github.com/.extraheader 2025-09-07T14:36:37.2970780Z Entering 'third_party/tensorpipe' 2025-09-07T14:36:37.2997987Z http.https://github.com/.extraheader 2025-09-07T14:36:37.3033505Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T14:36:37.3059491Z http.https://github.com/.extraheader 2025-09-07T14:36:37.3093988Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T14:36:37.3119635Z http.https://github.com/.extraheader 2025-09-07T14:36:37.3154746Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T14:36:37.3180381Z http.https://github.com/.extraheader 2025-09-07T14:36:37.3215482Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T14:36:37.3241265Z http.https://github.com/.extraheader 2025-09-07T14:36:37.3276030Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T14:36:37.3302341Z http.https://github.com/.extraheader 2025-09-07T14:36:37.3483768Z Post job cleanup. 2025-09-07T14:36:37.4379784Z [command]/usr/bin/git version 2025-09-07T14:36:37.4417490Z git version 2.50.1 2025-09-07T14:36:37.4456242Z Temporarily overriding HOME='/home/charlie/_work/_temp/ba16e8a8-757f-48c4-9a95-497d2e5fdf29' before making global git config changes 2025-09-07T14:36:37.4456949Z Adding repository directory to the temporary git global config as a safe directory 2025-09-07T14:36:37.4461210Z [command]/usr/bin/git config --global --add safe.directory /home/charlie/_work/pytorch/pytorch 2025-09-07T14:36:37.4496071Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-09-07T14:36:37.4539337Z [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' || :" 2025-09-07T14:36:37.4809281Z Entering 'android/libs/fbjni' 2025-09-07T14:36:37.4860635Z Entering 'third_party/FP16' 2025-09-07T14:36:37.4908710Z Entering 'third_party/FXdiv' 2025-09-07T14:36:37.4956604Z Entering 'third_party/NNPACK' 2025-09-07T14:36:37.5005712Z Entering 'third_party/NVTX' 2025-09-07T14:36:37.5058492Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T14:36:37.5107408Z Entering 'third_party/XNNPACK' 2025-09-07T14:36:37.5169950Z Entering 'third_party/aiter' 2025-09-07T14:36:37.5219412Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T14:36:37.5277479Z Entering 'third_party/benchmark' 2025-09-07T14:36:37.5328295Z Entering 'third_party/composable_kernel' 2025-09-07T14:36:37.5386023Z Entering 'third_party/cpp-httplib' 2025-09-07T14:36:37.5436352Z Entering 'third_party/cpuinfo' 2025-09-07T14:36:37.5486206Z Entering 'third_party/cudnn_frontend' 2025-09-07T14:36:37.5536087Z Entering 'third_party/cutlass' 2025-09-07T14:36:37.5595026Z Entering 'third_party/fbgemm' 2025-09-07T14:36:37.5646146Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T14:36:37.5693709Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T14:36:37.5747784Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T14:36:37.5795274Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T14:36:37.5850663Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T14:36:37.5897864Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T14:36:37.5944377Z Entering 'third_party/fbgemm/external/json' 2025-09-07T14:36:37.5995833Z Entering 'third_party/flash-attention' 2025-09-07T14:36:37.6046702Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T14:36:37.6100194Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T14:36:37.6157004Z Entering 'third_party/flatbuffers' 2025-09-07T14:36:37.6208689Z Entering 'third_party/fmt' 2025-09-07T14:36:37.6257515Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T14:36:37.6307493Z Entering 'third_party/gloo' 2025-09-07T14:36:37.6357750Z Entering 'third_party/googletest' 2025-09-07T14:36:37.6409189Z Entering 'third_party/ideep' 2025-09-07T14:36:37.6456922Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T14:36:37.6512306Z Entering 'third_party/ittapi' 2025-09-07T14:36:37.6561301Z Entering 'third_party/kineto' 2025-09-07T14:36:37.6609240Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T14:36:37.6655888Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T14:36:37.6705257Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T14:36:37.6753663Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T14:36:37.6801333Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T14:36:37.6846783Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 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2025-09-07T14:36:37.7506320Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T14:36:37.7553608Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T14:36:37.7600435Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T14:36:37.7646898Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T14:36:37.7694985Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T14:36:37.7741336Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T14:36:37.7787759Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T14:36:37.7833243Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T14:36:37.7882519Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T14:36:37.7932709Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T14:36:37.7998935Z Entering 'third_party/pocketfft' 2025-09-07T14:36:37.8047997Z Entering 'third_party/protobuf' 2025-09-07T14:36:37.8099861Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T14:36:37.8146888Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T14:36:37.8197157Z Entering 'third_party/psimd' 2025-09-07T14:36:37.8245916Z Entering 'third_party/pthreadpool' 2025-09-07T14:36:37.8296681Z Entering 'third_party/pybind11' 2025-09-07T14:36:37.8346071Z Entering 'third_party/python-peachpy' 2025-09-07T14:36:37.8406546Z Entering 'third_party/sleef' 2025-09-07T14:36:37.8445312Z Entering 'third_party/tensorpipe' 2025-09-07T14:36:37.8494245Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T14:36:37.8541434Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T14:36:37.8587845Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T14:36:37.8633747Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T14:36:37.8677643Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T14:36:37.8752086Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-09-07T14:36:37.8784405Z [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' || :" 2025-09-07T14:36:37.9047092Z Entering 'android/libs/fbjni' 2025-09-07T14:36:37.9097725Z Entering 'third_party/FP16' 2025-09-07T14:36:37.9146816Z Entering 'third_party/FXdiv' 2025-09-07T14:36:37.9195181Z Entering 'third_party/NNPACK' 2025-09-07T14:36:37.9243997Z Entering 'third_party/NVTX' 2025-09-07T14:36:37.9293794Z Entering 'third_party/VulkanMemoryAllocator' 2025-09-07T14:36:37.9342739Z Entering 'third_party/XNNPACK' 2025-09-07T14:36:37.9404788Z Entering 'third_party/aiter' 2025-09-07T14:36:37.9454811Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-09-07T14:36:37.9512022Z Entering 'third_party/benchmark' 2025-09-07T14:36:37.9563272Z Entering 'third_party/composable_kernel' 2025-09-07T14:36:37.9621254Z Entering 'third_party/cpp-httplib' 2025-09-07T14:36:37.9669606Z Entering 'third_party/cpuinfo' 2025-09-07T14:36:37.9719755Z Entering 'third_party/cudnn_frontend' 2025-09-07T14:36:37.9770349Z Entering 'third_party/cutlass' 2025-09-07T14:36:37.9828557Z Entering 'third_party/fbgemm' 2025-09-07T14:36:37.9879919Z Entering 'third_party/fbgemm/external/asmjit' 2025-09-07T14:36:37.9926740Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-09-07T14:36:37.9981828Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-09-07T14:36:38.0029826Z Entering 'third_party/fbgemm/external/cutlass' 2025-09-07T14:36:38.0086355Z Entering 'third_party/fbgemm/external/googletest' 2025-09-07T14:36:38.0133791Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-09-07T14:36:38.0180594Z Entering 'third_party/fbgemm/external/json' 2025-09-07T14:36:38.0231825Z Entering 'third_party/flash-attention' 2025-09-07T14:36:38.0283554Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-09-07T14:36:38.0337919Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-09-07T14:36:38.0395345Z Entering 'third_party/flatbuffers' 2025-09-07T14:36:38.0448475Z Entering 'third_party/fmt' 2025-09-07T14:36:38.0498578Z Entering 'third_party/gemmlowp/gemmlowp' 2025-09-07T14:36:38.0547783Z Entering 'third_party/gloo' 2025-09-07T14:36:38.0597147Z Entering 'third_party/googletest' 2025-09-07T14:36:38.0648188Z Entering 'third_party/ideep' 2025-09-07T14:36:38.0695165Z Entering 'third_party/ideep/mkl-dnn' 2025-09-07T14:36:38.0751453Z Entering 'third_party/ittapi' 2025-09-07T14:36:38.0800802Z Entering 'third_party/kineto' 2025-09-07T14:36:38.0849696Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-09-07T14:36:38.0896148Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-09-07T14:36:38.0946485Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-09-07T14:36:38.0995106Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-09-07T14:36:38.1043791Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-09-07T14:36:38.1090586Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-09-07T14:36:38.1141855Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-09-07T14:36:38.1191881Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-09-07T14:36:38.1241530Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-09-07T14:36:38.1289968Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-09-07T14:36:38.1342349Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-09-07T14:36:38.1389219Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-09-07T14:36:38.1439996Z Entering 'third_party/kleidiai' 2025-09-07T14:36:38.1490324Z Entering 'third_party/mimalloc' 2025-09-07T14:36:38.1539767Z Entering 'third_party/nlohmann' 2025-09-07T14:36:38.1589745Z Entering 'third_party/onnx' 2025-09-07T14:36:38.1653590Z Entering 'third_party/onnx/third_party/pybind11' 2025-09-07T14:36:38.1707984Z Entering 'third_party/opentelemetry-cpp' 2025-09-07T14:36:38.1759330Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-09-07T14:36:38.1807033Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-09-07T14:36:38.1855158Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-09-07T14:36:38.1902412Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-09-07T14:36:38.1950588Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-09-07T14:36:38.1997393Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-09-07T14:36:38.2044546Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-09-07T14:36:38.2091506Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-09-07T14:36:38.2142047Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-09-07T14:36:38.2193311Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-09-07T14:36:38.2260116Z Entering 'third_party/pocketfft' 2025-09-07T14:36:38.2310473Z Entering 'third_party/protobuf' 2025-09-07T14:36:38.2361865Z Entering 'third_party/protobuf/third_party/benchmark' 2025-09-07T14:36:38.2408869Z Entering 'third_party/protobuf/third_party/googletest' 2025-09-07T14:36:38.2459136Z Entering 'third_party/psimd' 2025-09-07T14:36:38.2509165Z Entering 'third_party/pthreadpool' 2025-09-07T14:36:38.2559013Z Entering 'third_party/pybind11' 2025-09-07T14:36:38.2608531Z Entering 'third_party/python-peachpy' 2025-09-07T14:36:38.2658343Z Entering 'third_party/sleef' 2025-09-07T14:36:38.2708382Z Entering 'third_party/tensorpipe' 2025-09-07T14:36:38.2758198Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-09-07T14:36:38.2806246Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-09-07T14:36:38.2854242Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-09-07T14:36:38.2900111Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-09-07T14:36:38.2945785Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-09-07T14:36:38.3152100Z Cleaning up orphan processes