2025-09-07T07:35:19.2535693Z Current runner version: '2.328.0'
2025-09-07T07:35:19.2540550Z Runner name: 'i-04e43c8796a0bfd2e'
2025-09-07T07:35:19.2541377Z Runner group name: 'default'
2025-09-07T07:35:19.2542099Z Machine name: 'ip-10-0-74-111'
2025-09-07T07:35:19.2544240Z ##[group]GITHUB_TOKEN Permissions
2025-09-07T07:35:19.2546347Z Contents: read
2025-09-07T07:35:19.2546792Z Metadata: read
2025-09-07T07:35:19.2547210Z ##[endgroup]
2025-09-07T07:35:19.2548851Z Secret source: Actions
2025-09-07T07:35:19.2549425Z Prepare workflow directory
2025-09-07T07:35:19.2934738Z Prepare all required actions
2025-09-07T07:35:19.2963778Z Getting action download info
2025-09-07T07:35:19.5960604Z Download action repository 'pytorch/test-infra@main' (SHA:548a4bc624d43a01cdf165a63b041f0ae014ddbd)
2025-09-07T07:35:20.7001911Z Download action repository 'pytorch/pytorch@main' (SHA:93fb23d6fae7c4e82c4239a1033e522088742634)
2025-09-07T07:35:34.4443291Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065)
2025-09-07T07:35:34.7166353Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722)
2025-09-07T07:35:34.8825402Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076)
2025-09-07T07:35:35.0157065Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a)
2025-09-07T07:35:35.2657554Z Getting action download info
2025-09-07T07:35:35.3655324Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955)
2025-09-07T07:35:35.5722683Z Getting action download info
2025-09-07T07:35:35.6751389Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e)
2025-09-07T07:35:35.8304055Z Getting action download info
2025-09-07T07:35:35.9407629Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482)
2025-09-07T07:35:36.0824456Z Getting action download info
2025-09-07T07:35:36.1976894Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (93fb23d6fae7c4e82c4239a1033e522088742634)
2025-09-07T07:35:36.1979743Z ##[group] Inputs
2025-09-07T07:35:36.1980013Z   build-environment: linux-jammy-py3.9-gcc11-build
2025-09-07T07:35:36.1982617Z   test-matrix: {"include": [{"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 1, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 2, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 3, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 1, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 2, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 3, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 4, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 5, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 1, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 2, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 3, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 4, "num_shards": 4, "runner": "linux.24xlarge.amd"}]}
2025-09-07T07:35:36.1986000Z   docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:35:36.1986723Z   sync-tag: 
2025-09-07T07:35:36.1987400Z   timeout-minutes: 720
2025-09-07T07:35:36.1987573Z   use-gha: 
2025-09-07T07:35:36.1987965Z   dashboard-tag: training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true
2025-09-07T07:35:36.1988408Z   s3-bucket: gha-artifacts
2025-09-07T07:35:36.1988584Z   aws-role-to-assume: 
2025-09-07T07:35:36.1988974Z   disable-monitor: false
2025-09-07T07:35:36.1989184Z   monitor-log-interval: 15
2025-09-07T07:35:36.1989382Z   monitor-data-collect-interval: 4
2025-09-07T07:35:36.1989588Z ##[endgroup]
2025-09-07T07:35:36.1989919Z Complete job name: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:35:36.3085621Z A job started hook has been configured by the self-hosted runner administrator
2025-09-07T07:35:36.3164737Z ##[group]Run '/home/ec2-user/runner-scripts/before_job.sh'
2025-09-07T07:35:36.3173573Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:35:36.3174077Z ##[endgroup]
2025-09-07T07:35:37.5561704Z Runner Type: linux.24xlarge.amd
2025-09-07T07:35:37.5562145Z Instance Type: m7a.24xlarge
2025-09-07T07:35:37.5562337Z AMI Name: unknown
2025-09-07T07:35:37.5602873Z AMI ID: ami-05ffe3c48a9991133
2025-09-07T07:35:41.7955158Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main
2025-09-07T07:35:41.7955461Z with:
2025-09-07T07:35:41.7955944Z   github-secret: ***
2025-09-07T07:35:41.7956401Z   instructions: All testing is done inside the container, to start an interactive session run:
  docker exec -it $(docker container ps --format '{{.ID}}') bash

2025-09-07T07:35:41.7956882Z   activate-with-label: false
2025-09-07T07:35:41.7957070Z   label: with-ssh
2025-09-07T07:35:41.7957236Z   remove-existing-keys: true
2025-09-07T07:35:41.7957409Z   fail-silently: true
2025-09-07T07:35:41.7957574Z env:
2025-09-07T07:35:41.7957725Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:35:41.7957955Z ##[endgroup]
2025-09-07T07:35:41.9114355Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info.
2025-09-07T07:35:41.9115040Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys
2025-09-07T07:35:41.9283634Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main
2025-09-07T07:35:41.9284135Z with:
2025-09-07T07:35:41.9284380Z   no-sudo: true
2025-09-07T07:35:41.9284658Z   submodules: recursive
2025-09-07T07:35:41.9284919Z   fetch-depth: 0
2025-09-07T07:35:41.9285149Z env:
2025-09-07T07:35:41.9285420Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:35:41.9315954Z ##[endgroup]
2025-09-07T07:35:41.9375081Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-09-07T07:35:41.9375702Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-09-07T07:35:41.9387164Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:35:41.9387437Z env:
2025-09-07T07:35:41.9387625Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:35:41.9387849Z ##[endgroup]
2025-09-07T07:35:41.9473428Z ##[group]Run # Use all available CPUs for fetching
2025-09-07T07:35:41.9473754Z # Use all available CPUs for fetching
2025-09-07T07:35:41.9473986Z cd "${GITHUB_WORKSPACE}"
2025-09-07T07:35:41.9474229Z git config --global fetch.parallel 0
2025-09-07T07:35:41.9474494Z git config --global submodule.fetchJobs 0
2025-09-07T07:35:41.9474731Z 
2025-09-07T07:35:41.9475311Z # Clean workspace. The default checkout action should also do this, but
2025-09-07T07:35:41.9475615Z # do it here as well just in case
2025-09-07T07:35:41.9475832Z if [[ -d .git ]]; then
2025-09-07T07:35:41.9476030Z   if [ -z "${NO_SUDO}" ]; then
2025-09-07T07:35:41.9476235Z     sudo git clean -ffdx
2025-09-07T07:35:41.9476426Z   else
2025-09-07T07:35:41.9476794Z     git clean -ffdx
2025-09-07T07:35:41.9476971Z   fi
2025-09-07T07:35:41.9477122Z fi
2025-09-07T07:35:41.9484391Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:35:41.9484657Z env:
2025-09-07T07:35:41.9484814Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:35:41.9484990Z   NO_SUDO: true
2025-09-07T07:35:41.9485227Z ##[endgroup]
2025-09-07T07:35:41.9612166Z ##[group]Run actions/checkout@v4
2025-09-07T07:35:41.9612380Z with:
2025-09-07T07:35:41.9612554Z   ref: 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:35:41.9612767Z   fetch-depth: 0
2025-09-07T07:35:41.9612925Z   submodules: recursive
2025-09-07T07:35:41.9613105Z   show-progress: false
2025-09-07T07:35:41.9613290Z   repository: pytorch/pytorch
2025-09-07T07:35:41.9613551Z   token: ***
2025-09-07T07:35:41.9613704Z   ssh-strict: true
2025-09-07T07:35:41.9613861Z   ssh-user: git
2025-09-07T07:35:41.9614031Z   persist-credentials: true
2025-09-07T07:35:41.9614210Z   clean: true
2025-09-07T07:35:41.9614403Z   sparse-checkout-cone-mode: true
2025-09-07T07:35:41.9614603Z   fetch-tags: false
2025-09-07T07:35:41.9614767Z   lfs: false
2025-09-07T07:35:41.9614921Z   set-safe-directory: true
2025-09-07T07:35:41.9615111Z env:
2025-09-07T07:35:41.9615261Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:35:41.9615438Z ##[endgroup]
2025-09-07T07:35:42.0492946Z Syncing repository: pytorch/pytorch
2025-09-07T07:35:42.0493946Z ##[group]Getting Git version info
2025-09-07T07:35:42.0494272Z Working directory is '/home/ec2-user/actions-runner/_work/pytorch/pytorch'
2025-09-07T07:35:42.0494740Z [command]/usr/bin/git version
2025-09-07T07:35:42.0701626Z git version 2.47.1
2025-09-07T07:35:42.0722503Z ##[endgroup]
2025-09-07T07:35:42.0730354Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/836a0869-facd-4c56-9266-705aa4a0fecd/.gitconfig'
2025-09-07T07:35:42.0747338Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/836a0869-facd-4c56-9266-705aa4a0fecd' before making global git config changes
2025-09-07T07:35:42.0748019Z Adding repository directory to the temporary git global config as a safe directory
2025-09-07T07:35:42.0751485Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-09-07T07:35:42.0795778Z Deleting the contents of '/home/ec2-user/actions-runner/_work/pytorch/pytorch'
2025-09-07T07:35:42.0798511Z ##[group]Initializing the repository
2025-09-07T07:35:42.0802005Z [command]/usr/bin/git init /home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-09-07T07:35:42.0865398Z hint: Using 'master' as the name for the initial branch. This default branch name
2025-09-07T07:35:42.0865821Z hint: is subject to change. To configure the initial branch name to use in all
2025-09-07T07:35:42.0866203Z hint: of your new repositories, which will suppress this warning, call:
2025-09-07T07:35:42.0866476Z hint:
2025-09-07T07:35:42.0866694Z hint: 	git config --global init.defaultBranch <name>
2025-09-07T07:35:42.0866930Z hint:
2025-09-07T07:35:42.0867150Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and
2025-09-07T07:35:42.0867506Z hint: 'development'. The just-created branch can be renamed via this command:
2025-09-07T07:35:42.0867775Z hint:
2025-09-07T07:35:42.0867923Z hint: 	git branch -m <name>
2025-09-07T07:35:42.0888110Z Initialized empty Git repository in /home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/
2025-09-07T07:35:42.0897792Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch
2025-09-07T07:35:42.0935861Z ##[endgroup]
2025-09-07T07:35:42.0936176Z ##[group]Disabling automatic garbage collection
2025-09-07T07:35:42.0938827Z [command]/usr/bin/git config --local gc.auto 0
2025-09-07T07:35:42.0968384Z ##[endgroup]
2025-09-07T07:35:42.0968653Z ##[group]Setting up auth
2025-09-07T07:35:42.0973520Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand
2025-09-07T07:35:42.0999174Z [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' || :"
2025-09-07T07:35:42.1399942Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader
2025-09-07T07:35:42.1428170Z [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' || :"
2025-09-07T07:35:42.1787172Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic ***
2025-09-07T07:35:42.1843520Z ##[endgroup]
2025-09-07T07:35:42.1843946Z ##[group]Fetching the repository
2025-09-07T07:35:42.1849262Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/*
2025-09-07T07:36:14.0821616Z From https://github.com/pytorch/pytorch
2025-09-07T07:36:14.0822000Z  * [new branch]              160583                      -> origin/160583
2025-09-07T07:36:14.0822463Z  * [new branch]              2.6.0.dev20241004+          -> origin/2.6.0.dev20241004+
2025-09-07T07:36:14.0822809Z  * [new branch]              5addvllmbuild               -> origin/5addvllmbuild
2025-09-07T07:36:14.0823191Z  * [new branch]              AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest
2025-09-07T07:36:14.0823620Z  * [new branch]              HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes
2025-09-07T07:36:14.0824044Z  * [new branch]              ISSUE-154849                -> origin/ISSUE-154849
2025-09-07T07:36:14.0826355Z  * [new branch]              JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops
2025-09-07T07:36:14.0828121Z  * [new branch]              NicoshevSVE128              -> origin/NicoshevSVE128
2025-09-07T07:36:14.0829480Z  * [new branch]              PR-AOTInductorNoneBug       -> origin/PR-AOTInductorNoneBug
2025-09-07T07:36:14.0830804Z  * [new branch]              PR-AOTInductorNoneBugFix    -> origin/PR-AOTInductorNoneBugFix
2025-09-07T07:36:14.0832583Z  * [new branch]              PR-FixConfigsIssue          -> origin/PR-FixConfigsIssue
2025-09-07T07:36:14.0833205Z  * [new branch]              PR-NoneBugFix-viable        -> origin/PR-NoneBugFix-viable
2025-09-07T07:36:14.0834515Z  * [new branch]              PR-ResetToZero              -> origin/PR-ResetToZero
2025-09-07T07:36:14.0835833Z  * [new branch]              Update-Flash-Packaging      -> origin/Update-Flash-Packaging
2025-09-07T07:36:14.0837056Z  * [new branch]              VLA_exp                     -> origin/VLA_exp
2025-09-07T07:36:14.0839238Z  * [new branch]              actually-run-mps-aot-inductor -> origin/actually-run-mps-aot-inductor
2025-09-07T07:36:14.0840508Z  * [new branch]              add-missing-args-normalization -> origin/add-missing-args-normalization
2025-09-07T07:36:14.0841801Z  * [new branch]              add-user-guide-structure    -> origin/add-user-guide-structure
2025-09-07T07:36:14.0843274Z  * [new branch]              add-vllm-nightly-build      -> origin/add-vllm-nightly-build
2025-09-07T07:36:14.0844490Z  * [new branch]              add_compile_benchmarking    -> origin/add_compile_benchmarking
2025-09-07T07:36:14.0845806Z  * [new branch]              addmm-heuristic             -> origin/addmm-heuristic
2025-09-07T07:36:14.0847097Z  * [new branch]              addsimde                    -> origin/addsimde
2025-09-07T07:36:14.0848374Z  * [new branch]              addvllmtest                 -> origin/addvllmtest
2025-09-07T07:36:14.0850228Z  * [new branch]              adi/acl_upgrade             -> origin/adi/acl_upgrade
2025-09-07T07:36:14.0851475Z  * [new branch]              adi/test                    -> origin/adi/test
2025-09-07T07:36:14.0852723Z  * [new branch]              adi/test_bgemm              -> origin/adi/test_bgemm
2025-09-07T07:36:14.0854015Z  * [new branch]              adi/test_fusions            -> origin/adi/test_fusions
2025-09-07T07:36:14.0855101Z  * [new branch]              adi/test_onednn_v3.9        -> origin/adi/test_onednn_v3.9
2025-09-07T07:36:14.0856621Z  * [new branch]              adi/test_presve_change      -> origin/adi/test_presve_change
2025-09-07T07:36:14.0857502Z  * [new branch]              adi/test_timm               -> origin/adi/test_timm
2025-09-07T07:36:14.0859155Z  * [new branch]              adi/testpresve_change       -> origin/adi/testpresve_change
2025-09-07T07:36:14.0861503Z  * [new branch]              aditew01/test/vec_bf16      -> origin/aditew01/test/vec_bf16
2025-09-07T07:36:14.0862963Z  * [new branch]              ah-globalfeedback-hook      -> origin/ah-globalfeedback-hook
2025-09-07T07:36:14.0864168Z  * [new branch]              alt-disable                 -> origin/alt-disable
2025-09-07T07:36:14.0866655Z  * [new branch]              angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files
2025-09-07T07:36:14.0867373Z  * [new branch]              angelayi/aoti_inductor_fx   -> origin/angelayi/aoti_inductor_fx
2025-09-07T07:36:14.0868622Z  * [new branch]              angelayi/benchmark          -> origin/angelayi/benchmark
2025-09-07T07:36:14.0869992Z  * [new branch]              angelayi/benchmark2         -> origin/angelayi/benchmark2
2025-09-07T07:36:14.0871261Z  * [new branch]              angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization
2025-09-07T07:36:14.0872399Z  * [new branch]              angelayi/cpp_loader         -> origin/angelayi/cpp_loader
2025-09-07T07:36:14.0874086Z  * [new branch]              angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph
2025-09-07T07:36:14.0875572Z  * [new branch]              angelayi/customop           -> origin/angelayi/customop
2025-09-07T07:36:14.0877152Z  * [new branch]              angelayi/fake_cache_empty   -> origin/angelayi/fake_cache_empty
2025-09-07T07:36:14.0878481Z  * [new branch]              angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing
2025-09-07T07:36:14.0879670Z  * [new branch]              angelayi/item               -> origin/angelayi/item
2025-09-07T07:36:14.0881056Z  * [new branch]              angelayi/no_so_weight       -> origin/angelayi/no_so_weight
2025-09-07T07:36:14.0882221Z  * [new branch]              angelayi/opoverload         -> origin/angelayi/opoverload
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2025-09-07T07:36:14.7267936Z  * [new branch]              mm_out_dtype_compile        -> origin/mm_out_dtype_compile
2025-09-07T07:36:14.7269205Z  * [new branch]              modify-setupvllm            -> origin/modify-setupvllm
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2025-09-07T07:36:14.7396693Z  * [new branch]              qchip/export-D54134695      -> origin/qchip/export-D54134695
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2025-09-07T07:36:14.7638445Z  * [new branch]              workonoldcommit             -> origin/workonoldcommit
2025-09-07T07:36:14.7639949Z  * [new branch]              wychi-autotune-prune-configs-by-shared-mem -> origin/wychi-autotune-prune-configs-by-shared-mem
2025-09-07T07:36:14.7641554Z  * [new branch]              xmfan/ca_0516               -> origin/xmfan/ca_0516
2025-09-07T07:36:14.7642690Z  * [new branch]              xmfan/ca_1051b93192         -> origin/xmfan/ca_1051b93192
2025-09-07T07:36:14.7643866Z  * [new branch]              xmfan/ca_1a722f62c248391fc4a542e8851a5559aa356ae8 -> origin/xmfan/ca_1a722f62c248391fc4a542e8851a5559aa356ae8
2025-09-07T07:36:14.7644841Z  * [new branch]              xmfan/ca_5a2be192d1         -> origin/xmfan/ca_5a2be192d1
2025-09-07T07:36:14.7645932Z  * [new branch]              xmfan/ca_9d59b516e9         -> origin/xmfan/ca_9d59b516e9
2025-09-07T07:36:14.7647119Z  * [new branch]              xmfan/ca_api                -> origin/xmfan/ca_api
2025-09-07T07:36:14.7648365Z  * [new branch]              xmfan/ca_apr8               -> origin/xmfan/ca_apr8
2025-09-07T07:36:14.7649779Z  * [new branch]              xmfan/ca_base               -> origin/xmfan/ca_base
2025-09-07T07:36:14.7651270Z  * [new branch]              xmfan/ca_cudagraphs         -> origin/xmfan/ca_cudagraphs
2025-09-07T07:36:14.7652544Z  * [new branch]              xmfan/ca_dynamic            -> origin/xmfan/ca_dynamic
2025-09-07T07:36:14.7653711Z  * [new branch]              xmfan/ca_fix_dyn            -> origin/xmfan/ca_fix_dyn
2025-09-07T07:36:14.7654910Z  * [new branch]              xmfan/ca_fix_lowering       -> origin/xmfan/ca_fix_lowering
2025-09-07T07:36:14.7656082Z  * [new branch]              xmfan/ca_fix_polyfills      -> origin/xmfan/ca_fix_polyfills
2025-09-07T07:36:14.7657171Z  * [new branch]              xmfan/ca_jan3               -> origin/xmfan/ca_jan3
2025-09-07T07:36:14.7658406Z  * [new branch]              xmfan/ca_jun18              -> origin/xmfan/ca_jun18
2025-09-07T07:36:14.7659675Z  * [new branch]              xmfan/ca_jun24              -> origin/xmfan/ca_jun24
2025-09-07T07:36:14.7660925Z  * [new branch]              xmfan/ca_mem_base           -> origin/xmfan/ca_mem_base
2025-09-07T07:36:14.7662104Z  * [new branch]              xmfan/ca_mem_fix            -> origin/xmfan/ca_mem_fix
2025-09-07T07:36:14.7663280Z  * [new branch]              xmfan/ca_memory_fix         -> origin/xmfan/ca_memory_fix
2025-09-07T07:36:14.7664508Z  * [new branch]              xmfan/ca_memory_fix_rebased -> origin/xmfan/ca_memory_fix_rebased
2025-09-07T07:36:14.7665826Z  * [new branch]              xmfan/ca_memory_fix_rebased2 -> origin/xmfan/ca_memory_fix_rebased2
2025-09-07T07:36:14.7666937Z  * [new branch]              xmfan/ca_move_to_cuda       -> origin/xmfan/ca_move_to_cuda
2025-09-07T07:36:14.7668133Z  * [new branch]              xmfan/ca_nested             -> origin/xmfan/ca_nested
2025-09-07T07:36:14.7669328Z  * [new branch]              xmfan/ca_overhead           -> origin/xmfan/ca_overhead
2025-09-07T07:36:14.7670530Z  * [new branch]              xmfan/ca_overhead_0eba7e5451 -> origin/xmfan/ca_overhead_0eba7e5451
2025-09-07T07:36:14.7671739Z  * [new branch]              xmfan/ca_scalar             -> origin/xmfan/ca_scalar
2025-09-07T07:36:14.7673407Z  * [new branch]              xmfan/ca_subclass_mem_fix   -> origin/xmfan/ca_subclass_mem_fix
2025-09-07T07:36:14.7674581Z  * [new branch]              xmfan/ca_warm_mem           -> origin/xmfan/ca_warm_mem
2025-09-07T07:36:14.7675791Z  * [new branch]              xmfan/ca_warm_mem_base      -> origin/xmfan/ca_warm_mem_base
2025-09-07T07:36:14.7676966Z  * [new branch]              xmfan/cacu_jun18            -> origin/xmfan/cacu_jun18
2025-09-07T07:36:14.7678119Z  * [new branch]              xmfan/cacu_jun19            -> origin/xmfan/cacu_jun19
2025-09-07T07:36:14.7679467Z  * [new branch]              xmfan/cacu_jun4             -> origin/xmfan/cacu_jun4
2025-09-07T07:36:14.7680728Z  * [new branch]              xmfan/cacu_may27            -> origin/xmfan/cacu_may27
2025-09-07T07:36:14.7682036Z  * [new branch]              xmfan/disable_duck_shape    -> origin/xmfan/disable_duck_shape
2025-09-07T07:36:14.7683259Z  * [new branch]              xmfan/fca_cpp_node_passthrough -> origin/xmfan/fca_cpp_node_passthrough
2025-09-07T07:36:14.7684412Z  * [new branch]              xmfan/issue_123374          -> origin/xmfan/issue_123374
2025-09-07T07:36:14.7685764Z  * [new branch]              xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9
2025-09-07T07:36:14.7686975Z  * [new branch]              xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9
2025-09-07T07:36:14.7688018Z  * [new branch]              xmfan/segfault_test         -> origin/xmfan/segfault_test
2025-09-07T07:36:14.7689217Z  * [new branch]              xmfan/single_step           -> origin/xmfan/single_step
2025-09-07T07:36:14.7690390Z  * [new branch]              xmfan/sth_0829              -> origin/xmfan/sth_0829
2025-09-07T07:36:14.7691735Z  * [new branch]              xmfan/test                  -> origin/xmfan/test
2025-09-07T07:36:14.7693510Z  * [new branch]              yguo/debug-0226-constexpr   -> origin/yguo/debug-0226-constexpr
2025-09-07T07:36:14.7694619Z  * [new branch]              yguo/new_latest_changes     -> origin/yguo/new_latest_changes
2025-09-07T07:36:14.7695763Z  * [new branch]              yguo/patch_constexpr_changes -> origin/yguo/patch_constexpr_changes
2025-09-07T07:36:14.7697424Z  * [new branch]              yihan_quantization          -> origin/yihan_quantization
2025-09-07T07:36:14.7701715Z  * [new branch]              yiming/add_jit_trace_benchmark -> origin/yiming/add_jit_trace_benchmark
2025-09-07T07:36:14.7702896Z  * [new branch]              yiming/add_nativert_benchmark -> origin/yiming/add_nativert_benchmark
2025-09-07T07:36:14.7703973Z  * [new branch]              yiming/bootcamp             -> origin/yiming/bootcamp
2025-09-07T07:36:14.7705737Z  * [new branch]              zainr/canary-test           -> origin/zainr/canary-test
2025-09-07T07:36:14.7707102Z  * [new branch]              zainr/cleanup-gh-runners    -> origin/zainr/cleanup-gh-runners
2025-09-07T07:36:14.7708160Z  * [new branch]              zainr/git-push-v2           -> origin/zainr/git-push-v2
2025-09-07T07:36:14.7709283Z  * [new branch]              zainr/pull-migration-c      -> origin/zainr/pull-migration-c
2025-09-07T07:36:14.7710408Z  * [new branch]              zainr/test                  -> origin/zainr/test
2025-09-07T07:36:14.7711805Z  * [new branch]              zainr/test2                 -> origin/zainr/test2
2025-09-07T07:36:14.7712749Z  * [new branch]              zainr/unstable              -> origin/zainr/unstable
2025-09-07T07:36:14.7714033Z  * [new branch]              zainr/unstable-xla          -> origin/zainr/unstable-xla
2025-09-07T07:36:14.7715451Z  * [new branch]              zasdfgbnm-patch-3           -> origin/zasdfgbnm-patch-3
2025-09-07T07:36:14.7716715Z  * [new branch]              zb2p                        -> origin/zb2p
2025-09-07T07:36:14.7718020Z  * [new branch]              zero_grad_optimization      -> origin/zero_grad_optimization
2025-09-07T07:36:14.7719350Z  * [new branch]              zeros-and-scatter-part2     -> origin/zeros-and-scatter-part2
2025-09-07T07:36:14.7721449Z  * [new branch]              zhxchen17/scratch/0         -> origin/zhxchen17/scratch/0
2025-09-07T07:36:14.7723241Z  * [new branch]              zhxhcen17/moodycamel        -> origin/zhxhcen17/moodycamel
2025-09-07T07:36:14.7724960Z  * [new branch]              zxiiro/main                 -> origin/zxiiro/main
2025-09-07T07:36:14.7726161Z  * [new tag]                 bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug
2025-09-07T07:36:14.7727269Z  * [new tag]                 ci/binaries/77164           -> ci/binaries/77164
2025-09-07T07:36:14.7728510Z  * [new tag]                 ciflow/binaries/156049      -> ciflow/binaries/156049
2025-09-07T07:36:14.7729305Z  * [new tag]                 ciflow/binaries/156712      -> ciflow/binaries/156712
2025-09-07T07:36:14.7730098Z  * [new tag]                 ciflow/binaries/157432      -> ciflow/binaries/157432
2025-09-07T07:36:14.7730927Z  * [new tag]                 ciflow/binaries/157685      -> ciflow/binaries/157685
2025-09-07T07:36:14.7731680Z  * [new tag]                 ciflow/binaries/157689      -> ciflow/binaries/157689
2025-09-07T07:36:14.7732476Z  * [new tag]                 ciflow/binaries/158104      -> ciflow/binaries/158104
2025-09-07T07:36:14.7733375Z  * [new tag]                 ciflow/binaries/160229      -> ciflow/binaries/160229
2025-09-07T07:36:14.7734246Z  * [new tag]                 ciflow/binaries/160720      -> ciflow/binaries/160720
2025-09-07T07:36:14.7735483Z  * [new tag]                 ciflow/binaries/162080      -> ciflow/binaries/162080
2025-09-07T07:36:14.7736273Z  * [new tag]                 ciflow/binaries/162329      -> ciflow/binaries/162329
2025-09-07T07:36:14.7737315Z  * [new tag]                 ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049
2025-09-07T07:36:14.7738059Z  * [new tag]                 ciflow/binaries_libtorch/156711 -> ciflow/binaries_libtorch/156711
2025-09-07T07:36:14.7738866Z  * [new tag]                 ciflow/binaries_libtorch/157432 -> ciflow/binaries_libtorch/157432
2025-09-07T07:36:14.7739807Z  * [new tag]                 ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049
2025-09-07T07:36:14.7740652Z  * [new tag]                 ciflow/binaries_wheel/156711 -> ciflow/binaries_wheel/156711
2025-09-07T07:36:14.7741322Z  * [new tag]                 ciflow/binaries_wheel/157432 -> ciflow/binaries_wheel/157432
2025-09-07T07:36:14.7742129Z  * [new tag]                 ciflow/binaries_wheel/162136 -> ciflow/binaries_wheel/162136
2025-09-07T07:36:14.7742988Z  * [new tag]                 ciflow/binaries_wheel/162252 -> ciflow/binaries_wheel/162252
2025-09-07T07:36:14.7743796Z  * [new tag]                 ciflow/binaries_wheel/162325 -> ciflow/binaries_wheel/162325
2025-09-07T07:36:14.7744856Z  * [new tag]                 ciflow/h100-distributed/156703 -> ciflow/h100-distributed/156703
2025-09-07T07:36:14.7745967Z  * [new tag]                 ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635
2025-09-07T07:36:14.7746774Z  * [new tag]                 ciflow/h100-symm-mem/161984 -> ciflow/h100-symm-mem/161984
2025-09-07T07:36:14.7747985Z  * [new tag]                 ciflow/h100-symm-mem/162003 -> ciflow/h100-symm-mem/162003
2025-09-07T07:36:14.7748853Z  * [new tag]                 ciflow/h100-symm-mem/162011 -> ciflow/h100-symm-mem/162011
2025-09-07T07:36:14.7749525Z  * [new tag]                 ciflow/h100-symm-mem/162026 -> ciflow/h100-symm-mem/162026
2025-09-07T07:36:14.7750348Z  * [new tag]                 ciflow/h100-symm-mem/162033 -> ciflow/h100-symm-mem/162033
2025-09-07T07:36:14.7751196Z  * [new tag]                 ciflow/h100-symm-mem/162040 -> ciflow/h100-symm-mem/162040
2025-09-07T07:36:14.7751986Z  * [new tag]                 ciflow/h100-symm-mem/162041 -> ciflow/h100-symm-mem/162041
2025-09-07T07:36:14.7753010Z  * [new tag]                 ciflow/h100-symm-mem/162142 -> ciflow/h100-symm-mem/162142
2025-09-07T07:36:14.7753529Z  * [new tag]                 ciflow/h100-symm-mem/162150 -> ciflow/h100-symm-mem/162150
2025-09-07T07:36:14.7754360Z  * [new tag]                 ciflow/h100-symm-mem/162243 -> ciflow/h100-symm-mem/162243
2025-09-07T07:36:14.7755422Z  * [new tag]                 ciflow/h100-symm-mem/162320 -> ciflow/h100-symm-mem/162320
2025-09-07T07:36:14.7756580Z  * [new tag]                 ciflow/h100/159158          -> ciflow/h100/159158
2025-09-07T07:36:14.7757790Z  * [new tag]                 ciflow/h100/160480          -> ciflow/h100/160480
2025-09-07T07:36:14.7758663Z  * [new tag]                 ciflow/h100/161749          -> ciflow/h100/161749
2025-09-07T07:36:14.7759560Z  * [new tag]                 ciflow/h100/162022          -> ciflow/h100/162022
2025-09-07T07:36:14.7760260Z  * [new tag]                 ciflow/h100/162278          -> ciflow/h100/162278
2025-09-07T07:36:14.7761645Z  * [new tag]                 ciflow/inductor-perf-test-nightly-rocm/156592 -> ciflow/inductor-perf-test-nightly-rocm/156592
2025-09-07T07:36:14.7762897Z  * [new tag]                 ciflow/inductor-perf-test-nightly/156592 -> ciflow/inductor-perf-test-nightly/156592
2025-09-07T07:36:14.7763991Z  * [new tag]                 ciflow/inductor-periodic/162063 -> ciflow/inductor-periodic/162063
2025-09-07T07:36:14.7764715Z  * [new tag]                 ciflow/inductor-periodic/162227 -> ciflow/inductor-periodic/162227
2025-09-07T07:36:14.7765666Z  * [new tag]                 ciflow/inductor-periodic/162323 -> ciflow/inductor-periodic/162323
2025-09-07T07:36:14.7766746Z  * [new tag]                 ciflow/inductor-rocm/154170 -> ciflow/inductor-rocm/154170
2025-09-07T07:36:14.7767666Z  * [new tag]                 ciflow/inductor-rocm/159146 -> ciflow/inductor-rocm/159146
2025-09-07T07:36:14.7768394Z  * [new tag]                 ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158
2025-09-07T07:36:14.7769342Z  * [new tag]                 ciflow/inductor-rocm/161715 -> ciflow/inductor-rocm/161715
2025-09-07T07:36:14.7770258Z  * [new tag]                 ciflow/inductor-rocm/162053 -> ciflow/inductor-rocm/162053
2025-09-07T07:36:14.7771216Z  * [new tag]                 ciflow/inductor-rocm/162056 -> ciflow/inductor-rocm/162056
2025-09-07T07:36:14.7772237Z  * [new tag]                 ciflow/inductor/137400      -> ciflow/inductor/137400
2025-09-07T07:36:14.7772940Z  * [new tag]                 ciflow/inductor/148180      -> ciflow/inductor/148180
2025-09-07T07:36:14.7773761Z  * [new tag]                 ciflow/inductor/148328      -> ciflow/inductor/148328
2025-09-07T07:36:14.7774482Z  * [new tag]                 ciflow/inductor/148484      -> ciflow/inductor/148484
2025-09-07T07:36:14.7775391Z  * [new tag]                 ciflow/inductor/148492      -> ciflow/inductor/148492
2025-09-07T07:36:14.7776108Z  * [new tag]                 ciflow/inductor/152624      -> ciflow/inductor/152624
2025-09-07T07:36:14.7777508Z  * [new tag]                 ciflow/inductor/154694      -> ciflow/inductor/154694
2025-09-07T07:36:14.7778382Z  * [new tag]                 ciflow/inductor/156049      -> ciflow/inductor/156049
2025-09-07T07:36:14.7779074Z  * [new tag]                 ciflow/inductor/156592      -> ciflow/inductor/156592
2025-09-07T07:36:14.7779787Z  * [new tag]                 ciflow/inductor/157635      -> ciflow/inductor/157635
2025-09-07T07:36:14.7780789Z  * [new tag]                 ciflow/inductor/157685      -> ciflow/inductor/157685
2025-09-07T07:36:14.7781649Z  * [new tag]                 ciflow/inductor/157686      -> ciflow/inductor/157686
2025-09-07T07:36:14.7782711Z  * [new tag]                 ciflow/inductor/157689      -> ciflow/inductor/157689
2025-09-07T07:36:14.7783722Z  * [new tag]                 ciflow/inductor/157699      -> ciflow/inductor/157699
2025-09-07T07:36:14.7784661Z  * [new tag]                 ciflow/inductor/157743      -> ciflow/inductor/157743
2025-09-07T07:36:14.7785660Z  * [new tag]                 ciflow/inductor/157994      -> ciflow/inductor/157994
2025-09-07T07:36:14.7786533Z  * [new tag]                 ciflow/inductor/158091      -> ciflow/inductor/158091
2025-09-07T07:36:14.7787355Z  * [new tag]                 ciflow/inductor/158104      -> ciflow/inductor/158104
2025-09-07T07:36:14.7788292Z  * [new tag]                 ciflow/inductor/158404      -> ciflow/inductor/158404
2025-09-07T07:36:14.7789140Z  * [new tag]                 ciflow/inductor/158647      -> ciflow/inductor/158647
2025-09-07T07:36:14.7790087Z  * [new tag]                 ciflow/inductor/158932      -> ciflow/inductor/158932
2025-09-07T07:36:14.7790908Z  * [new tag]                 ciflow/inductor/159146      -> ciflow/inductor/159146
2025-09-07T07:36:14.7791724Z  * [new tag]                 ciflow/inductor/159158      -> ciflow/inductor/159158
2025-09-07T07:36:14.7792665Z  * [new tag]                 ciflow/inductor/159274      -> ciflow/inductor/159274
2025-09-07T07:36:14.7793495Z  * [new tag]                 ciflow/inductor/159664      -> ciflow/inductor/159664
2025-09-07T07:36:14.7794466Z  * [new tag]                 ciflow/inductor/159778      -> ciflow/inductor/159778
2025-09-07T07:36:14.7795304Z  * [new tag]                 ciflow/inductor/159835      -> ciflow/inductor/159835
2025-09-07T07:36:14.7796320Z  * [new tag]                 ciflow/inductor/159944      -> ciflow/inductor/159944
2025-09-07T07:36:14.7797266Z  * [new tag]                 ciflow/inductor/160161      -> ciflow/inductor/160161
2025-09-07T07:36:14.7798167Z  * [new tag]                 ciflow/inductor/160174      -> ciflow/inductor/160174
2025-09-07T07:36:14.7799343Z  * [new tag]                 ciflow/inductor/160323      -> ciflow/inductor/160323
2025-09-07T07:36:14.7800436Z  * [new tag]                 ciflow/inductor/160324      -> ciflow/inductor/160324
2025-09-07T07:36:14.7801399Z  * [new tag]                 ciflow/inductor/160325      -> ciflow/inductor/160325
2025-09-07T07:36:14.7802581Z  * [new tag]                 ciflow/inductor/160326      -> ciflow/inductor/160326
2025-09-07T07:36:14.7803479Z  * [new tag]                 ciflow/inductor/160327      -> ciflow/inductor/160327
2025-09-07T07:36:14.7804341Z  * [new tag]                 ciflow/inductor/160328      -> ciflow/inductor/160328
2025-09-07T07:36:14.7805321Z  * [new tag]                 ciflow/inductor/160329      -> ciflow/inductor/160329
2025-09-07T07:36:14.7806155Z  * [new tag]                 ciflow/inductor/160480      -> ciflow/inductor/160480
2025-09-07T07:36:14.7807180Z  * [new tag]                 ciflow/inductor/160532      -> ciflow/inductor/160532
2025-09-07T07:36:14.7808503Z  * [new tag]                 ciflow/inductor/160539      -> ciflow/inductor/160539
2025-09-07T07:36:14.7809333Z  * [new tag]                 ciflow/inductor/160580      -> ciflow/inductor/160580
2025-09-07T07:36:14.7810177Z  * [new tag]                 ciflow/inductor/160685      -> ciflow/inductor/160685
2025-09-07T07:36:14.7811010Z  * [new tag]                 ciflow/inductor/160686      -> ciflow/inductor/160686
2025-09-07T07:36:14.7811828Z  * [new tag]                 ciflow/inductor/160687      -> ciflow/inductor/160687
2025-09-07T07:36:14.7812666Z  * [new tag]                 ciflow/inductor/160688      -> ciflow/inductor/160688
2025-09-07T07:36:14.7813471Z  * [new tag]                 ciflow/inductor/160690      -> ciflow/inductor/160690
2025-09-07T07:36:14.7814342Z  * [new tag]                 ciflow/inductor/160706      -> ciflow/inductor/160706
2025-09-07T07:36:14.7815320Z  * [new tag]                 ciflow/inductor/160729      -> ciflow/inductor/160729
2025-09-07T07:36:14.7816036Z  * [new tag]                 ciflow/inductor/160798      -> ciflow/inductor/160798
2025-09-07T07:36:14.7817000Z  * [new tag]                 ciflow/inductor/160836      -> ciflow/inductor/160836
2025-09-07T07:36:14.7817846Z  * [new tag]                 ciflow/inductor/160843      -> ciflow/inductor/160843
2025-09-07T07:36:14.7818880Z  * [new tag]                 ciflow/inductor/160869      -> ciflow/inductor/160869
2025-09-07T07:36:14.7819726Z  * [new tag]                 ciflow/inductor/160920      -> ciflow/inductor/160920
2025-09-07T07:36:14.7820544Z  * [new tag]                 ciflow/inductor/160943      -> ciflow/inductor/160943
2025-09-07T07:36:14.7821391Z  * [new tag]                 ciflow/inductor/161092      -> ciflow/inductor/161092
2025-09-07T07:36:14.7822266Z  * [new tag]                 ciflow/inductor/161093      -> ciflow/inductor/161093
2025-09-07T07:36:14.7823166Z  * [new tag]                 ciflow/inductor/161109      -> ciflow/inductor/161109
2025-09-07T07:36:14.7823989Z  * [new tag]                 ciflow/inductor/161118      -> ciflow/inductor/161118
2025-09-07T07:36:14.7824941Z  * [new tag]                 ciflow/inductor/161178      -> ciflow/inductor/161178
2025-09-07T07:36:14.7825859Z  * [new tag]                 ciflow/inductor/161246      -> ciflow/inductor/161246
2025-09-07T07:36:14.7826736Z  * [new tag]                 ciflow/inductor/161349      -> ciflow/inductor/161349
2025-09-07T07:36:14.7827562Z  * [new tag]                 ciflow/inductor/161350      -> ciflow/inductor/161350
2025-09-07T07:36:14.7828397Z  * [new tag]                 ciflow/inductor/161351      -> ciflow/inductor/161351
2025-09-07T07:36:14.7829312Z  * [new tag]                 ciflow/inductor/161397      -> ciflow/inductor/161397
2025-09-07T07:36:14.7830072Z  * [new tag]                 ciflow/inductor/161404      -> ciflow/inductor/161404
2025-09-07T07:36:14.7830943Z  * [new tag]                 ciflow/inductor/161405      -> ciflow/inductor/161405
2025-09-07T07:36:14.7831836Z  * [new tag]                 ciflow/inductor/161406      -> ciflow/inductor/161406
2025-09-07T07:36:14.7832831Z  * [new tag]                 ciflow/inductor/161410      -> ciflow/inductor/161410
2025-09-07T07:36:14.7833725Z  * [new tag]                 ciflow/inductor/161414      -> ciflow/inductor/161414
2025-09-07T07:36:14.7834798Z  * [new tag]                 ciflow/inductor/161442      -> ciflow/inductor/161442
2025-09-07T07:36:14.7836062Z  * [new tag]                 ciflow/inductor/161458      -> ciflow/inductor/161458
2025-09-07T07:36:14.7836890Z  * [new tag]                 ciflow/inductor/161468      -> ciflow/inductor/161468
2025-09-07T07:36:14.7837740Z  * [new tag]                 ciflow/inductor/161469      -> ciflow/inductor/161469
2025-09-07T07:36:14.7838663Z  * [new tag]                 ciflow/inductor/161485      -> ciflow/inductor/161485
2025-09-07T07:36:14.7839487Z  * [new tag]                 ciflow/inductor/161499      -> ciflow/inductor/161499
2025-09-07T07:36:14.7840309Z  * [new tag]                 ciflow/inductor/161534      -> ciflow/inductor/161534
2025-09-07T07:36:14.7841144Z  * [new tag]                 ciflow/inductor/161595      -> ciflow/inductor/161595
2025-09-07T07:36:14.7841967Z  * [new tag]                 ciflow/inductor/161596      -> ciflow/inductor/161596
2025-09-07T07:36:14.7843168Z  * [new tag]                 ciflow/inductor/161630      -> ciflow/inductor/161630
2025-09-07T07:36:14.7844030Z  * [new tag]                 ciflow/inductor/161667      -> ciflow/inductor/161667
2025-09-07T07:36:14.7844842Z  * [new tag]                 ciflow/inductor/161670      -> ciflow/inductor/161670
2025-09-07T07:36:14.7845677Z  * [new tag]                 ciflow/inductor/161673      -> ciflow/inductor/161673
2025-09-07T07:36:14.7846511Z  * [new tag]                 ciflow/inductor/161674      -> ciflow/inductor/161674
2025-09-07T07:36:14.7847638Z  * [new tag]                 ciflow/inductor/161675      -> ciflow/inductor/161675
2025-09-07T07:36:14.7848314Z  * [new tag]                 ciflow/inductor/161693      -> ciflow/inductor/161693
2025-09-07T07:36:14.7849200Z  * [new tag]                 ciflow/inductor/161695      -> ciflow/inductor/161695
2025-09-07T07:36:14.7850017Z  * [new tag]                 ciflow/inductor/161715      -> ciflow/inductor/161715
2025-09-07T07:36:14.7850838Z  * [new tag]                 ciflow/inductor/161730      -> ciflow/inductor/161730
2025-09-07T07:36:14.7851679Z  * [new tag]                 ciflow/inductor/161732      -> ciflow/inductor/161732
2025-09-07T07:36:14.7852592Z  * [new tag]                 ciflow/inductor/161744      -> ciflow/inductor/161744
2025-09-07T07:36:14.7853442Z  * [new tag]                 ciflow/inductor/161746      -> ciflow/inductor/161746
2025-09-07T07:36:14.7854265Z  * [new tag]                 ciflow/inductor/161747      -> ciflow/inductor/161747
2025-09-07T07:36:14.7855096Z  * [new tag]                 ciflow/inductor/161819      -> ciflow/inductor/161819
2025-09-07T07:36:14.7855935Z  * [new tag]                 ciflow/inductor/161821      -> ciflow/inductor/161821
2025-09-07T07:36:14.7856748Z  * [new tag]                 ciflow/inductor/161828      -> ciflow/inductor/161828
2025-09-07T07:36:14.7857553Z  * [new tag]                 ciflow/inductor/161879      -> ciflow/inductor/161879
2025-09-07T07:36:14.7858382Z  * [new tag]                 ciflow/inductor/161880      -> ciflow/inductor/161880
2025-09-07T07:36:14.7859243Z  * [new tag]                 ciflow/inductor/161881      -> ciflow/inductor/161881
2025-09-07T07:36:14.7860178Z  * [new tag]                 ciflow/inductor/161907      -> ciflow/inductor/161907
2025-09-07T07:36:14.7861037Z  * [new tag]                 ciflow/inductor/161914      -> ciflow/inductor/161914
2025-09-07T07:36:14.7862028Z  * [new tag]                 ciflow/inductor/161924      -> ciflow/inductor/161924
2025-09-07T07:36:14.7862968Z  * [new tag]                 ciflow/inductor/161936      -> ciflow/inductor/161936
2025-09-07T07:36:14.7863777Z  * [new tag]                 ciflow/inductor/161938      -> ciflow/inductor/161938
2025-09-07T07:36:14.7864642Z  * [new tag]                 ciflow/inductor/161939      -> ciflow/inductor/161939
2025-09-07T07:36:14.7865458Z  * [new tag]                 ciflow/inductor/161940      -> ciflow/inductor/161940
2025-09-07T07:36:14.7866443Z  * [new tag]                 ciflow/inductor/161955      -> ciflow/inductor/161955
2025-09-07T07:36:14.7867254Z  * [new tag]                 ciflow/inductor/161957      -> ciflow/inductor/161957
2025-09-07T07:36:14.7868078Z  * [new tag]                 ciflow/inductor/161975      -> ciflow/inductor/161975
2025-09-07T07:36:14.7868903Z  * [new tag]                 ciflow/inductor/161977      -> ciflow/inductor/161977
2025-09-07T07:36:14.7869758Z  * [new tag]                 ciflow/inductor/161978      -> ciflow/inductor/161978
2025-09-07T07:36:14.7870587Z  * [new tag]                 ciflow/inductor/161979      -> ciflow/inductor/161979
2025-09-07T07:36:14.7871409Z  * [new tag]                 ciflow/inductor/161980      -> ciflow/inductor/161980
2025-09-07T07:36:14.7872268Z  * [new tag]                 ciflow/inductor/161988      -> ciflow/inductor/161988
2025-09-07T07:36:14.7873117Z  * [new tag]                 ciflow/inductor/161994      -> ciflow/inductor/161994
2025-09-07T07:36:14.7873917Z  * [new tag]                 ciflow/inductor/162013      -> ciflow/inductor/162013
2025-09-07T07:36:14.7874740Z  * [new tag]                 ciflow/inductor/162014      -> ciflow/inductor/162014
2025-09-07T07:36:14.7875572Z  * [new tag]                 ciflow/inductor/162017      -> ciflow/inductor/162017
2025-09-07T07:36:14.7876420Z  * [new tag]                 ciflow/inductor/162021      -> ciflow/inductor/162021
2025-09-07T07:36:14.7877229Z  * [new tag]                 ciflow/inductor/162023      -> ciflow/inductor/162023
2025-09-07T07:36:14.7878043Z  * [new tag]                 ciflow/inductor/162027      -> ciflow/inductor/162027
2025-09-07T07:36:14.7878928Z  * [new tag]                 ciflow/inductor/162029      -> ciflow/inductor/162029
2025-09-07T07:36:14.7879764Z  * [new tag]                 ciflow/inductor/162030      -> ciflow/inductor/162030
2025-09-07T07:36:14.7880551Z  * [new tag]                 ciflow/inductor/162031      -> ciflow/inductor/162031
2025-09-07T07:36:14.7881391Z  * [new tag]                 ciflow/inductor/162033      -> ciflow/inductor/162033
2025-09-07T07:36:14.7882404Z  * [new tag]                 ciflow/inductor/162052      -> ciflow/inductor/162052
2025-09-07T07:36:14.7883206Z  * [new tag]                 ciflow/inductor/162053      -> ciflow/inductor/162053
2025-09-07T07:36:14.7884041Z  * [new tag]                 ciflow/inductor/162056      -> ciflow/inductor/162056
2025-09-07T07:36:14.7884862Z  * [new tag]                 ciflow/inductor/162063      -> ciflow/inductor/162063
2025-09-07T07:36:14.7885686Z  * [new tag]                 ciflow/inductor/162066      -> ciflow/inductor/162066
2025-09-07T07:36:14.7886505Z  * [new tag]                 ciflow/inductor/162068      -> ciflow/inductor/162068
2025-09-07T07:36:14.7887527Z  * [new tag]                 ciflow/inductor/162081      -> ciflow/inductor/162081
2025-09-07T07:36:14.7888378Z  * [new tag]                 ciflow/inductor/162088      -> ciflow/inductor/162088
2025-09-07T07:36:14.7889291Z  * [new tag]                 ciflow/inductor/162089      -> ciflow/inductor/162089
2025-09-07T07:36:14.7890255Z  * [new tag]                 ciflow/inductor/162094      -> ciflow/inductor/162094
2025-09-07T07:36:14.7891514Z  * [new tag]                 ciflow/inductor/162098      -> ciflow/inductor/162098
2025-09-07T07:36:14.7892337Z  * [new tag]                 ciflow/inductor/162101      -> ciflow/inductor/162101
2025-09-07T07:36:14.7893188Z  * [new tag]                 ciflow/inductor/162102      -> ciflow/inductor/162102
2025-09-07T07:36:14.7893970Z  * [new tag]                 ciflow/inductor/162104      -> ciflow/inductor/162104
2025-09-07T07:36:14.7894908Z  * [new tag]                 ciflow/inductor/162106      -> ciflow/inductor/162106
2025-09-07T07:36:14.7895729Z  * [new tag]                 ciflow/inductor/162108      -> ciflow/inductor/162108
2025-09-07T07:36:14.7896608Z  * [new tag]                 ciflow/inductor/162126      -> ciflow/inductor/162126
2025-09-07T07:36:14.7897491Z  * [new tag]                 ciflow/inductor/162149      -> ciflow/inductor/162149
2025-09-07T07:36:14.7898357Z  * [new tag]                 ciflow/inductor/162164      -> ciflow/inductor/162164
2025-09-07T07:36:14.7899480Z  * [new tag]                 ciflow/inductor/162166      -> ciflow/inductor/162166
2025-09-07T07:36:14.7900316Z  * [new tag]                 ciflow/inductor/162169      -> ciflow/inductor/162169
2025-09-07T07:36:14.7901141Z  * [new tag]                 ciflow/inductor/162170      -> ciflow/inductor/162170
2025-09-07T07:36:14.7901958Z  * [new tag]                 ciflow/inductor/162171      -> ciflow/inductor/162171
2025-09-07T07:36:14.7902794Z  * [new tag]                 ciflow/inductor/162183      -> ciflow/inductor/162183
2025-09-07T07:36:14.7903619Z  * [new tag]                 ciflow/inductor/162189      -> ciflow/inductor/162189
2025-09-07T07:36:14.7904456Z  * [new tag]                 ciflow/inductor/162190      -> ciflow/inductor/162190
2025-09-07T07:36:14.7905282Z  * [new tag]                 ciflow/inductor/162191      -> ciflow/inductor/162191
2025-09-07T07:36:14.7906202Z  * [new tag]                 ciflow/inductor/162194      -> ciflow/inductor/162194
2025-09-07T07:36:14.7907320Z  * [new tag]                 ciflow/inductor/162200      -> ciflow/inductor/162200
2025-09-07T07:36:14.7908170Z  * [new tag]                 ciflow/inductor/162201      -> ciflow/inductor/162201
2025-09-07T07:36:14.7909021Z  * [new tag]                 ciflow/inductor/162208      -> ciflow/inductor/162208
2025-09-07T07:36:14.7909986Z  * [new tag]                 ciflow/inductor/162211      -> ciflow/inductor/162211
2025-09-07T07:36:14.7910922Z  * [new tag]                 ciflow/inductor/162216      -> ciflow/inductor/162216
2025-09-07T07:36:14.7911589Z  * [new tag]                 ciflow/inductor/162220      -> ciflow/inductor/162220
2025-09-07T07:36:14.7912589Z  * [new tag]                 ciflow/inductor/162222      -> ciflow/inductor/162222
2025-09-07T07:36:14.7913395Z  * [new tag]                 ciflow/inductor/162227      -> ciflow/inductor/162227
2025-09-07T07:36:14.7914247Z  * [new tag]                 ciflow/inductor/162238      -> ciflow/inductor/162238
2025-09-07T07:36:14.7915051Z  * [new tag]                 ciflow/inductor/162239      -> ciflow/inductor/162239
2025-09-07T07:36:14.7915873Z  * [new tag]                 ciflow/inductor/162240      -> ciflow/inductor/162240
2025-09-07T07:36:14.7916714Z  * [new tag]                 ciflow/inductor/162244      -> ciflow/inductor/162244
2025-09-07T07:36:14.7917622Z  * [new tag]                 ciflow/inductor/162245      -> ciflow/inductor/162245
2025-09-07T07:36:14.7918438Z  * [new tag]                 ciflow/inductor/162262      -> ciflow/inductor/162262
2025-09-07T07:36:14.7919264Z  * [new tag]                 ciflow/inductor/162275      -> ciflow/inductor/162275
2025-09-07T07:36:14.7920080Z  * [new tag]                 ciflow/inductor/162278      -> ciflow/inductor/162278
2025-09-07T07:36:14.7920927Z  * [new tag]                 ciflow/inductor/162284      -> ciflow/inductor/162284
2025-09-07T07:36:14.7921765Z  * [new tag]                 ciflow/inductor/162286      -> ciflow/inductor/162286
2025-09-07T07:36:14.7922606Z  * [new tag]                 ciflow/inductor/162288      -> ciflow/inductor/162288
2025-09-07T07:36:14.7923428Z  * [new tag]                 ciflow/inductor/162293      -> ciflow/inductor/162293
2025-09-07T07:36:14.7924297Z  * [new tag]                 ciflow/inductor/162294      -> ciflow/inductor/162294
2025-09-07T07:36:14.7925065Z  * [new tag]                 ciflow/inductor/162295      -> ciflow/inductor/162295
2025-09-07T07:36:14.7925940Z  * [new tag]                 ciflow/inductor/162296      -> ciflow/inductor/162296
2025-09-07T07:36:14.7926755Z  * [new tag]                 ciflow/inductor/162298      -> ciflow/inductor/162298
2025-09-07T07:36:14.7927615Z  * [new tag]                 ciflow/inductor/162307      -> ciflow/inductor/162307
2025-09-07T07:36:14.7928421Z  * [new tag]                 ciflow/inductor/162309      -> ciflow/inductor/162309
2025-09-07T07:36:14.7929244Z  * [new tag]                 ciflow/inductor/162311      -> ciflow/inductor/162311
2025-09-07T07:36:14.7930115Z  * [new tag]                 ciflow/inductor/162312      -> ciflow/inductor/162312
2025-09-07T07:36:14.7930963Z  * [new tag]                 ciflow/inductor/162315      -> ciflow/inductor/162315
2025-09-07T07:36:14.7931767Z  * [new tag]                 ciflow/inductor/162316      -> ciflow/inductor/162316
2025-09-07T07:36:14.7932707Z  * [new tag]                 ciflow/inductor/162318      -> ciflow/inductor/162318
2025-09-07T07:36:14.7933549Z  * [new tag]                 ciflow/inductor/162323      -> ciflow/inductor/162323
2025-09-07T07:36:14.7934419Z  * [new tag]                 ciflow/inductor/162341      -> ciflow/inductor/162341
2025-09-07T07:36:14.7935225Z  * [new tag]                 ciflow/inductor/162345      -> ciflow/inductor/162345
2025-09-07T07:36:14.7936311Z  * [new tag]                 ciflow/inductor/3b9a386     -> ciflow/inductor/3b9a386
2025-09-07T07:36:14.7937285Z  * [new tag]                 ciflow/inductor/3d4b92b     -> ciflow/inductor/3d4b92b
2025-09-07T07:36:14.7938266Z  * [new tag]                 ciflow/inductor/d224ac7     -> ciflow/inductor/d224ac7
2025-09-07T07:36:14.7939318Z  * [new tag]                 ciflow/linux-aarch64/157994 -> ciflow/linux-aarch64/157994
2025-09-07T07:36:14.7940186Z  * [new tag]                 ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737
2025-09-07T07:36:14.7940847Z  * [new tag]                 ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078
2025-09-07T07:36:14.7941913Z  * [new tag]                 ciflow/mps/157553           -> ciflow/mps/157553
2025-09-07T07:36:14.7942806Z  * [new tag]                 ciflow/mps/157635           -> ciflow/mps/157635
2025-09-07T07:36:14.7943474Z  * [new tag]                 ciflow/mps/161988           -> ciflow/mps/161988
2025-09-07T07:36:14.7944315Z  * [new tag]                 ciflow/mps/162108           -> ciflow/mps/162108
2025-09-07T07:36:14.7945149Z  * [new tag]                 ciflow/mps/162153           -> ciflow/mps/162153
2025-09-07T07:36:14.7946063Z  * [new tag]                 ciflow/mps/162281           -> ciflow/mps/162281
2025-09-07T07:36:14.7947109Z  * [new tag]                 ciflow/nightly/156049       -> ciflow/nightly/156049
2025-09-07T07:36:14.7947832Z  * [new tag]                 ciflow/nightly/158104       -> ciflow/nightly/158104
2025-09-07T07:36:14.7948879Z  * [new tag]                 ciflow/op-benchmark/157994  -> ciflow/op-benchmark/157994
2025-09-07T07:36:14.7950076Z  * [new tag]                 ciflow/periodic-rocm-mi300/161529 -> ciflow/periodic-rocm-mi300/161529
2025-09-07T07:36:14.7950818Z  * [new tag]                 ciflow/periodic-rocm-mi300/161715 -> ciflow/periodic-rocm-mi300/161715
2025-09-07T07:36:14.7952150Z  * [new tag]                 ciflow/periodic/054a2fd     -> ciflow/periodic/054a2fd
2025-09-07T07:36:14.7952862Z  * [new tag]                 ciflow/periodic/156703      -> ciflow/periodic/156703
2025-09-07T07:36:14.7953662Z  * [new tag]                 ciflow/periodic/161715      -> ciflow/periodic/161715
2025-09-07T07:36:14.7954495Z  * [new tag]                 ciflow/periodic/162021      -> ciflow/periodic/162021
2025-09-07T07:36:14.7969275Z  * [new tag]                 ciflow/periodic/162323      -> ciflow/periodic/162323
2025-09-07T07:36:14.7969625Z  * [new tag]                 ciflow/periodic/2a6d37d     -> ciflow/periodic/2a6d37d
2025-09-07T07:36:14.7969770Z  * [new tag]                 ciflow/periodic/317eeb8     -> ciflow/periodic/317eeb8
2025-09-07T07:36:14.7969996Z  * [new tag]                 ciflow/periodic/3c32        -> ciflow/periodic/3c32
2025-09-07T07:36:14.7970130Z  * [new tag]                 ciflow/periodic/3e98831     -> ciflow/periodic/3e98831
2025-09-07T07:36:14.7970278Z  * [new tag]                 ciflow/periodic/94512-point -> ciflow/periodic/94512-point
2025-09-07T07:36:14.7970428Z  * [new tag]                 ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519
2025-09-07T07:36:14.7970570Z  * [new tag]                 ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275
2025-09-07T07:36:14.7970714Z  * [new tag]                 ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761
2025-09-07T07:36:14.7970847Z  * [new tag]                 ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12
2025-09-07T07:36:14.7971015Z  * [new tag]                 ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0
2025-09-07T07:36:14.7971145Z  * [new tag]                 ciflow/periodic/sha-ec5b83  -> ciflow/periodic/sha-ec5b83
2025-09-07T07:36:14.7971277Z  * [new tag]                 ciflow/rocm-mi300/154170    -> ciflow/rocm-mi300/154170
2025-09-07T07:36:14.7971393Z  * [new tag]                 ciflow/rocm-mi300/158747    -> ciflow/rocm-mi300/158747
2025-09-07T07:36:14.7971507Z  * [new tag]                 ciflow/rocm-mi300/159146    -> ciflow/rocm-mi300/159146
2025-09-07T07:36:14.7971629Z  * [new tag]                 ciflow/rocm-mi300/159158    -> ciflow/rocm-mi300/159158
2025-09-07T07:36:14.7971743Z  * [new tag]                 ciflow/rocm-mi300/161715    -> ciflow/rocm-mi300/161715
2025-09-07T07:36:14.7971861Z  * [new tag]                 ciflow/rocm-mi300/161957    -> ciflow/rocm-mi300/161957
2025-09-07T07:36:14.7973033Z  * [new tag]                 ciflow/rocm-mi300/162053    -> ciflow/rocm-mi300/162053
2025-09-07T07:36:14.7973800Z  * [new tag]                 ciflow/rocm-mi300/162056    -> ciflow/rocm-mi300/162056
2025-09-07T07:36:14.7974697Z  * [new tag]                 ciflow/rocm-mi300/162112    -> ciflow/rocm-mi300/162112
2025-09-07T07:36:14.7975521Z  * [new tag]                 ciflow/rocm-mi300/162245    -> ciflow/rocm-mi300/162245
2025-09-07T07:36:14.7976261Z  * [new tag]                 ciflow/rocm-mi300/162278    -> ciflow/rocm-mi300/162278
2025-09-07T07:36:14.7977252Z  * [new tag]                 ciflow/rocm-mi300/162288    -> ciflow/rocm-mi300/162288
2025-09-07T07:36:14.7978327Z  * [new tag]                 ciflow/rocm-mi355/162053    -> ciflow/rocm-mi355/162053
2025-09-07T07:36:14.7979351Z  * [new tag]                 ciflow/rocm-mi355/162056    -> ciflow/rocm-mi355/162056
2025-09-07T07:36:14.7980396Z  * [new tag]                 ciflow/rocm/148492          -> ciflow/rocm/148492
2025-09-07T07:36:14.7981119Z  * [new tag]                 ciflow/rocm/154170          -> ciflow/rocm/154170
2025-09-07T07:36:14.7982103Z  * [new tag]                 ciflow/rocm/156491          -> ciflow/rocm/156491
2025-09-07T07:36:14.7982892Z  * [new tag]                 ciflow/rocm/156592          -> ciflow/rocm/156592
2025-09-07T07:36:14.7983708Z  * [new tag]                 ciflow/rocm/158747          -> ciflow/rocm/158747
2025-09-07T07:36:14.7984416Z  * [new tag]                 ciflow/rocm/159146          -> ciflow/rocm/159146
2025-09-07T07:36:14.7985453Z  * [new tag]                 ciflow/rocm/159158          -> ciflow/rocm/159158
2025-09-07T07:36:14.7986291Z  * [new tag]                 ciflow/rocm/161715          -> ciflow/rocm/161715
2025-09-07T07:36:14.7987193Z  * [new tag]                 ciflow/rocm/161972          -> ciflow/rocm/161972
2025-09-07T07:36:14.7988007Z  * [new tag]                 ciflow/rocm/162052          -> ciflow/rocm/162052
2025-09-07T07:36:14.7988791Z  * [new tag]                 ciflow/rocm/162053          -> ciflow/rocm/162053
2025-09-07T07:36:14.7989861Z  * [new tag]                 ciflow/rocm/162056          -> ciflow/rocm/162056
2025-09-07T07:36:14.7991084Z  * [new tag]                 ciflow/rocm/162112          -> ciflow/rocm/162112
2025-09-07T07:36:14.7992099Z  * [new tag]                 ciflow/rocm/162278          -> ciflow/rocm/162278
2025-09-07T07:36:14.7992962Z  * [new tag]                 ciflow/rocm/162288          -> ciflow/rocm/162288
2025-09-07T07:36:14.7993823Z  * [new tag]                 ciflow/rocm/162305          -> ciflow/rocm/162305
2025-09-07T07:36:14.7995075Z  * [new tag]                 ciflow/slow/01c7106         -> ciflow/slow/01c7106
2025-09-07T07:36:14.7996025Z  * [new tag]                 ciflow/slow/0577043         -> ciflow/slow/0577043
2025-09-07T07:36:14.7997247Z  * [new tag]                 ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym
2025-09-07T07:36:14.7997931Z  * [new tag]                 ciflow/slow/0e81104         -> ciflow/slow/0e81104
2025-09-07T07:36:14.7998889Z  * [new tag]                 ciflow/slow/161395          -> ciflow/slow/161395
2025-09-07T07:36:14.7999855Z  * [new tag]                 ciflow/slow/1732077         -> ciflow/slow/1732077
2025-09-07T07:36:14.8000800Z  * [new tag]                 ciflow/slow/187eb7c         -> ciflow/slow/187eb7c
2025-09-07T07:36:14.8001724Z  * [new tag]                 ciflow/slow/1faef89         -> ciflow/slow/1faef89
2025-09-07T07:36:14.8002922Z  * [new tag]                 ciflow/slow/3920ec1         -> ciflow/slow/3920ec1
2025-09-07T07:36:14.8004021Z  * [new tag]                 ciflow/slow/3b7c6b2         -> ciflow/slow/3b7c6b2
2025-09-07T07:36:14.8005111Z  * [new tag]                 ciflow/slow/59a3759         -> ciflow/slow/59a3759
2025-09-07T07:36:14.8006071Z  * [new tag]                 ciflow/slow/70ef0bb         -> ciflow/slow/70ef0bb
2025-09-07T07:36:14.8007022Z  * [new tag]                 ciflow/slow/788ff06         -> ciflow/slow/788ff06
2025-09-07T07:36:14.8008324Z  * [new tag]                 ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym
2025-09-07T07:36:14.8009140Z  * [new tag]                 ciflow/slow/9d85864         -> ciflow/slow/9d85864
2025-09-07T07:36:14.8010070Z  * [new tag]                 ciflow/slow/9ffad5b         -> ciflow/slow/9ffad5b
2025-09-07T07:36:14.8011178Z  * [new tag]                 ciflow/slow/a206e8b         -> ciflow/slow/a206e8b
2025-09-07T07:36:14.8012078Z  * [new tag]                 ciflow/slow/a837609         -> ciflow/slow/a837609
2025-09-07T07:36:14.8013033Z  * [new tag]                 ciflow/slow/af841f3         -> ciflow/slow/af841f3
2025-09-07T07:36:14.8014332Z  * [new tag]                 ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym
2025-09-07T07:36:14.8015191Z  * [new tag]                 ciflow/triton_binaries/162329 -> ciflow/triton_binaries/162329
2025-09-07T07:36:14.8016175Z  * [new tag]                 ciflow/trunk/113258         -> ciflow/trunk/113258
2025-09-07T07:36:14.8016937Z  * [new tag]                 ciflow/trunk/137400         -> ciflow/trunk/137400
2025-09-07T07:36:14.8017655Z  * [new tag]                 ciflow/trunk/148180         -> ciflow/trunk/148180
2025-09-07T07:36:14.8018445Z  * [new tag]                 ciflow/trunk/148328         -> ciflow/trunk/148328
2025-09-07T07:36:14.8019228Z  * [new tag]                 ciflow/trunk/148492         -> ciflow/trunk/148492
2025-09-07T07:36:14.8020143Z  * [new tag]                 ciflow/trunk/148919         -> ciflow/trunk/148919
2025-09-07T07:36:14.8020903Z  * [new tag]                 ciflow/trunk/152624         -> ciflow/trunk/152624
2025-09-07T07:36:14.8021686Z  * [new tag]                 ciflow/trunk/154170         -> ciflow/trunk/154170
2025-09-07T07:36:14.8022539Z  * [new tag]                 ciflow/trunk/154694         -> ciflow/trunk/154694
2025-09-07T07:36:14.8023262Z  * [new tag]                 ciflow/trunk/156049         -> ciflow/trunk/156049
2025-09-07T07:36:14.8024045Z  * [new tag]                 ciflow/trunk/156703         -> ciflow/trunk/156703
2025-09-07T07:36:14.8025144Z  * [new tag]                 ciflow/trunk/156711         -> ciflow/trunk/156711
2025-09-07T07:36:14.8026494Z  * [new tag]                 ciflow/trunk/157432         -> ciflow/trunk/157432
2025-09-07T07:36:14.8027499Z  * [new tag]                 ciflow/trunk/157685         -> ciflow/trunk/157685
2025-09-07T07:36:14.8028325Z  * [new tag]                 ciflow/trunk/157689         -> ciflow/trunk/157689
2025-09-07T07:36:14.8029553Z  * [new tag]                 ciflow/trunk/157699         -> ciflow/trunk/157699
2025-09-07T07:36:14.8030410Z  * [new tag]                 ciflow/trunk/157813         -> ciflow/trunk/157813
2025-09-07T07:36:14.8031231Z  * [new tag]                 ciflow/trunk/157994         -> ciflow/trunk/157994
2025-09-07T07:36:14.8032059Z  * [new tag]                 ciflow/trunk/158091         -> ciflow/trunk/158091
2025-09-07T07:36:14.8032856Z  * [new tag]                 ciflow/trunk/158104         -> ciflow/trunk/158104
2025-09-07T07:36:14.8033709Z  * [new tag]                 ciflow/trunk/158404         -> ciflow/trunk/158404
2025-09-07T07:36:14.8034614Z  * [new tag]                 ciflow/trunk/158647         -> ciflow/trunk/158647
2025-09-07T07:36:14.8035692Z  * [new tag]                 ciflow/trunk/158846         -> ciflow/trunk/158846
2025-09-07T07:36:14.8036518Z  * [new tag]                 ciflow/trunk/159158         -> ciflow/trunk/159158
2025-09-07T07:36:14.8037491Z  * [new tag]                 ciflow/trunk/159682         -> ciflow/trunk/159682
2025-09-07T07:36:14.8038275Z  * [new tag]                 ciflow/trunk/159835         -> ciflow/trunk/159835
2025-09-07T07:36:14.8039097Z  * [new tag]                 ciflow/trunk/160161         -> ciflow/trunk/160161
2025-09-07T07:36:14.8039918Z  * [new tag]                 ciflow/trunk/160236         -> ciflow/trunk/160236
2025-09-07T07:36:14.8040761Z  * [new tag]                 ciflow/trunk/160329         -> ciflow/trunk/160329
2025-09-07T07:36:14.8041574Z  * [new tag]                 ciflow/trunk/160480         -> ciflow/trunk/160480
2025-09-07T07:36:14.8042398Z  * [new tag]                 ciflow/trunk/160532         -> ciflow/trunk/160532
2025-09-07T07:36:14.8043209Z  * [new tag]                 ciflow/trunk/160836         -> ciflow/trunk/160836
2025-09-07T07:36:14.8044095Z  * [new tag]                 ciflow/trunk/160843         -> ciflow/trunk/160843
2025-09-07T07:36:14.8044909Z  * [new tag]                 ciflow/trunk/160869         -> ciflow/trunk/160869
2025-09-07T07:36:14.8045795Z  * [new tag]                 ciflow/trunk/160940         -> ciflow/trunk/160940
2025-09-07T07:36:14.8046623Z  * [new tag]                 ciflow/trunk/160943         -> ciflow/trunk/160943
2025-09-07T07:36:14.8047609Z  * [new tag]                 ciflow/trunk/160953         -> ciflow/trunk/160953
2025-09-07T07:36:14.8048552Z  * [new tag]                 ciflow/trunk/161035         -> ciflow/trunk/161035
2025-09-07T07:36:14.8049383Z  * [new tag]                 ciflow/trunk/161178         -> ciflow/trunk/161178
2025-09-07T07:36:14.8050178Z  * [new tag]                 ciflow/trunk/161349         -> ciflow/trunk/161349
2025-09-07T07:36:14.8051020Z  * [new tag]                 ciflow/trunk/161350         -> ciflow/trunk/161350
2025-09-07T07:36:14.8051914Z  * [new tag]                 ciflow/trunk/161351         -> ciflow/trunk/161351
2025-09-07T07:36:14.8052755Z  * [new tag]                 ciflow/trunk/161395         -> ciflow/trunk/161395
2025-09-07T07:36:14.8053613Z  * [new tag]                 ciflow/trunk/161405         -> ciflow/trunk/161405
2025-09-07T07:36:14.8054428Z  * [new tag]                 ciflow/trunk/161406         -> ciflow/trunk/161406
2025-09-07T07:36:14.8055243Z  * [new tag]                 ciflow/trunk/161410         -> ciflow/trunk/161410
2025-09-07T07:36:14.8056075Z  * [new tag]                 ciflow/trunk/161468         -> ciflow/trunk/161468
2025-09-07T07:36:14.8056998Z  * [new tag]                 ciflow/trunk/161499         -> ciflow/trunk/161499
2025-09-07T07:36:14.8058083Z  * [new tag]                 ciflow/trunk/161527         -> ciflow/trunk/161527
2025-09-07T07:36:14.8058936Z  * [new tag]                 ciflow/trunk/161534         -> ciflow/trunk/161534
2025-09-07T07:36:14.8059794Z  * [new tag]                 ciflow/trunk/161591         -> ciflow/trunk/161591
2025-09-07T07:36:14.8060634Z  * [new tag]                 ciflow/trunk/161595         -> ciflow/trunk/161595
2025-09-07T07:36:14.8061453Z  * [new tag]                 ciflow/trunk/161596         -> ciflow/trunk/161596
2025-09-07T07:36:14.8062292Z  * [new tag]                 ciflow/trunk/161633         -> ciflow/trunk/161633
2025-09-07T07:36:14.8063117Z  * [new tag]                 ciflow/trunk/161634         -> ciflow/trunk/161634
2025-09-07T07:36:14.8063981Z  * [new tag]                 ciflow/trunk/161635         -> ciflow/trunk/161635
2025-09-07T07:36:14.8064759Z  * [new tag]                 ciflow/trunk/161667         -> ciflow/trunk/161667
2025-09-07T07:36:14.8065618Z  * [new tag]                 ciflow/trunk/161670         -> ciflow/trunk/161670
2025-09-07T07:36:14.8066475Z  * [new tag]                 ciflow/trunk/161692         -> ciflow/trunk/161692
2025-09-07T07:36:14.8067293Z  * [new tag]                 ciflow/trunk/161693         -> ciflow/trunk/161693
2025-09-07T07:36:14.8068158Z  * [new tag]                 ciflow/trunk/161695         -> ciflow/trunk/161695
2025-09-07T07:36:14.8069119Z  * [new tag]                 ciflow/trunk/161730         -> ciflow/trunk/161730
2025-09-07T07:36:14.8069978Z  * [new tag]                 ciflow/trunk/161744         -> ciflow/trunk/161744
2025-09-07T07:36:14.8070785Z  * [new tag]                 ciflow/trunk/161749         -> ciflow/trunk/161749
2025-09-07T07:36:14.8071633Z  * [new tag]                 ciflow/trunk/161881         -> ciflow/trunk/161881
2025-09-07T07:36:14.8072436Z  * [new tag]                 ciflow/trunk/161924         -> ciflow/trunk/161924
2025-09-07T07:36:14.8073404Z  * [new tag]                 ciflow/trunk/161926         -> ciflow/trunk/161926
2025-09-07T07:36:14.8074223Z  * [new tag]                 ciflow/trunk/161936         -> ciflow/trunk/161936
2025-09-07T07:36:14.8075043Z  * [new tag]                 ciflow/trunk/161952         -> ciflow/trunk/161952
2025-09-07T07:36:14.8075933Z  * [new tag]                 ciflow/trunk/161955         -> ciflow/trunk/161955
2025-09-07T07:36:14.8076682Z  * [new tag]                 ciflow/trunk/161957         -> ciflow/trunk/161957
2025-09-07T07:36:14.8077515Z  * [new tag]                 ciflow/trunk/161959         -> ciflow/trunk/161959
2025-09-07T07:36:14.8078320Z  * [new tag]                 ciflow/trunk/161977         -> ciflow/trunk/161977
2025-09-07T07:36:14.8079223Z  * [new tag]                 ciflow/trunk/161988         -> ciflow/trunk/161988
2025-09-07T07:36:14.8080025Z  * [new tag]                 ciflow/trunk/161994         -> ciflow/trunk/161994
2025-09-07T07:36:14.8080981Z  * [new tag]                 ciflow/trunk/162007         -> ciflow/trunk/162007
2025-09-07T07:36:14.8081810Z  * [new tag]                 ciflow/trunk/162013         -> ciflow/trunk/162013
2025-09-07T07:36:14.8082685Z  * [new tag]                 ciflow/trunk/162017         -> ciflow/trunk/162017
2025-09-07T07:36:14.8083483Z  * [new tag]                 ciflow/trunk/162021         -> ciflow/trunk/162021
2025-09-07T07:36:14.8084730Z  * [new tag]                 ciflow/trunk/162022         -> ciflow/trunk/162022
2025-09-07T07:36:14.8085567Z  * [new tag]                 ciflow/trunk/162040         -> ciflow/trunk/162040
2025-09-07T07:36:14.8086393Z  * [new tag]                 ciflow/trunk/162041         -> ciflow/trunk/162041
2025-09-07T07:36:14.8087352Z  * [new tag]                 ciflow/trunk/162062         -> ciflow/trunk/162062
2025-09-07T07:36:14.8088173Z  * [new tag]                 ciflow/trunk/162066         -> ciflow/trunk/162066
2025-09-07T07:36:14.8089010Z  * [new tag]                 ciflow/trunk/162089         -> ciflow/trunk/162089
2025-09-07T07:36:14.8089845Z  * [new tag]                 ciflow/trunk/162099         -> ciflow/trunk/162099
2025-09-07T07:36:14.8090682Z  * [new tag]                 ciflow/trunk/162104         -> ciflow/trunk/162104
2025-09-07T07:36:14.8091540Z  * [new tag]                 ciflow/trunk/162106         -> ciflow/trunk/162106
2025-09-07T07:36:14.8092357Z  * [new tag]                 ciflow/trunk/162112         -> ciflow/trunk/162112
2025-09-07T07:36:14.8093160Z  * [new tag]                 ciflow/trunk/162119         -> ciflow/trunk/162119
2025-09-07T07:36:14.8093982Z  * [new tag]                 ciflow/trunk/162142         -> ciflow/trunk/162142
2025-09-07T07:36:14.8094822Z  * [new tag]                 ciflow/trunk/162169         -> ciflow/trunk/162169
2025-09-07T07:36:14.8095641Z  * [new tag]                 ciflow/trunk/162183         -> ciflow/trunk/162183
2025-09-07T07:36:14.8096473Z  * [new tag]                 ciflow/trunk/162190         -> ciflow/trunk/162190
2025-09-07T07:36:14.8097318Z  * [new tag]                 ciflow/trunk/162194         -> ciflow/trunk/162194
2025-09-07T07:36:14.8098120Z  * [new tag]                 ciflow/trunk/162200         -> ciflow/trunk/162200
2025-09-07T07:36:14.8099106Z  * [new tag]                 ciflow/trunk/162206         -> ciflow/trunk/162206
2025-09-07T07:36:14.8099964Z  * [new tag]                 ciflow/trunk/162208         -> ciflow/trunk/162208
2025-09-07T07:36:14.8100827Z  * [new tag]                 ciflow/trunk/162222         -> ciflow/trunk/162222
2025-09-07T07:36:14.8101642Z  * [new tag]                 ciflow/trunk/162238         -> ciflow/trunk/162238
2025-09-07T07:36:14.8102462Z  * [new tag]                 ciflow/trunk/162244         -> ciflow/trunk/162244
2025-09-07T07:36:14.8103544Z  * [new tag]                 ciflow/trunk/162267         -> ciflow/trunk/162267
2025-09-07T07:36:14.8104505Z  * [new tag]                 ciflow/trunk/162269         -> ciflow/trunk/162269
2025-09-07T07:36:14.8105325Z  * [new tag]                 ciflow/trunk/162278         -> ciflow/trunk/162278
2025-09-07T07:36:14.8106280Z  * [new tag]                 ciflow/trunk/162286         -> ciflow/trunk/162286
2025-09-07T07:36:14.8107210Z  * [new tag]                 ciflow/trunk/162288         -> ciflow/trunk/162288
2025-09-07T07:36:14.8108051Z  * [new tag]                 ciflow/trunk/162293         -> ciflow/trunk/162293
2025-09-07T07:36:14.8109092Z  * [new tag]                 ciflow/trunk/162310         -> ciflow/trunk/162310
2025-09-07T07:36:14.8109766Z  * [new tag]                 ciflow/trunk/162311         -> ciflow/trunk/162311
2025-09-07T07:36:14.8110622Z  * [new tag]                 ciflow/trunk/162315         -> ciflow/trunk/162315
2025-09-07T07:36:14.8111476Z  * [new tag]                 ciflow/trunk/162325         -> ciflow/trunk/162325
2025-09-07T07:36:14.8112643Z  * [new tag]                 ciflow/trunk/162328         -> ciflow/trunk/162328
2025-09-07T07:36:14.8113462Z  * [new tag]                 ciflow/trunk/162329         -> ciflow/trunk/162329
2025-09-07T07:36:14.8114715Z  * [new tag]                 ciflow/unstable/123         -> ciflow/unstable/123
2025-09-07T07:36:14.8115732Z  * [new tag]                 ciflow/vllm/162292          -> ciflow/vllm/162292
2025-09-07T07:36:14.8116821Z  * [new tag]                 ciflow/win-arm64/156049     -> ciflow/win-arm64/156049
2025-09-07T07:36:14.8117983Z  * [new tag]                 ciflow/win-arm64/158104     -> ciflow/win-arm64/158104
2025-09-07T07:36:14.8118601Z  * [new tag]                 ciflow/xpu/157699           -> ciflow/xpu/157699
2025-09-07T07:36:14.8119431Z  * [new tag]                 ciflow/xpu/157994           -> ciflow/xpu/157994
2025-09-07T07:36:14.8120391Z  * [new tag]                 ciflow/xpu/159459           -> ciflow/xpu/159459
2025-09-07T07:36:14.8121238Z  * [new tag]                 ciflow/xpu/159718           -> ciflow/xpu/159718
2025-09-07T07:36:14.8121895Z  * [new tag]                 ciflow/xpu/159944           -> ciflow/xpu/159944
2025-09-07T07:36:14.8122858Z  * [new tag]                 ciflow/xpu/160867           -> ciflow/xpu/160867
2025-09-07T07:36:14.8123760Z  * [new tag]                 ciflow/xpu/160938           -> ciflow/xpu/160938
2025-09-07T07:36:14.8124598Z  * [new tag]                 ciflow/xpu/160940           -> ciflow/xpu/160940
2025-09-07T07:36:14.8125344Z  * [new tag]                 ciflow/xpu/160953           -> ciflow/xpu/160953
2025-09-07T07:36:14.8126308Z  * [new tag]                 ciflow/xpu/161045           -> ciflow/xpu/161045
2025-09-07T07:36:14.8127319Z  * [new tag]                 ciflow/xpu/161058           -> ciflow/xpu/161058
2025-09-07T07:36:14.8128440Z  * [new tag]                 ciflow/xpu/161246           -> ciflow/xpu/161246
2025-09-07T07:36:14.8129554Z  * [new tag]                 ciflow/xpu/161397           -> ciflow/xpu/161397
2025-09-07T07:36:14.8130559Z  * [new tag]                 ciflow/xpu/161485           -> ciflow/xpu/161485
2025-09-07T07:36:14.8131432Z  * [new tag]                 ciflow/xpu/161988           -> ciflow/xpu/161988
2025-09-07T07:36:14.8132230Z  * [new tag]                 ciflow/xpu/162062           -> ciflow/xpu/162062
2025-09-07T07:36:14.8133227Z  * [new tag]                 cslpull75                   -> cslpull75
2025-09-07T07:36:14.8134062Z  * [new tag]                 cslpull76                   -> cslpull76
2025-09-07T07:36:14.8134922Z  * [new tag]                 cslpull77                   -> cslpull77
2025-09-07T07:36:14.8135784Z  * [new tag]                 cslpull78                   -> cslpull78
2025-09-07T07:36:14.8136882Z  * [new tag]                 cslpull79                   -> cslpull79
2025-09-07T07:36:14.8138100Z  * [new tag]                 cslpull80                   -> cslpull80
2025-09-07T07:36:14.8139045Z  * [new tag]                 cslpull81                   -> cslpull81
2025-09-07T07:36:14.8139929Z  * [new tag]                 cslpull82                   -> cslpull82
2025-09-07T07:36:14.8140832Z  * [new tag]                 cslpull83                   -> cslpull83
2025-09-07T07:36:14.8141743Z  * [new tag]                 cslpull84                   -> cslpull84
2025-09-07T07:36:14.8142606Z  * [new tag]                 cslpull85                   -> cslpull85
2025-09-07T07:36:14.8143518Z  * [new tag]                 cslpull86                   -> cslpull86
2025-09-07T07:36:14.8144410Z  * [new tag]                 cslpull87                   -> cslpull87
2025-09-07T07:36:14.8145479Z  * [new tag]                 cslpull88                   -> cslpull88
2025-09-07T07:36:14.8146377Z  * [new tag]                 cslpull89                   -> cslpull89
2025-09-07T07:36:14.8147073Z  * [new tag]                 cslpull90                   -> cslpull90
2025-09-07T07:36:14.8148929Z  * [new tag]                 cslpull91                   -> cslpull91
2025-09-07T07:36:14.8149808Z  * [new tag]                 cslpull92                   -> cslpull92
2025-09-07T07:36:14.8150750Z  * [new tag]                 flight_5                    -> flight_5
2025-09-07T07:36:14.8151689Z  * [new tag]                 flight_5.1                  -> flight_5.1
2025-09-07T07:36:14.8152648Z  * [new tag]                 flight_5.2                  -> flight_5.2
2025-09-07T07:36:14.8153482Z  * [new tag]                 flight_5.3                  -> flight_5.3
2025-09-07T07:36:14.8154382Z  * [new tag]                 forpull1                    -> forpull1
2025-09-07T07:36:14.8155594Z  * [new tag]                 malfet/tag-2ef5611          -> malfet/tag-2ef5611
2025-09-07T07:36:14.8156486Z  * [new tag]                 malfet/tag-317b1a0          -> malfet/tag-317b1a0
2025-09-07T07:36:14.8157392Z  * [new tag]                 malfet/tag-ec6f767          -> malfet/tag-ec6f767
2025-09-07T07:36:14.8158471Z  * [new tag]                 nightly-binary              -> nightly-binary
2025-09-07T07:36:14.8159190Z  * [new tag]                 sqzhang_flight4_plus        -> sqzhang_flight4_plus
2025-09-07T07:36:14.8160393Z  * [new tag]                 sqzhang_flight_3            -> sqzhang_flight_3
2025-09-07T07:36:14.8161704Z  * [new tag]                 trunk/00636e0171e7e733628c408084805442270cf608 -> trunk/00636e0171e7e733628c408084805442270cf608
2025-09-07T07:36:14.8162778Z  * [new tag]                 trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4 -> trunk/019fed39aa6b2dd8c69347378d53423e5efae8d4
2025-09-07T07:36:14.8163967Z  * [new tag]                 trunk/01ab325cc2e0dc221af4d710974e1b9175066544 -> trunk/01ab325cc2e0dc221af4d710974e1b9175066544
2025-09-07T07:36:14.8165443Z  * [new tag]                 trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b -> trunk/01edcd4df8bf0c7b4cc2d3ec868bd2059eeea83b
2025-09-07T07:36:14.8166448Z  * [new tag]                 trunk/040d00af048967dde7938d358d7f5988cbd18388 -> trunk/040d00af048967dde7938d358d7f5988cbd18388
2025-09-07T07:36:14.8167463Z  * [new tag]                 trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5 -> trunk/0447f2d99b4351b2ff129dce6eebb371024f73e5
2025-09-07T07:36:14.8168582Z  * [new tag]                 trunk/047603d35bdc70046216384838d6340feab79bf4 -> trunk/047603d35bdc70046216384838d6340feab79bf4
2025-09-07T07:36:14.8169542Z  * [new tag]                 trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81 -> trunk/06da7c0730b3764f178ec3a90dedf4ffa4202d81
2025-09-07T07:36:14.8170621Z  * [new tag]                 trunk/081cab045472ce045634548cc6c14a4870641e23 -> trunk/081cab045472ce045634548cc6c14a4870641e23
2025-09-07T07:36:14.8171570Z  * [new tag]                 trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572 -> trunk/09587daf8c9f21f5340f73921ce5f23d1a4a4572
2025-09-07T07:36:14.8172501Z  * [new tag]                 trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6 -> trunk/09be1890d72cc34fc946965dc4a27736bf0ca8c6
2025-09-07T07:36:14.8173455Z  * [new tag]                 trunk/09d2f1b6315d6d416fbf452793d65795863ebc66 -> trunk/09d2f1b6315d6d416fbf452793d65795863ebc66
2025-09-07T07:36:14.8174427Z  * [new tag]                 trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0 -> trunk/0af70e2353e1dcda83175fd4834ecb7b63e009e0
2025-09-07T07:36:14.8175845Z  * [new tag]                 trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736 -> trunk/0c0e056a9e20c17271a6144dd32c0c7e3ba26736
2025-09-07T07:36:14.8176801Z  * [new tag]                 trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9 -> trunk/0cd6c56bdfa9178ff61be82ce3b178926ddb64a9
2025-09-07T07:36:14.8177782Z  * [new tag]                 trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c -> trunk/0d421ace32c1605ee8e452ee1eeb03bd243dd96c
2025-09-07T07:36:14.8178875Z  * [new tag]                 trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171 -> trunk/0d71a9dd5b4b6d1dde58d91c9b71d96bc6a6a171
2025-09-07T07:36:14.8179708Z  * [new tag]                 trunk/0d84ff3b78f55492d3d4708458c92d776274939e -> trunk/0d84ff3b78f55492d3d4708458c92d776274939e
2025-09-07T07:36:14.8180670Z  * [new tag]                 trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63 -> trunk/0f45aaf4414048b17d720d0915ce221a8de8ec63
2025-09-07T07:36:14.8181688Z  * [new tag]                 trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f -> trunk/0ff8eabf1387de5acd6712a03bda61f1a3dfa27f
2025-09-07T07:36:14.8182592Z  * [new tag]                 trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f -> trunk/104f2680e03d13a4765ca69f905d8f16fc0c822f
2025-09-07T07:36:14.8183592Z  * [new tag]                 trunk/12814701555d3e41dfcdf8f9273af5821e322df0 -> trunk/12814701555d3e41dfcdf8f9273af5821e322df0
2025-09-07T07:36:14.8184560Z  * [new tag]                 trunk/13b65196db422bdb394cb482e208c61ed448898c -> trunk/13b65196db422bdb394cb482e208c61ed448898c
2025-09-07T07:36:14.8185569Z  * [new tag]                 trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46 -> trunk/13d66e2a66eceed14b8a8f5a971087df4f688a46
2025-09-07T07:36:14.8186479Z  * [new tag]                 trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225 -> trunk/145a3a7bda15e3963a33eb1b54bba5d4a270b225
2025-09-07T07:36:14.8187470Z  * [new tag]                 trunk/146371483318e17929daefd37c8e459d9d6d47bb -> trunk/146371483318e17929daefd37c8e459d9d6d47bb
2025-09-07T07:36:14.8188452Z  * [new tag]                 trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339 -> trunk/15c77a8cfd341e74fd124b077492ef2bfa51b339
2025-09-07T07:36:14.8189381Z  * [new tag]                 trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654 -> trunk/17fa8eec4a1e32939ab4d364ee6e75487a79b654
2025-09-07T07:36:14.8190779Z  * [new tag]                 trunk/190c391a28845a14df26abb228d26aa813efb20c -> trunk/190c391a28845a14df26abb228d26aa813efb20c
2025-09-07T07:36:14.8191806Z  * [new tag]                 trunk/1a588ace4667bde1331fbd8ed957157dca5cee68 -> trunk/1a588ace4667bde1331fbd8ed957157dca5cee68
2025-09-07T07:36:14.8192815Z  * [new tag]                 trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7 -> trunk/1aa7476885e8f6e7b0ec3a5b6383aad9d3f343e7
2025-09-07T07:36:14.8193615Z  * [new tag]                 trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53 -> trunk/1aeb421c342c9e9607842f4c87cb46e8e816ee53
2025-09-07T07:36:14.8194590Z  * [new tag]                 trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a -> trunk/1c1b28d5b6a942fafe23b2f09302d93c25226d4a
2025-09-07T07:36:14.8195577Z  * [new tag]                 trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99 -> trunk/1ebd70d0c0d562d3be9abdee2a21906584af7d99
2025-09-07T07:36:14.8196556Z  * [new tag]                 trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965 -> trunk/1ec2c15914da4ef7bd926ed9aebc8671c75fe965
2025-09-07T07:36:14.8197475Z  * [new tag]                 trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a -> trunk/1f51056bd64e73d1aa81321bc3c098575b1bc78a
2025-09-07T07:36:14.8198461Z  * [new tag]                 trunk/1f820de639c75a1562d3fb03f160439f853ae07b -> trunk/1f820de639c75a1562d3fb03f160439f853ae07b
2025-09-07T07:36:14.8199865Z  * [new tag]                 trunk/204697f0e695d82894c5010fbec664c4391f90cc -> trunk/204697f0e695d82894c5010fbec664c4391f90cc
2025-09-07T07:36:14.8201304Z  * [new tag]                 trunk/20629b1619fe636227d01fc85ba221daa7185a05 -> trunk/20629b1619fe636227d01fc85ba221daa7185a05
2025-09-07T07:36:14.8201637Z  * [new tag]                 trunk/20b47acef845e9c4f71da9429a396d293f50ebe7 -> trunk/20b47acef845e9c4f71da9429a396d293f50ebe7
2025-09-07T07:36:14.8202837Z  * [new tag]                 trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd -> trunk/20bfb2539d7c5250379648eda35f80b8a7d642dd
2025-09-07T07:36:14.8203568Z  * [new tag]                 trunk/21fae99c180d17def562797ea0fb154d8fdf88e3 -> trunk/21fae99c180d17def562797ea0fb154d8fdf88e3
2025-09-07T07:36:14.8205066Z  * [new tag]                 trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f -> trunk/248355faf53f9f7ba2fd0a367d59600c6d991e7f
2025-09-07T07:36:14.8205403Z  * [new tag]                 trunk/25f4aaed9ec26f39c13862323ff8582006473d23 -> trunk/25f4aaed9ec26f39c13862323ff8582006473d23
2025-09-07T07:36:14.8206539Z  * [new tag]                 trunk/261a84a1764412f8e659c956e3f81997ec3de9d5 -> trunk/261a84a1764412f8e659c956e3f81997ec3de9d5
2025-09-07T07:36:14.8207592Z  * [new tag]                 trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f -> trunk/28f4ab0737937858730f29f5c4e601e109cf9d5f
2025-09-07T07:36:14.8208557Z  * [new tag]                 trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4 -> trunk/291cd11f2d5df6f48d348cce0e4e762f274f4dc4
2025-09-07T07:36:14.8209492Z  * [new tag]                 trunk/29280864d941e6108ab57f7298f520c0cf9696e9 -> trunk/29280864d941e6108ab57f7298f520c0cf9696e9
2025-09-07T07:36:14.8210748Z  * [new tag]                 trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5 -> trunk/2a45837e98c63cae9d1a2e2133a727b829e549d5
2025-09-07T07:36:14.8211772Z  * [new tag]                 trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef -> trunk/2a5c0785e2f975697fd7bdf1411de6e03dcaa1ef
2025-09-07T07:36:14.8212726Z  * [new tag]                 trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c -> trunk/2b8a83901c58a0858ea9e4ce00055f48e6ed164c
2025-09-07T07:36:14.8213691Z  * [new tag]                 trunk/2ba65472dd54488a86a50326ea990195fc6732d6 -> trunk/2ba65472dd54488a86a50326ea990195fc6732d6
2025-09-07T07:36:14.8214669Z  * [new tag]                 trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0 -> trunk/2c03f0acc53ed13fe8ebfe809129f25996e009a0
2025-09-07T07:36:14.8215484Z  * [new tag]                 trunk/2dd529df0092799f68ee7afcf52338276906706a -> trunk/2dd529df0092799f68ee7afcf52338276906706a
2025-09-07T07:36:14.8216647Z  * [new tag]                 trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5 -> trunk/2f6b4b1ad3f82bb3bd984f6e65744ea339ffb8b5
2025-09-07T07:36:14.8217507Z  * [new tag]                 trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8 -> trunk/2fa0520a64ed8aa734a56c4d124958f0b5711ca8
2025-09-07T07:36:14.8218506Z  * [new tag]                 trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8 -> trunk/302df2ac5dc4222294c09d48804a2dddb8f4bad8
2025-09-07T07:36:14.8219274Z  * [new tag]                 trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43 -> trunk/33028597bfa2e0178e28c8cce33cb9b3800cac43
2025-09-07T07:36:14.8220298Z  * [new tag]                 trunk/34aa78274d6770086025a967fa63a86830e08176 -> trunk/34aa78274d6770086025a967fa63a86830e08176
2025-09-07T07:36:14.8221248Z  * [new tag]                 trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449 -> trunk/3559c354ce6a14d11fe29fb12fa2747a2f2af449
2025-09-07T07:36:14.8222003Z  * [new tag]                 trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b -> trunk/36d207fcaaede0d1e58a5168084c307b32b6fd8b
2025-09-07T07:36:14.8222836Z  * [new tag]                 trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0 -> trunk/377033757ae5ca524ea842f1b0a5f446ed3d8fe0
2025-09-07T07:36:14.8223846Z  * [new tag]                 trunk/3771380f83fcac154a7c89ad679311d8c4818287 -> trunk/3771380f83fcac154a7c89ad679311d8c4818287
2025-09-07T07:36:14.8224791Z  * [new tag]                 trunk/3a207816cc569f78863d86c01f2a3d265350e39f -> trunk/3a207816cc569f78863d86c01f2a3d265350e39f
2025-09-07T07:36:14.8225859Z  * [new tag]                 trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67 -> trunk/3a20a20e7065ec927fdd216d4da3b04f879b3c67
2025-09-07T07:36:14.8226951Z  * [new tag]                 trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0 -> trunk/3bbc2e3e4f025523eaa5dbff220b3e96bca608d0
2025-09-07T07:36:14.8227886Z  * [new tag]                 trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f -> trunk/3c0ff1b569c45cfa6935ad8031a9d4cf1551aa3f
2025-09-07T07:36:14.8229198Z  * [new tag]                 trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf -> trunk/3c45af079afc92a03b03ddf4f9198902ffcf30cf
2025-09-07T07:36:14.8230210Z  * [new tag]                 trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5 -> trunk/3dde5d7f9bf80dd6623a712bc429e9e4302464b5
2025-09-07T07:36:14.8231120Z  * [new tag]                 trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d -> trunk/403a3a393cda7e60f503f3b04b8805a845dcf45d
2025-09-07T07:36:14.8232107Z  * [new tag]                 trunk/420c52ecf36f86d32da0853bfbe074b682b070aa -> trunk/420c52ecf36f86d32da0853bfbe074b682b070aa
2025-09-07T07:36:14.8233046Z  * [new tag]                 trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6 -> trunk/43b7c86a2c0f91320f5c5f4827b111edff06fdb6
2025-09-07T07:36:14.8233984Z  * [new tag]                 trunk/451ed931562ec8b46d1f7e6c266a68132a119336 -> trunk/451ed931562ec8b46d1f7e6c266a68132a119336
2025-09-07T07:36:14.8234928Z  * [new tag]                 trunk/480c7391126656154318fabf1d57ebc01e196e63 -> trunk/480c7391126656154318fabf1d57ebc01e196e63
2025-09-07T07:36:14.8237126Z  * [new tag]                 trunk/48bedd753da22634aa94fbafeb731e82025404f3 -> trunk/48bedd753da22634aa94fbafeb731e82025404f3
2025-09-07T07:36:14.8237365Z  * [new tag]                 trunk/494878a11b79071ada0b98f34042d47155be6d1c -> trunk/494878a11b79071ada0b98f34042d47155be6d1c
2025-09-07T07:36:14.8238527Z  * [new tag]                 trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051 -> trunk/4ae57d448c0a7d37e4cfd5c27d977fad2cef4051
2025-09-07T07:36:14.8239265Z  * [new tag]                 trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf -> trunk/4cdaf8265d86f984254b62052da8c26ef61ef1cf
2025-09-07T07:36:14.8239788Z  * [new tag]                 trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e -> trunk/4d4abec80f03cd8fdefe1d9cb3a60d3690cd777e
2025-09-07T07:36:14.8240614Z  * [new tag]                 trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186 -> trunk/4e42aa8ffc44b8340eb0eeaf80a2cafc4763a186
2025-09-07T07:36:14.8241553Z  * [new tag]                 trunk/4f72d932feee0749397fec876dcd43994f50b215 -> trunk/4f72d932feee0749397fec876dcd43994f50b215
2025-09-07T07:36:14.8242606Z  * [new tag]                 trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d -> trunk/50fc22dedf3c4a27be61fa05551c4f320281b42d
2025-09-07T07:36:14.8243543Z  * [new tag]                 trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9 -> trunk/5211f1f908907ffc064b56e43cf8659f7fc22aa9
2025-09-07T07:36:14.8244514Z  * [new tag]                 trunk/524b78d4f67045b83bb69edc56ab16efe282971c -> trunk/524b78d4f67045b83bb69edc56ab16efe282971c
2025-09-07T07:36:14.8245475Z  * [new tag]                 trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15 -> trunk/54e275e0d81fe1e1ccfa4fb5f2a5a9aaca00ca15
2025-09-07T07:36:14.8246311Z  * [new tag]                 trunk/5561e45758d59c94605873d5db48ed459c004c3b -> trunk/5561e45758d59c94605873d5db48ed459c004c3b
2025-09-07T07:36:14.8247358Z  * [new tag]                 trunk/57278d45f046d4f89f45d373b1af4dd56934ff24 -> trunk/57278d45f046d4f89f45d373b1af4dd56934ff24
2025-09-07T07:36:14.8248307Z  * [new tag]                 trunk/5927a70934ccf7b70182d364c23245a7dd685503 -> trunk/5927a70934ccf7b70182d364c23245a7dd685503
2025-09-07T07:36:14.8249250Z  * [new tag]                 trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599 -> trunk/5985e28912aeb40b103ebfcf2fd0665eb4a50599
2025-09-07T07:36:14.8250304Z  * [new tag]                 trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6 -> trunk/5a2da090ed6db88bb657c4e51ec0b310cd08bff6
2025-09-07T07:36:14.8251222Z  * [new tag]                 trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5 -> trunk/5c473e9f5ee0ef0fc38e6cf34a95b547f8cdc8d5
2025-09-07T07:36:14.8252203Z  * [new tag]                 trunk/5c67426d6847667a7c55a2dd01f470fa37238c18 -> trunk/5c67426d6847667a7c55a2dd01f470fa37238c18
2025-09-07T07:36:14.8253143Z  * [new tag]                 trunk/5da573c42c332bc68d4b7946c69f690a876d951a -> trunk/5da573c42c332bc68d4b7946c69f690a876d951a
2025-09-07T07:36:14.8254127Z  * [new tag]                 trunk/5e5870e858f60ff4bf87d03f3592097e934a9580 -> trunk/5e5870e858f60ff4bf87d03f3592097e934a9580
2025-09-07T07:36:14.8255084Z  * [new tag]                 trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84 -> trunk/5f3cbc9442aa55b5afb29f4ac8ca9be569003e84
2025-09-07T07:36:14.8256164Z  * [new tag]                 trunk/600c25e9a17fe56e3dee872be8854db08916ba0c -> trunk/600c25e9a17fe56e3dee872be8854db08916ba0c
2025-09-07T07:36:14.8257011Z  * [new tag]                 trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14 -> trunk/601ae8e4831fc8123fffcfb8fd2e6b6381b42e14
2025-09-07T07:36:14.8258120Z  * [new tag]                 trunk/6087ef41e54c2494b117ffd923faf20f515a6806 -> trunk/6087ef41e54c2494b117ffd923faf20f515a6806
2025-09-07T07:36:14.8259258Z  * [new tag]                 trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1 -> trunk/626cb7df8161dd4ecb4fe43b60f37ce9076f56b1
2025-09-07T07:36:14.8260209Z  * [new tag]                 trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6 -> trunk/62c3f9a97fd3dea7132a93066d32d893ffe101e6
2025-09-07T07:36:14.8261181Z  * [new tag]                 trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35 -> trunk/63a9c23fe99eacfd09610c36dfe8f01b053c1a35
2025-09-07T07:36:14.8262132Z  * [new tag]                 trunk/65985937d97505f648b6ed852c3129f2dd08b251 -> trunk/65985937d97505f648b6ed852c3129f2dd08b251
2025-09-07T07:36:14.8263541Z  * [new tag]                 trunk/66f3b4a682a6153517dd23369fdc3289b6494b07 -> trunk/66f3b4a682a6153517dd23369fdc3289b6494b07
2025-09-07T07:36:14.8264314Z  * [new tag]                 trunk/6737e2c996990024187ba620d2764f3b6f6add2c -> trunk/6737e2c996990024187ba620d2764f3b6f6add2c
2025-09-07T07:36:14.8265331Z  * [new tag]                 trunk/67c31dcd364f10072a55f4a30ffd1151c686283a -> trunk/67c31dcd364f10072a55f4a30ffd1151c686283a
2025-09-07T07:36:14.8266414Z  * [new tag]                 trunk/68738beff73e9c3512e18b4edea811a897ce42db -> trunk/68738beff73e9c3512e18b4edea811a897ce42db
2025-09-07T07:36:14.8267432Z  * [new tag]                 trunk/69a25f68884a168550695fdb1a7c310c54d29536 -> trunk/69a25f68884a168550695fdb1a7c310c54d29536
2025-09-07T07:36:14.8268358Z  * [new tag]                 trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f -> trunk/6b1900c22f1a07b9519346898d4c71d8a2b0f12f
2025-09-07T07:36:14.8269250Z  * [new tag]                 trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774 -> trunk/6b8b3ac4403f771bd4a8f9a45d93347304148774
2025-09-07T07:36:14.8270247Z  * [new tag]                 trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b -> trunk/6f7608d603834d6068b2e7a5d59bec3973b6bb1b
2025-09-07T07:36:14.8271225Z  * [new tag]                 trunk/70d36e047dfb3488fd6335016711a784d810ebda -> trunk/70d36e047dfb3488fd6335016711a784d810ebda
2025-09-07T07:36:14.8272205Z  * [new tag]                 trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b -> trunk/71992dd805ff9d6763f77214dfe8b0465e88c87b
2025-09-07T07:36:14.8273181Z  * [new tag]                 trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20 -> trunk/734ce8eba9c69381f187359bf0fef1d71d84cd20
2025-09-07T07:36:14.8274180Z  * [new tag]                 trunk/73eb4511fb863a37944342b7e92aae706de603c8 -> trunk/73eb4511fb863a37944342b7e92aae706de603c8
2025-09-07T07:36:14.8275141Z  * [new tag]                 trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b -> trunk/75bc23cfc345bd4c05e7f97c416c4b3d2d1fa64b
2025-09-07T07:36:14.8276098Z  * [new tag]                 trunk/771f369448321a387f2018535bc8b8b6e5f12fab -> trunk/771f369448321a387f2018535bc8b8b6e5f12fab
2025-09-07T07:36:14.8277122Z  * [new tag]                 trunk/789d4942127143f2adcb53612c058ce4c9a2cf20 -> trunk/789d4942127143f2adcb53612c058ce4c9a2cf20
2025-09-07T07:36:14.8277925Z  * [new tag]                 trunk/791eff96c85678c950888f9da24650083ee673fe -> trunk/791eff96c85678c950888f9da24650083ee673fe
2025-09-07T07:36:14.8278744Z  * [new tag]                 trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9 -> trunk/793fc12aff1f69fbbf9f4278182fb52bbe350fc9
2025-09-07T07:36:14.8279764Z  * [new tag]                 trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01 -> trunk/79fcd5247a9a129eee526a14df30bfc6a22b3f01
2025-09-07T07:36:14.8280741Z  * [new tag]                 trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348 -> trunk/7f4ff79210eb06924f223ae3a1941ee0e2635348
2025-09-07T07:36:14.8281627Z  * [new tag]                 trunk/8076a185c85112be62be292eb47409c88a585b1c -> trunk/8076a185c85112be62be292eb47409c88a585b1c
2025-09-07T07:36:14.8282597Z  * [new tag]                 trunk/80dd397f1979371a5583fa3d5c7352029522a78d -> trunk/80dd397f1979371a5583fa3d5c7352029522a78d
2025-09-07T07:36:14.8283413Z  * [new tag]                 trunk/8171d6052ec12628eb67e0040839314056014429 -> trunk/8171d6052ec12628eb67e0040839314056014429
2025-09-07T07:36:14.8284486Z  * [new tag]                 trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071 -> trunk/81aeefa657b7ccc26b275c50a9f33b2f056e8071
2025-09-07T07:36:14.8285431Z  * [new tag]                 trunk/81b7b16618bda250ce55982894a83dc0805eb64c -> trunk/81b7b16618bda250ce55982894a83dc0805eb64c
2025-09-07T07:36:14.8286454Z  * [new tag]                 trunk/827f0d405448de31f79d1089f7d7fceab2f87895 -> trunk/827f0d405448de31f79d1089f7d7fceab2f87895
2025-09-07T07:36:14.8287476Z  * [new tag]                 trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8 -> trunk/82f63c8f6de63c30132a8ac299b6e8c2fd0d3fe8
2025-09-07T07:36:14.8288406Z  * [new tag]                 trunk/850e1382a9c56bfde18af09d3e72352d775e9435 -> trunk/850e1382a9c56bfde18af09d3e72352d775e9435
2025-09-07T07:36:14.8289471Z  * [new tag]                 trunk/8678d831c48e616b717bff50f2d03141d2e9f965 -> trunk/8678d831c48e616b717bff50f2d03141d2e9f965
2025-09-07T07:36:14.8290501Z  * [new tag]                 trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60 -> trunk/869cbcc16e489a4f5a14a93d5779b0ea86061c60
2025-09-07T07:36:14.8291934Z  * [new tag]                 trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7 -> trunk/8703debf669bc2238211bfd039f4ecdd8228b7f7
2025-09-07T07:36:14.8292901Z  * [new tag]                 trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608 -> trunk/874069fbe46e82da5cfa405e6c0deb12e89ff608
2025-09-07T07:36:14.8293900Z  * [new tag]                 trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3 -> trunk/8875d6e394da2fffd04f31b28bf258c94d4776a3
2025-09-07T07:36:14.8294952Z  * [new tag]                 trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16 -> trunk/88d94d17e8c5155451393afa6eb3bab48ab61c16
2025-09-07T07:36:14.8295961Z  * [new tag]                 trunk/890626632def7e0ef95a2d01e87a0e4627824a9f -> trunk/890626632def7e0ef95a2d01e87a0e4627824a9f
2025-09-07T07:36:14.8297016Z  * [new tag]                 trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570 -> trunk/8975cda2520b7b1b5bc3b4d8213edf261fa82570
2025-09-07T07:36:14.8297954Z  * [new tag]                 trunk/89d41d3f61d04f14730ec26f008a59bef6624610 -> trunk/89d41d3f61d04f14730ec26f008a59bef6624610
2025-09-07T07:36:14.8299070Z  * [new tag]                 trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41 -> trunk/8bb213b6d599ef1273fe52f9b1f6d476056c3a41
2025-09-07T07:36:14.8304098Z  * [new tag]                 trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af -> trunk/8e23a1227b5fb2e39afaa7d57c075a75b640a5af
2025-09-07T07:36:14.8305418Z  * [new tag]                 trunk/8ec551bb354ab2b85fbbba9d461740a20366d248 -> trunk/8ec551bb354ab2b85fbbba9d461740a20366d248
2025-09-07T07:36:14.8306556Z  * [new tag]                 trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d -> trunk/8fd3c9ce919c8d5c645fd348bba517e948cbc29d
2025-09-07T07:36:14.8307714Z  * [new tag]                 trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9 -> trunk/90f50f7e68e120d9574e6e3189e37b4280010ad9
2025-09-07T07:36:14.8308743Z  * [new tag]                 trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9 -> trunk/91f0bcf43fc0bc743350d491ac63b77e92054ac9
2025-09-07T07:36:14.8309920Z  * [new tag]                 trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab -> trunk/92576a594b8121f6b0b1b5a3ea16d08792fc68ab
2025-09-07T07:36:14.8310924Z  * [new tag]                 trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d -> trunk/92a43025e0baa1f2ce345f28d22913b518a1ab9d
2025-09-07T07:36:14.8311742Z  * [new tag]                 trunk/93fb23d6fae7c4e82c4239a1033e522088742634 -> trunk/93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:36:14.8312947Z  * [new tag]                 trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c -> trunk/9458d1ac3bd70c2af316a8ba95d2c6c9c1199c9c
2025-09-07T07:36:14.8314024Z  * [new tag]                 trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e -> trunk/9480cdc0b61488c89a23c2f64f43b2dcedc8728e
2025-09-07T07:36:14.8314962Z  * [new tag]                 trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840 -> trunk/9491d289b329e4ba4a9f5f5b1be7960671bb7840
2025-09-07T07:36:14.8315978Z  * [new tag]                 trunk/9499c8761cd2067feb9877414e818f6fd00290f1 -> trunk/9499c8761cd2067feb9877414e818f6fd00290f1
2025-09-07T07:36:14.8316944Z  * [new tag]                 trunk/95ee0bfea99d3d346d6502b91b497d2b35795504 -> trunk/95ee0bfea99d3d346d6502b91b497d2b35795504
2025-09-07T07:36:14.8317946Z  * [new tag]                 trunk/98374612fc2febd686be20761e56bdc2424bc36a -> trunk/98374612fc2febd686be20761e56bdc2424bc36a
2025-09-07T07:36:14.8318998Z  * [new tag]                 trunk/98efc9e93d8fc61eb53cb91378443617cb550500 -> trunk/98efc9e93d8fc61eb53cb91378443617cb550500
2025-09-07T07:36:14.8319997Z  * [new tag]                 trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9 -> trunk/994f2a5dbcbdc915da39bf6f6ce4d1f5e74835c9
2025-09-07T07:36:14.8321024Z  * [new tag]                 trunk/99f356fa58c8d726cef022d8710f5491291158f6 -> trunk/99f356fa58c8d726cef022d8710f5491291158f6
2025-09-07T07:36:14.8322025Z  * [new tag]                 trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99 -> trunk/9a1c5c0a078b94d13ac5c1ae0d754d19fb73bf99
2025-09-07T07:36:14.8323003Z  * [new tag]                 trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd -> trunk/9a665ca3c472384e9d722bddba79e5a7680f1abd
2025-09-07T07:36:14.8323988Z  * [new tag]                 trunk/9aedb3cd87b52160872173c177f61053d97bed57 -> trunk/9aedb3cd87b52160872173c177f61053d97bed57
2025-09-07T07:36:14.8324984Z  * [new tag]                 trunk/9b81fe281da41f2421506339d26b027a468902f4 -> trunk/9b81fe281da41f2421506339d26b027a468902f4
2025-09-07T07:36:14.8325931Z  * [new tag]                 trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e -> trunk/9bdcee01f86e2969cff1140cdecfca13cb51816e
2025-09-07T07:36:14.8327044Z  * [new tag]                 trunk/9c03d6be87eedc06e524e202e07a7e776551a839 -> trunk/9c03d6be87eedc06e524e202e07a7e776551a839
2025-09-07T07:36:14.8328022Z  * [new tag]                 trunk/9c957723a0fedd9c637e63e023a613019e2cab60 -> trunk/9c957723a0fedd9c637e63e023a613019e2cab60
2025-09-07T07:36:14.8329029Z  * [new tag]                 trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5 -> trunk/9e5247f51d81735e5f1e65e80588985fa93bccc5
2025-09-07T07:36:14.8330050Z  * [new tag]                 trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26 -> trunk/9eadb37cdd699f7e8e8177a5227bfeb16184ef26
2025-09-07T07:36:14.8331054Z  * [new tag]                 trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29 -> trunk/a00cdc1e4159db73c9ffb3f25e93e55877709a29
2025-09-07T07:36:14.8332028Z  * [new tag]                 trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705 -> trunk/a02ee4a816d11380c6f564c1aba64d56af5ba705
2025-09-07T07:36:14.8333119Z  * [new tag]                 trunk/a3c7f77e50f900721817934120d60c2361b3c40d -> trunk/a3c7f77e50f900721817934120d60c2361b3c40d
2025-09-07T07:36:14.8334087Z  * [new tag]                 trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802 -> trunk/a3d72b09ae12126a2b7d4a63a45ac100a882a802
2025-09-07T07:36:14.8335107Z  * [new tag]                 trunk/a3e5466002791da609fcb069155d8ee347baee92 -> trunk/a3e5466002791da609fcb069155d8ee347baee92
2025-09-07T07:36:14.8336106Z  * [new tag]                 trunk/a714437093ed196eee28f7de454cf4c41badc098 -> trunk/a714437093ed196eee28f7de454cf4c41badc098
2025-09-07T07:36:14.8337100Z  * [new tag]                 trunk/a75e8cd27098f290de0b7439685d05ce02e91356 -> trunk/a75e8cd27098f290de0b7439685d05ce02e91356
2025-09-07T07:36:14.8337936Z  * [new tag]                 trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae -> trunk/a8d6943d36c1c2a5f90d3573460695bad4b623ae
2025-09-07T07:36:14.8338977Z  * [new tag]                 trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34 -> trunk/a918bbad6ab20649ff82eefb48417ecbe96bcb34
2025-09-07T07:36:14.8340328Z  * [new tag]                 trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e -> trunk/a99d8d39bc842d6ebc3e368b178e4884d24b056e
2025-09-07T07:36:14.8340973Z  * [new tag]                 trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02 -> trunk/aac1a50a191b4102d566c9c1ea22f06d6c2e3f02
2025-09-07T07:36:14.8342030Z  * [new tag]                 trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92 -> trunk/aad96a202244c7d0d120c04ba8db593edd8c0f92
2025-09-07T07:36:14.8343007Z  * [new tag]                 trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c -> trunk/ab643e4dbbaf7b663d4237514cbf01af9b11565c
2025-09-07T07:36:14.8344015Z  * [new tag]                 trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47 -> trunk/abc447174cd2cf8591edbc70a9f836f9a5779f47
2025-09-07T07:36:14.8344984Z  * [new tag]                 trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d -> trunk/acece97c3a9dceb63194e314da93fdf37cf15a0d
2025-09-07T07:36:14.8346094Z  * [new tag]                 trunk/adae7f66aacf3f248c3101b858cf98d5809119fa -> trunk/adae7f66aacf3f248c3101b858cf98d5809119fa
2025-09-07T07:36:14.8347210Z  * [new tag]                 trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c -> trunk/ae0edc133e61e3b16caf0b2ee0ff3f33ab72af4c
2025-09-07T07:36:14.8348216Z  * [new tag]                 trunk/aed33a8fcbd60b052d4559d261390c5797129c6d -> trunk/aed33a8fcbd60b052d4559d261390c5797129c6d
2025-09-07T07:36:14.8349266Z  * [new tag]                 trunk/b04e922712080a3652e438d05e8bb74e0cd2d238 -> trunk/b04e922712080a3652e438d05e8bb74e0cd2d238
2025-09-07T07:36:14.8350371Z  * [new tag]                 trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f -> trunk/b0a3e58dd71c1a039ac0ef51e5bd8f704f632f6f
2025-09-07T07:36:14.8351336Z  * [new tag]                 trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1 -> trunk/b16d3f4c8c01d461c2f01064e9ca5fa2b33f5cf1
2025-09-07T07:36:14.8352341Z  * [new tag]                 trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09 -> trunk/b18bb6796f210a183e687d9d64984a5a9d13cf09
2025-09-07T07:36:14.8353275Z  * [new tag]                 trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de -> trunk/b1bb98ddebdd3e41bf7987372409bdce96ae55de
2025-09-07T07:36:14.8354365Z  * [new tag]                 trunk/b2b4add0e754411372060e1d7b4057a66439172b -> trunk/b2b4add0e754411372060e1d7b4057a66439172b
2025-09-07T07:36:14.8355350Z  * [new tag]                 trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05 -> trunk/b2c7b9ad2dc5a7c0b61febd307761bd5bc2f0f05
2025-09-07T07:36:14.8356410Z  * [new tag]                 trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37 -> trunk/b40d9432be44a6b5974ee62e7d19c3c61c5ece37
2025-09-07T07:36:14.8357418Z  * [new tag]                 trunk/b4ad38279b178b7bd14355123c1101e2e853e77b -> trunk/b4ad38279b178b7bd14355123c1101e2e853e77b
2025-09-07T07:36:14.8358445Z  * [new tag]                 trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde -> trunk/b67c41039835bd9b20b83cd6233e86baaa5f5dde
2025-09-07T07:36:14.8359596Z  * [new tag]                 trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c -> trunk/b6d0a9ea9056ede4f7024dbf3bd6c43be3aff49c
2025-09-07T07:36:14.8360653Z  * [new tag]                 trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734 -> trunk/b7dad7dd49448c88d0751fa2e29c70afe985f734
2025-09-07T07:36:14.8362146Z  * [new tag]                 trunk/b7e207ca9f046ddd716076965a0cce403ba99052 -> trunk/b7e207ca9f046ddd716076965a0cce403ba99052
2025-09-07T07:36:14.8363191Z  * [new tag]                 trunk/b919560c4a7010e2d89facee25586269a994746e -> trunk/b919560c4a7010e2d89facee25586269a994746e
2025-09-07T07:36:14.8364403Z  * [new tag]                 trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354 -> trunk/b9ba612f7a968f7b27e121ca8f4d0a4d954f5354
2025-09-07T07:36:14.8365522Z  * [new tag]                 trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8 -> trunk/ba7f546ccccb5e0b36d9070dc25f26a9647f89f8
2025-09-07T07:36:14.8366531Z  * [new tag]                 trunk/bb950284c7e72905994bc25dd436c10e48088d85 -> trunk/bb950284c7e72905994bc25dd436c10e48088d85
2025-09-07T07:36:14.8367539Z  * [new tag]                 trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d -> trunk/bbedc71fd3267c639c38b4ec25eaa22f973d9c4d
2025-09-07T07:36:14.8368471Z  * [new tag]                 trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37 -> trunk/bc4db2c27fce6ff1648bdc5af31ec225d2a31f37
2025-09-07T07:36:14.8369386Z  * [new tag]                 trunk/bc505977fb66677a09c31155c987330fbb18a865 -> trunk/bc505977fb66677a09c31155c987330fbb18a865
2025-09-07T07:36:14.8370413Z  * [new tag]                 trunk/bd39e47feea7326afb5bbb67fcb1e69279239527 -> trunk/bd39e47feea7326afb5bbb67fcb1e69279239527
2025-09-07T07:36:14.8371493Z  * [new tag]                 trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1 -> trunk/be5b03dde96638f25ffd732a4fed7e41b4cf40e1
2025-09-07T07:36:14.8372512Z  * [new tag]                 trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3 -> trunk/bffc7dd1f374d8408911cd22c6b3d6df39ded9b3
2025-09-07T07:36:14.8373529Z  * [new tag]                 trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf -> trunk/c024b1f5a18d5c5aee5cc2acdd4c52b24b93ffcf
2025-09-07T07:36:14.8374531Z  * [new tag]                 trunk/c0983e6cc0acf71689e1851d12609e00b3f59371 -> trunk/c0983e6cc0acf71689e1851d12609e00b3f59371
2025-09-07T07:36:14.8375501Z  * [new tag]                 trunk/c10195e723eeeedd099ed8b73eda7184ca618fad -> trunk/c10195e723eeeedd099ed8b73eda7184ca618fad
2025-09-07T07:36:14.8376543Z  * [new tag]                 trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99 -> trunk/c157cf6488ade6a7ee2ce2d25b059e1335630a99
2025-09-07T07:36:14.8377527Z  * [new tag]                 trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7 -> trunk/c2a30246172fd71d56529907ffd3c27b76b1f3a7
2025-09-07T07:36:14.8378532Z  * [new tag]                 trunk/c32111149921b48bfef909293f1049e21619ed76 -> trunk/c32111149921b48bfef909293f1049e21619ed76
2025-09-07T07:36:14.8379551Z  * [new tag]                 trunk/c37103234afc832dcad307e9016230810957c9d5 -> trunk/c37103234afc832dcad307e9016230810957c9d5
2025-09-07T07:36:14.8380382Z  * [new tag]                 trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836 -> trunk/c3ceca2995cd35e1376c4b0704669bff1a81e836
2025-09-07T07:36:14.8381428Z  * [new tag]                 trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd -> trunk/c3d54dea9febb1236d48d19e5d4876a63f2e20fd
2025-09-07T07:36:14.8382448Z  * [new tag]                 trunk/c465b3d52c5687fe910d35a5c75341b77f821741 -> trunk/c465b3d52c5687fe910d35a5c75341b77f821741
2025-09-07T07:36:14.8383492Z  * [new tag]                 trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b -> trunk/c5b8a10be5e89396da916d1069ffcb7135f0372b
2025-09-07T07:36:14.8384389Z  * [new tag]                 trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30 -> trunk/c7e41071a08f4045bc11ab60ec366d7357d56e30
2025-09-07T07:36:14.8385430Z  * [new tag]                 trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65 -> trunk/c98ddaca6d2e19ca37aff00c4ff0cda1e9a6ff65
2025-09-07T07:36:14.8386486Z  * [new tag]                 trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b -> trunk/cb1e31362c7b53acf4ac95b9f8878064c184f03b
2025-09-07T07:36:14.8387498Z  * [new tag]                 trunk/cbfb005f7cce79974795b148e265f594f59477c8 -> trunk/cbfb005f7cce79974795b148e265f594f59477c8
2025-09-07T07:36:14.8388680Z  * [new tag]                 trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358 -> trunk/cc5bdd12401bda835291d2f3cb297132ebdbf358
2025-09-07T07:36:14.8389798Z  * [new tag]                 trunk/cd529b686d54bbaa443f5b310140de48422d96c7 -> trunk/cd529b686d54bbaa443f5b310140de48422d96c7
2025-09-07T07:36:14.8390872Z  * [new tag]                 trunk/cec0ff122815582af5302360aff03676558c5c87 -> trunk/cec0ff122815582af5302360aff03676558c5c87
2025-09-07T07:36:14.8391882Z  * [new tag]                 trunk/d11720efdb563d02cf4f7d324311fb15a755268e -> trunk/d11720efdb563d02cf4f7d324311fb15a755268e
2025-09-07T07:36:14.8392911Z  * [new tag]                 trunk/d1706d9128ae24d9048167e80d3fe5196d19035e -> trunk/d1706d9128ae24d9048167e80d3fe5196d19035e
2025-09-07T07:36:14.8393943Z  * [new tag]                 trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d -> trunk/d1a15abfdcaef138f2d9e93a9f46be44f30b766d
2025-09-07T07:36:14.8395118Z  * [new tag]                 trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49 -> trunk/d232a95d4a79404ca05c1f52d37fde7339dcdf49
2025-09-07T07:36:14.8396074Z  * [new tag]                 trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e -> trunk/d2d4c8e9b2371c9aacfb771d9402ac7427b9778e
2025-09-07T07:36:14.8397042Z  * [new tag]                 trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7 -> trunk/d33840c542b387ab08ba49aa6c45aa9567fd9be7
2025-09-07T07:36:14.8398072Z  * [new tag]                 trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1 -> trunk/d5643e8f3a648a99636bfa1f2a41d54bd3c0d0f1
2025-09-07T07:36:14.8399154Z  * [new tag]                 trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7 -> trunk/d5b38410b5b6cf75c7a7389972777a6497926ee7
2025-09-07T07:36:14.8400079Z  * [new tag]                 trunk/d5e0f4202ba14632e4d14862ace096609e763462 -> trunk/d5e0f4202ba14632e4d14862ace096609e763462
2025-09-07T07:36:14.8401121Z  * [new tag]                 trunk/d636c181f9140a7b59be10b36eae23039fc2bb72 -> trunk/d636c181f9140a7b59be10b36eae23039fc2bb72
2025-09-07T07:36:14.8402547Z  * [new tag]                 trunk/d64718503728001a1e78168fd7f2d4ff23e57285 -> trunk/d64718503728001a1e78168fd7f2d4ff23e57285
2025-09-07T07:36:14.8403621Z  * [new tag]                 trunk/d67c29ad22670320d676b02e394274af34e8e643 -> trunk/d67c29ad22670320d676b02e394274af34e8e643
2025-09-07T07:36:14.8404622Z  * [new tag]                 trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95 -> trunk/d6b74568e2c98ce58ecc145b72ac66d4caf7ce95
2025-09-07T07:36:14.8405645Z  * [new tag]                 trunk/d711f27845abd45007ccab6076649ebd896c2661 -> trunk/d711f27845abd45007ccab6076649ebd896c2661
2025-09-07T07:36:14.8406608Z  * [new tag]                 trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab -> trunk/d9d6dde0f42d4bcc8c97671ac50d5096c7e500ab
2025-09-07T07:36:14.8407594Z  * [new tag]                 trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9 -> trunk/da4db4b33d1fdd046650cf19fdbac581a19bf2f9
2025-09-07T07:36:14.8408416Z  * [new tag]                 trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1 -> trunk/dac8a4b91c01c3bbc96f54e621b1ea4ffdbd29d1
2025-09-07T07:36:14.8409629Z  * [new tag]                 trunk/dbec08729fb9848bebed6048c63831b87170d061 -> trunk/dbec08729fb9848bebed6048c63831b87170d061
2025-09-07T07:36:14.8410402Z  * [new tag]                 trunk/dcf385395d838f38c8dca25913578230dd43099a -> trunk/dcf385395d838f38c8dca25913578230dd43099a
2025-09-07T07:36:14.8411447Z  * [new tag]                 trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17 -> trunk/dd2519abe83ec3c40d4797492434e41fe3b47e17
2025-09-07T07:36:14.8412463Z  * [new tag]                 trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d -> trunk/dec72ea4b006dd0fbcaaaa106ad273d73807ab9d
2025-09-07T07:36:14.8413529Z  * [new tag]                 trunk/e0a62b266c021b910ce6dc02a6c9429210487717 -> trunk/e0a62b266c021b910ce6dc02a6c9429210487717
2025-09-07T07:36:14.8414684Z  * [new tag]                 trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228 -> trunk/e19e02c84c9dcc408375e5cae3b0709c18b99228
2025-09-07T07:36:14.8415735Z  * [new tag]                 trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937 -> trunk/e304ea4e69d3a7deeb7e48c7450c214a4c953937
2025-09-07T07:36:14.8416775Z  * [new tag]                 trunk/e3068cdb446adefb5a875616ba37a60235391439 -> trunk/e3068cdb446adefb5a875616ba37a60235391439
2025-09-07T07:36:14.8417750Z  * [new tag]                 trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6 -> trunk/e381d4b0205d5f126c1de534f867ba776f7c3ee6
2025-09-07T07:36:14.8418785Z  * [new tag]                 trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2 -> trunk/e4bd0ff4f8981b805df32ea5b3550621965ea4f2
2025-09-07T07:36:14.8419610Z  * [new tag]                 trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7 -> trunk/e532c9d4f1cdcbc1ea9628f55b9813e77847bdc7
2025-09-07T07:36:14.8420650Z  * [new tag]                 trunk/e92cd9415377403b6e90585e764639e2e0b5973b -> trunk/e92cd9415377403b6e90585e764639e2e0b5973b
2025-09-07T07:36:14.8421759Z  * [new tag]                 trunk/e9481b6617b5576b099d8ca5798111592e9ad090 -> trunk/e9481b6617b5576b099d8ca5798111592e9ad090
2025-09-07T07:36:14.8422518Z  * [new tag]                 trunk/ea1883dfd3e42defe37b11202b878bb76defa087 -> trunk/ea1883dfd3e42defe37b11202b878bb76defa087
2025-09-07T07:36:14.8423549Z  * [new tag]                 trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8 -> trunk/eac3d6f04cfbbebe3d470dacd216da7d4b1f95a8
2025-09-07T07:36:14.8424528Z  * [new tag]                 trunk/eb18d32bda75189494d955aa001ade15f10333de -> trunk/eb18d32bda75189494d955aa001ade15f10333de
2025-09-07T07:36:14.8425453Z  * [new tag]                 trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9 -> trunk/ef3be6726f7ff4b77c22db10cec5b686f9107ea9
2025-09-07T07:36:14.8426525Z  * [new tag]                 trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04 -> trunk/ef8aabd42422725026cb4dbf48aafa9efa226a04
2025-09-07T07:36:14.8428104Z  * [new tag]                 trunk/f00445b43eee57e20bb9316fa796ca23bf73373b -> trunk/f00445b43eee57e20bb9316fa796ca23bf73373b
2025-09-07T07:36:14.8429179Z  * [new tag]                 trunk/f0c391102b754e3b145e8c59231d2df563487e37 -> trunk/f0c391102b754e3b145e8c59231d2df563487e37
2025-09-07T07:36:14.8430225Z  * [new tag]                 trunk/f27985b7e796fb66a1b476284ba42d8cb360a751 -> trunk/f27985b7e796fb66a1b476284ba42d8cb360a751
2025-09-07T07:36:14.8431322Z  * [new tag]                 trunk/f36f285953700f971552083a5da9d0ceacb63bbd -> trunk/f36f285953700f971552083a5da9d0ceacb63bbd
2025-09-07T07:36:14.8432330Z  * [new tag]                 trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb -> trunk/f3cebec39ebc110e1c8b06e741896585f7892dbb
2025-09-07T07:36:14.8433165Z  * [new tag]                 trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c -> trunk/f4c33cd44acac92c0b451a04da20ebe9370e5b0c
2025-09-07T07:36:14.8434256Z  * [new tag]                 trunk/f612045ce105f008b2b675e2fc870163babeb2e8 -> trunk/f612045ce105f008b2b675e2fc870163babeb2e8
2025-09-07T07:36:14.8435278Z  * [new tag]                 trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c -> trunk/f8746b878dfc1e9639d42cbde832e9b9e792c86c
2025-09-07T07:36:14.8436184Z  * [new tag]                 trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c -> trunk/f8ffa9194e26523e5f976d4a824d5cc58922727c
2025-09-07T07:36:14.8437183Z  * [new tag]                 trunk/f981a7fa5230b98974291fdde32fe8488bc5d469 -> trunk/f981a7fa5230b98974291fdde32fe8488bc5d469
2025-09-07T07:36:14.8438198Z  * [new tag]                 trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7 -> trunk/fbf3d2027daabbcb44d0af274b139be2a248a4f7
2025-09-07T07:36:14.8439374Z  * [new tag]                 trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa -> trunk/fca2601c9d628e1bd2d75c7318cd22c4e8c832aa
2025-09-07T07:36:14.8440381Z  * [new tag]                 trunk/fea20775ad96bdca972a1811d7d3372f368614ab -> trunk/fea20775ad96bdca972a1811d7d3372f368614ab
2025-09-07T07:36:14.8441197Z  * [new tag]                 trunk/fefee081642f87419a21dc852f7167d4640443cd -> trunk/fefee081642f87419a21dc852f7167d4640443cd
2025-09-07T07:36:14.8442136Z  * [new tag]                 v0.1.1                      -> v0.1.1
2025-09-07T07:36:14.8443073Z  * [new tag]                 v0.1.10                     -> v0.1.10
2025-09-07T07:36:14.8443955Z  * [new tag]                 v0.1.11                     -> v0.1.11
2025-09-07T07:36:14.8444848Z  * [new tag]                 v0.1.12                     -> v0.1.12
2025-09-07T07:36:14.8445739Z  * [new tag]                 v0.1.2                      -> v0.1.2
2025-09-07T07:36:14.8446579Z  * [new tag]                 v0.1.3                      -> v0.1.3
2025-09-07T07:36:14.8447512Z  * [new tag]                 v0.1.4                      -> v0.1.4
2025-09-07T07:36:14.8448401Z  * [new tag]                 v0.1.5                      -> v0.1.5
2025-09-07T07:36:14.8449305Z  * [new tag]                 v0.1.6                      -> v0.1.6
2025-09-07T07:36:14.8450173Z  * [new tag]                 v0.1.7                      -> v0.1.7
2025-09-07T07:36:14.8451068Z  * [new tag]                 v0.1.8                      -> v0.1.8
2025-09-07T07:36:14.8452016Z  * [new tag]                 v0.1.9                      -> v0.1.9
2025-09-07T07:36:14.8452870Z  * [new tag]                 v0.2.0                      -> v0.2.0
2025-09-07T07:36:14.8453819Z  * [new tag]                 v0.3.0                      -> v0.3.0
2025-09-07T07:36:14.8454815Z  * [new tag]                 v0.3.1                      -> v0.3.1
2025-09-07T07:36:14.8455739Z  * [new tag]                 v0.4.0                      -> v0.4.0
2025-09-07T07:36:14.8456708Z  * [new tag]                 v0.4.1                      -> v0.4.1
2025-09-07T07:36:14.8457641Z  * [new tag]                 v1.0.0                      -> v1.0.0
2025-09-07T07:36:14.8458567Z  * [new tag]                 v1.0.0a0                    -> v1.0.0a0
2025-09-07T07:36:14.8459462Z  * [new tag]                 v1.0.1                      -> v1.0.1
2025-09-07T07:36:14.8460427Z  * [new tag]                 v1.0rc0                     -> v1.0rc0
2025-09-07T07:36:14.8461126Z  * [new tag]                 v1.0rc1                     -> v1.0rc1
2025-09-07T07:36:14.8462131Z  * [new tag]                 v1.1.0                      -> v1.1.0
2025-09-07T07:36:14.8463227Z  * [new tag]                 v1.1.0a0                    -> v1.1.0a0
2025-09-07T07:36:14.8464479Z  * [new tag]                 v1.10.0                     -> v1.10.0
2025-09-07T07:36:14.8465471Z  * [new tag]                 v1.10.0-rc1                 -> v1.10.0-rc1
2025-09-07T07:36:14.8466538Z  * [new tag]                 v1.10.0-rc2                 -> v1.10.0-rc2
2025-09-07T07:36:14.8467219Z  * [new tag]                 v1.10.0-rc3                 -> v1.10.0-rc3
2025-09-07T07:36:14.8468244Z  * [new tag]                 v1.10.1                     -> v1.10.1
2025-09-07T07:36:14.8469097Z  * [new tag]                 v1.10.1-rc1                 -> v1.10.1-rc1
2025-09-07T07:36:14.8469747Z  * [new tag]                 v1.10.2                     -> v1.10.2
2025-09-07T07:36:14.8470508Z  * [new tag]                 v1.10.2-rc1                 -> v1.10.2-rc1
2025-09-07T07:36:14.8471493Z  * [new tag]                 v1.11.0                     -> v1.11.0
2025-09-07T07:36:14.8472500Z  * [new tag]                 v1.11.0-rc1                 -> v1.11.0-rc1
2025-09-07T07:36:14.8473589Z  * [new tag]                 v1.11.0-rc2                 -> v1.11.0-rc2
2025-09-07T07:36:14.8474492Z  * [new tag]                 v1.11.0-rc3                 -> v1.11.0-rc3
2025-09-07T07:36:14.8475493Z  * [new tag]                 v1.11.0-rc4                 -> v1.11.0-rc4
2025-09-07T07:36:14.8476404Z  * [new tag]                 v1.11.0-rc5                 -> v1.11.0-rc5
2025-09-07T07:36:14.8477193Z  * [new tag]                 v1.11.0-rc6                 -> v1.11.0-rc6
2025-09-07T07:36:14.8477865Z  * [new tag]                 v1.11.0-rc7                 -> v1.11.0-rc7
2025-09-07T07:36:14.8478838Z  * [new tag]                 v1.12.0                     -> v1.12.0
2025-09-07T07:36:14.8479798Z  * [new tag]                 v1.12.0-rc1                 -> v1.12.0-rc1
2025-09-07T07:36:14.8480744Z  * [new tag]                 v1.12.0-rc2                 -> v1.12.0-rc2
2025-09-07T07:36:14.8481703Z  * [new tag]                 v1.12.0-rc3                 -> v1.12.0-rc3
2025-09-07T07:36:14.8482658Z  * [new tag]                 v1.12.0-rc4                 -> v1.12.0-rc4
2025-09-07T07:36:14.8483574Z  * [new tag]                 v1.12.0-rc5                 -> v1.12.0-rc5
2025-09-07T07:36:14.8484536Z  * [new tag]                 v1.12.0-rc6                 -> v1.12.0-rc6
2025-09-07T07:36:14.8485352Z  * [new tag]                 v1.12.0-rc7                 -> v1.12.0-rc7
2025-09-07T07:36:14.8486363Z  * [new tag]                 v1.12.0-rc8                 -> v1.12.0-rc8
2025-09-07T07:36:14.8486795Z  * [new tag]                 v1.12.1                     -> v1.12.1
2025-09-07T07:36:14.8487882Z  * [new tag]                 v1.12.1-rc1                 -> v1.12.1-rc1
2025-09-07T07:36:14.8488889Z  * [new tag]                 v1.12.1-rc2                 -> v1.12.1-rc2
2025-09-07T07:36:14.8489933Z  * [new tag]                 v1.12.1-rc3                 -> v1.12.1-rc3
2025-09-07T07:36:14.8490999Z  * [new tag]                 v1.12.1-rc4                 -> v1.12.1-rc4
2025-09-07T07:36:14.8491996Z  * [new tag]                 v1.12.1-rc5                 -> v1.12.1-rc5
2025-09-07T07:36:14.8493025Z  * [new tag]                 v1.13.0                     -> v1.13.0
2025-09-07T07:36:14.8493925Z  * [new tag]                 v1.13.0-rc1                 -> v1.13.0-rc1
2025-09-07T07:36:14.8494819Z  * [new tag]                 v1.13.0-rc2                 -> v1.13.0-rc2
2025-09-07T07:36:14.8495763Z  * [new tag]                 v1.13.0-rc3                 -> v1.13.0-rc3
2025-09-07T07:36:14.8496796Z  * [new tag]                 v1.13.0-rc4                 -> v1.13.0-rc4
2025-09-07T07:36:14.8497867Z  * [new tag]                 v1.13.0-rc5                 -> v1.13.0-rc5
2025-09-07T07:36:14.8498295Z  * [new tag]                 v1.13.0-rc6                 -> v1.13.0-rc6
2025-09-07T07:36:14.8499411Z  * [new tag]                 v1.13.1                     -> v1.13.1
2025-09-07T07:36:14.8500305Z  * [new tag]                 v1.13.1-rc1                 -> v1.13.1-rc1
2025-09-07T07:36:14.8501126Z  * [new tag]                 v1.2.0                      -> v1.2.0
2025-09-07T07:36:14.8502081Z  * [new tag]                 v1.2.0a0                    -> v1.2.0a0
2025-09-07T07:36:14.8503006Z  * [new tag]                 v1.3.0                      -> v1.3.0
2025-09-07T07:36:14.8504032Z  * [new tag]                 v1.3.0a0                    -> v1.3.0a0
2025-09-07T07:36:14.8504815Z  * [new tag]                 v1.3.1                      -> v1.3.1
2025-09-07T07:36:14.8505810Z  * [new tag]                 v1.4.0                      -> v1.4.0
2025-09-07T07:36:14.8506764Z  * [new tag]                 v1.4.0a0                    -> v1.4.0a0
2025-09-07T07:36:14.8507529Z  * [new tag]                 v1.4.1                      -> v1.4.1
2025-09-07T07:36:14.8508683Z  * [new tag]                 v1.5.0                      -> v1.5.0
2025-09-07T07:36:14.8509781Z  * [new tag]                 v1.5.0-rc1                  -> v1.5.0-rc1
2025-09-07T07:36:14.8510757Z  * [new tag]                 v1.5.0-rc2                  -> v1.5.0-rc2
2025-09-07T07:36:14.8511774Z  * [new tag]                 v1.5.0-rc3                  -> v1.5.0-rc3
2025-09-07T07:36:14.8512628Z  * [new tag]                 v1.5.0-rc4                  -> v1.5.0-rc4
2025-09-07T07:36:14.8513533Z  * [new tag]                 v1.5.0-rc5                  -> v1.5.0-rc5
2025-09-07T07:36:14.8514388Z  * [new tag]                 v1.5.1                      -> v1.5.1
2025-09-07T07:36:14.8515194Z  * [new tag]                 v1.5.1-rc1                  -> v1.5.1-rc1
2025-09-07T07:36:14.8515988Z  * [new tag]                 v1.6.0                      -> v1.6.0
2025-09-07T07:36:14.8516927Z  * [new tag]                 v1.6.0-rc1                  -> v1.6.0-rc1
2025-09-07T07:36:14.8517926Z  * [new tag]                 v1.6.0-rc2                  -> v1.6.0-rc2
2025-09-07T07:36:14.8518882Z  * [new tag]                 v1.6.0-rc3                  -> v1.6.0-rc3
2025-09-07T07:36:14.8519837Z  * [new tag]                 v1.6.0-rc4                  -> v1.6.0-rc4
2025-09-07T07:36:14.8520795Z  * [new tag]                 v1.6.0-rc5                  -> v1.6.0-rc5
2025-09-07T07:36:14.8521696Z  * [new tag]                 v1.6.0-rc6                  -> v1.6.0-rc6
2025-09-07T07:36:14.8522397Z  * [new tag]                 v1.6.0-rc7                  -> v1.6.0-rc7
2025-09-07T07:36:14.8523405Z  * [new tag]                 v1.7.0                      -> v1.7.0
2025-09-07T07:36:14.8524482Z  * [new tag]                 v1.7.0-rc1                  -> v1.7.0-rc1
2025-09-07T07:36:14.8525494Z  * [new tag]                 v1.7.0-rc2                  -> v1.7.0-rc2
2025-09-07T07:36:14.8526392Z  * [new tag]                 v1.7.0-rc3                  -> v1.7.0-rc3
2025-09-07T07:36:14.8527282Z  * [new tag]                 v1.7.0-rc4                  -> v1.7.0-rc4
2025-09-07T07:36:14.8528127Z  * [new tag]                 v1.7.1                      -> v1.7.1
2025-09-07T07:36:14.8529307Z  * [new tag]                 v1.7.1-rc1                  -> v1.7.1-rc1
2025-09-07T07:36:14.8530090Z  * [new tag]                 v1.7.1-rc2                  -> v1.7.1-rc2
2025-09-07T07:36:14.8530908Z  * [new tag]                 v1.7.1-rc3                  -> v1.7.1-rc3
2025-09-07T07:36:14.8531820Z  * [new tag]                 v1.8.0                      -> v1.8.0
2025-09-07T07:36:14.8532623Z  * [new tag]                 v1.8.0-rc1                  -> v1.8.0-rc1
2025-09-07T07:36:14.8533585Z  * [new tag]                 v1.8.0-rc2                  -> v1.8.0-rc2
2025-09-07T07:36:14.8534547Z  * [new tag]                 v1.8.0-rc3                  -> v1.8.0-rc3
2025-09-07T07:36:14.8535499Z  * [new tag]                 v1.8.0-rc4                  -> v1.8.0-rc4
2025-09-07T07:36:14.8536282Z  * [new tag]                 v1.8.0-rc5                  -> v1.8.0-rc5
2025-09-07T07:36:14.8537094Z  * [new tag]                 v1.8.1                      -> v1.8.1
2025-09-07T07:36:14.8538033Z  * [new tag]                 v1.8.1-rc1                  -> v1.8.1-rc1
2025-09-07T07:36:14.8538704Z  * [new tag]                 v1.8.1-rc2                  -> v1.8.1-rc2
2025-09-07T07:36:14.8539513Z  * [new tag]                 v1.8.1-rc3                  -> v1.8.1-rc3
2025-09-07T07:36:14.8540826Z  * [new tag]                 v1.8.2                      -> v1.8.2
2025-09-07T07:36:14.8541617Z  * [new tag]                 v1.8.2-rc1                  -> v1.8.2-rc1
2025-09-07T07:36:14.8542600Z  * [new tag]                 v1.9.0                      -> v1.9.0
2025-09-07T07:36:14.8543521Z  * [new tag]                 v1.9.0-rc1                  -> v1.9.0-rc1
2025-09-07T07:36:14.8544529Z  * [new tag]                 v1.9.0-rc2                  -> v1.9.0-rc2
2025-09-07T07:36:14.8545625Z  * [new tag]                 v1.9.0-rc3                  -> v1.9.0-rc3
2025-09-07T07:36:14.8546393Z  * [new tag]                 v1.9.0-rc4                  -> v1.9.0-rc4
2025-09-07T07:36:14.8547412Z  * [new tag]                 v1.9.1                      -> v1.9.1
2025-09-07T07:36:14.8548500Z  * [new tag]                 v1.9.1-rc1                  -> v1.9.1-rc1
2025-09-07T07:36:14.8549196Z  * [new tag]                 v1.9.1-rc2                  -> v1.9.1-rc2
2025-09-07T07:36:14.8550243Z  * [new tag]                 v2.0.0                      -> v2.0.0
2025-09-07T07:36:14.8551508Z  * [new tag]                 v2.0.0-rc1                  -> v2.0.0-rc1
2025-09-07T07:36:14.8552532Z  * [new tag]                 v2.0.0-rc2                  -> v2.0.0-rc2
2025-09-07T07:36:14.8553517Z  * [new tag]                 v2.0.0-rc3                  -> v2.0.0-rc3
2025-09-07T07:36:14.8554515Z  * [new tag]                 v2.0.0-rc4                  -> v2.0.0-rc4
2025-09-07T07:36:14.8555560Z  * [new tag]                 v2.0.0-rc5                  -> v2.0.0-rc5
2025-09-07T07:36:14.8556338Z  * [new tag]                 v2.0.0-rc6                  -> v2.0.0-rc6
2025-09-07T07:36:14.8557535Z  * [new tag]                 v2.0.1                      -> v2.0.1
2025-09-07T07:36:14.8558573Z  * [new tag]                 v2.0.1-rc1                  -> v2.0.1-rc1
2025-09-07T07:36:14.8559279Z  * [new tag]                 v2.0.1-rc2                  -> v2.0.1-rc2
2025-09-07T07:36:14.8560179Z  * [new tag]                 v2.0.1-rc3                  -> v2.0.1-rc3
2025-09-07T07:36:14.8560938Z  * [new tag]                 v2.0.1-rc4                  -> v2.0.1-rc4
2025-09-07T07:36:14.8562304Z  * [new tag]                 v2.1.0                      -> v2.1.0
2025-09-07T07:36:14.8563201Z  * [new tag]                 v2.1.0-rc1                  -> v2.1.0-rc1
2025-09-07T07:36:14.8564146Z  * [new tag]                 v2.1.0-rc2                  -> v2.1.0-rc2
2025-09-07T07:36:14.8565183Z  * [new tag]                 v2.1.0-rc3                  -> v2.1.0-rc3
2025-09-07T07:36:14.8566174Z  * [new tag]                 v2.1.0-rc4                  -> v2.1.0-rc4
2025-09-07T07:36:14.8567143Z  * [new tag]                 v2.1.0-rc5                  -> v2.1.0-rc5
2025-09-07T07:36:14.8568362Z  * [new tag]                 v2.1.0-rc6                  -> v2.1.0-rc6
2025-09-07T07:36:14.8568869Z  * [new tag]                 v2.1.1                      -> v2.1.1
2025-09-07T07:36:14.8569819Z  * [new tag]                 v2.1.1-rc1                  -> v2.1.1-rc1
2025-09-07T07:36:14.8570699Z  * [new tag]                 v2.1.1-rc2                  -> v2.1.1-rc2
2025-09-07T07:36:14.8571759Z  * [new tag]                 v2.1.1-rc3                  -> v2.1.1-rc3
2025-09-07T07:36:14.8572757Z  * [new tag]                 v2.1.1-rc4                  -> v2.1.1-rc4
2025-09-07T07:36:14.8573637Z  * [new tag]                 v2.1.1-rc5                  -> v2.1.1-rc5
2025-09-07T07:36:14.8574414Z  * [new tag]                 v2.1.1-rc6                  -> v2.1.1-rc6
2025-09-07T07:36:14.8575355Z  * [new tag]                 v2.1.2                      -> v2.1.2
2025-09-07T07:36:14.8576428Z  * [new tag]                 v2.1.2-rc1                  -> v2.1.2-rc1
2025-09-07T07:36:14.8577442Z  * [new tag]                 v2.1.2-rc2                  -> v2.1.2-rc2
2025-09-07T07:36:14.8578315Z  * [new tag]                 v2.1.2-rc3                  -> v2.1.2-rc3
2025-09-07T07:36:14.8579197Z  * [new tag]                 v2.2.0                      -> v2.2.0
2025-09-07T07:36:14.8580161Z  * [new tag]                 v2.2.0-rc1                  -> v2.2.0-rc1
2025-09-07T07:36:14.8581086Z  * [new tag]                 v2.2.0-rc2                  -> v2.2.0-rc2
2025-09-07T07:36:14.8582015Z  * [new tag]                 v2.2.0-rc3                  -> v2.2.0-rc3
2025-09-07T07:36:14.8582886Z  * [new tag]                 v2.2.0-rc4                  -> v2.2.0-rc4
2025-09-07T07:36:14.8583822Z  * [new tag]                 v2.2.0-rc5                  -> v2.2.0-rc5
2025-09-07T07:36:14.8584744Z  * [new tag]                 v2.2.0-rc6                  -> v2.2.0-rc6
2025-09-07T07:36:14.8585615Z  * [new tag]                 v2.2.0-rc7                  -> v2.2.0-rc7
2025-09-07T07:36:14.8586322Z  * [new tag]                 v2.2.0-rc8                  -> v2.2.0-rc8
2025-09-07T07:36:14.8587428Z  * [new tag]                 v2.2.1                      -> v2.2.1
2025-09-07T07:36:14.8588395Z  * [new tag]                 v2.2.1-rc1                  -> v2.2.1-rc1
2025-09-07T07:36:14.8589231Z  * [new tag]                 v2.2.1-rc2                  -> v2.2.1-rc2
2025-09-07T07:36:14.8589952Z  * [new tag]                 v2.2.1-rc3                  -> v2.2.1-rc3
2025-09-07T07:36:14.8590601Z  * [new tag]                 v2.2.2                      -> v2.2.2
2025-09-07T07:36:14.8591645Z  * [new tag]                 v2.2.2-rc1                  -> v2.2.2-rc1
2025-09-07T07:36:14.8592419Z  * [new tag]                 v2.2.2-rc2                  -> v2.2.2-rc2
2025-09-07T07:36:14.8593194Z  * [new tag]                 v2.2.2-rc3                  -> v2.2.2-rc3
2025-09-07T07:36:14.8594174Z  * [new tag]                 v2.3.0                      -> v2.3.0
2025-09-07T07:36:14.8595095Z  * [new tag]                 v2.3.0-rc1                  -> v2.3.0-rc1
2025-09-07T07:36:14.8596065Z  * [new tag]                 v2.3.0-rc10                 -> v2.3.0-rc10
2025-09-07T07:36:14.8597115Z  * [new tag]                 v2.3.0-rc11                 -> v2.3.0-rc11
2025-09-07T07:36:14.8597997Z  * [new tag]                 v2.3.0-rc12                 -> v2.3.0-rc12
2025-09-07T07:36:14.8598973Z  * [new tag]                 v2.3.0-rc2                  -> v2.3.0-rc2
2025-09-07T07:36:14.8600090Z  * [new tag]                 v2.3.0-rc3                  -> v2.3.0-rc3
2025-09-07T07:36:14.8601079Z  * [new tag]                 v2.3.0-rc4                  -> v2.3.0-rc4
2025-09-07T07:36:14.8602212Z  * [new tag]                 v2.3.0-rc5                  -> v2.3.0-rc5
2025-09-07T07:36:14.8603114Z  * [new tag]                 v2.3.0-rc6                  -> v2.3.0-rc6
2025-09-07T07:36:14.8604083Z  * [new tag]                 v2.3.0-rc7                  -> v2.3.0-rc7
2025-09-07T07:36:14.8605045Z  * [new tag]                 v2.3.0-rc8                  -> v2.3.0-rc8
2025-09-07T07:36:14.8605879Z  * [new tag]                 v2.3.0-rc9                  -> v2.3.0-rc9
2025-09-07T07:36:14.8606874Z  * [new tag]                 v2.3.1                      -> v2.3.1
2025-09-07T07:36:14.8607547Z  * [new tag]                 v2.3.1-rc1                  -> v2.3.1-rc1
2025-09-07T07:36:14.8608499Z  * [new tag]                 v2.3.1-rc2                  -> v2.3.1-rc2
2025-09-07T07:36:14.8609472Z  * [new tag]                 v2.3.1-rc3                  -> v2.3.1-rc3
2025-09-07T07:36:14.8610416Z  * [new tag]                 v2.4.0                      -> v2.4.0
2025-09-07T07:36:14.8611785Z  * [new tag]                 v2.4.0-rc1                  -> v2.4.0-rc1
2025-09-07T07:36:14.8612745Z  * [new tag]                 v2.4.0-rc2                  -> v2.4.0-rc2
2025-09-07T07:36:14.8613662Z  * [new tag]                 v2.4.0-rc3                  -> v2.4.0-rc3
2025-09-07T07:36:14.8614599Z  * [new tag]                 v2.4.0-rc4                  -> v2.4.0-rc4
2025-09-07T07:36:14.8615593Z  * [new tag]                 v2.4.0-rc5                  -> v2.4.0-rc5
2025-09-07T07:36:14.8616552Z  * [new tag]                 v2.4.0-rc6                  -> v2.4.0-rc6
2025-09-07T07:36:14.8617555Z  * [new tag]                 v2.4.0-rc7                  -> v2.4.0-rc7
2025-09-07T07:36:14.8618463Z  * [new tag]                 v2.4.0-rc8                  -> v2.4.0-rc8
2025-09-07T07:36:14.8619488Z  * [new tag]                 v2.4.0-rc9                  -> v2.4.0-rc9
2025-09-07T07:36:14.8620265Z  * [new tag]                 v2.4.1                      -> v2.4.1
2025-09-07T07:36:14.8621266Z  * [new tag]                 v2.4.1-rc1                  -> v2.4.1-rc1
2025-09-07T07:36:14.8622210Z  * [new tag]                 v2.4.1-rc2                  -> v2.4.1-rc2
2025-09-07T07:36:14.8623287Z  * [new tag]                 v2.4.1-rc3                  -> v2.4.1-rc3
2025-09-07T07:36:14.8624224Z  * [new tag]                 v2.5.0                      -> v2.5.0
2025-09-07T07:36:14.8625121Z  * [new tag]                 v2.5.0-rc1                  -> v2.5.0-rc1
2025-09-07T07:36:14.8626015Z  * [new tag]                 v2.5.0-rc10                 -> v2.5.0-rc10
2025-09-07T07:36:14.8627001Z  * [new tag]                 v2.5.0-rc2                  -> v2.5.0-rc2
2025-09-07T07:36:14.8627943Z  * [new tag]                 v2.5.0-rc3                  -> v2.5.0-rc3
2025-09-07T07:36:14.8628873Z  * [new tag]                 v2.5.0-rc4                  -> v2.5.0-rc4
2025-09-07T07:36:14.8629847Z  * [new tag]                 v2.5.0-rc5                  -> v2.5.0-rc5
2025-09-07T07:36:14.8630823Z  * [new tag]                 v2.5.0-rc6                  -> v2.5.0-rc6
2025-09-07T07:36:14.8631861Z  * [new tag]                 v2.5.0-rc7                  -> v2.5.0-rc7
2025-09-07T07:36:14.8632747Z  * [new tag]                 v2.5.0-rc8                  -> v2.5.0-rc8
2025-09-07T07:36:14.8633677Z  * [new tag]                 v2.5.0-rc9                  -> v2.5.0-rc9
2025-09-07T07:36:14.8634484Z  * [new tag]                 v2.5.1                      -> v2.5.1
2025-09-07T07:36:14.8635187Z  * [new tag]                 v2.5.1-rc1                  -> v2.5.1-rc1
2025-09-07T07:36:14.8636065Z  * [new tag]                 v2.6.0                      -> v2.6.0
2025-09-07T07:36:14.8637081Z  * [new tag]                 v2.6.0-rc1                  -> v2.6.0-rc1
2025-09-07T07:36:14.8638078Z  * [new tag]                 v2.6.0-rc2                  -> v2.6.0-rc2
2025-09-07T07:36:14.8639037Z  * [new tag]                 v2.6.0-rc3                  -> v2.6.0-rc3
2025-09-07T07:36:14.8640037Z  * [new tag]                 v2.6.0-rc4                  -> v2.6.0-rc4
2025-09-07T07:36:14.8641140Z  * [new tag]                 v2.6.0-rc5                  -> v2.6.0-rc5
2025-09-07T07:36:14.8642160Z  * [new tag]                 v2.6.0-rc6                  -> v2.6.0-rc6
2025-09-07T07:36:14.8643157Z  * [new tag]                 v2.6.0-rc7                  -> v2.6.0-rc7
2025-09-07T07:36:14.8644135Z  * [new tag]                 v2.6.0-rc8                  -> v2.6.0-rc8
2025-09-07T07:36:14.8645131Z  * [new tag]                 v2.6.0-rc9                  -> v2.6.0-rc9
2025-09-07T07:36:14.8646447Z  * [new tag]                 v2.7.0                      -> v2.7.0
2025-09-07T07:36:14.8647250Z  * [new tag]                 v2.7.0-rc1                  -> v2.7.0-rc1
2025-09-07T07:36:14.8648085Z  * [new tag]                 v2.7.0-rc10                 -> v2.7.0-rc10
2025-09-07T07:36:14.8649051Z  * [new tag]                 v2.7.0-rc2                  -> v2.7.0-rc2
2025-09-07T07:36:14.8650194Z  * [new tag]                 v2.7.0-rc3                  -> v2.7.0-rc3
2025-09-07T07:36:14.8651167Z  * [new tag]                 v2.7.0-rc4                  -> v2.7.0-rc4
2025-09-07T07:36:14.8652107Z  * [new tag]                 v2.7.0-rc5                  -> v2.7.0-rc5
2025-09-07T07:36:14.8653042Z  * [new tag]                 v2.7.0-rc6                  -> v2.7.0-rc6
2025-09-07T07:36:14.8653992Z  * [new tag]                 v2.7.0-rc7                  -> v2.7.0-rc7
2025-09-07T07:36:14.8655019Z  * [new tag]                 v2.7.0-rc8                  -> v2.7.0-rc8
2025-09-07T07:36:14.8656013Z  * [new tag]                 v2.7.0-rc9                  -> v2.7.0-rc9
2025-09-07T07:36:14.8656899Z  * [new tag]                 v2.7.1                      -> v2.7.1
2025-09-07T07:36:14.8657794Z  * [new tag]                 v2.7.1-rc1                  -> v2.7.1-rc1
2025-09-07T07:36:14.8658776Z  * [new tag]                 v2.7.1-rc2                  -> v2.7.1-rc2
2025-09-07T07:36:14.8659779Z  * [new tag]                 v2.7.1-rc3                  -> v2.7.1-rc3
2025-09-07T07:36:14.8660923Z  * [new tag]                 v2.7.1-rc4                  -> v2.7.1-rc4
2025-09-07T07:36:14.8661898Z  * [new tag]                 v2.7.1-rc5                  -> v2.7.1-rc5
2025-09-07T07:36:14.8662715Z  * [new tag]                 v2.8.0                      -> v2.8.0
2025-09-07T07:36:14.8663694Z  * [new tag]                 v2.8.0-rc1                  -> v2.8.0-rc1
2025-09-07T07:36:14.8664676Z  * [new tag]                 v2.8.0-rc2                  -> v2.8.0-rc2
2025-09-07T07:36:14.8665777Z  * [new tag]                 v2.8.0-rc3                  -> v2.8.0-rc3
2025-09-07T07:36:14.8666821Z  * [new tag]                 v2.8.0-rc4                  -> v2.8.0-rc4
2025-09-07T07:36:14.8667927Z  * [new tag]                 v2.8.0-rc5                  -> v2.8.0-rc5
2025-09-07T07:36:14.8668909Z  * [new tag]                 v2.8.0-rc6                  -> v2.8.0-rc6
2025-09-07T07:36:14.8669893Z  * [new tag]                 v2.8.0-rc7                  -> v2.8.0-rc7
2025-09-07T07:36:14.8670834Z  * [new tag]                 v2.8.0-rc8                  -> v2.8.0-rc8
2025-09-07T07:36:14.8671817Z  * [new tag]                 whc_flight_1                -> whc_flight_1
2025-09-07T07:36:14.8672824Z  * [new tag]                 whc_flight_2                -> whc_flight_2
2025-09-07T07:36:14.8674154Z  * [new tag]                 whc_flight_4                -> whc_flight_4
2025-09-07T07:36:14.9508670Z [command]/usr/bin/git rev-parse --verify --quiet 93fb23d6fae7c4e82c4239a1033e522088742634^{object}
2025-09-07T07:36:14.9537468Z 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:36:14.9541594Z ##[endgroup]
2025-09-07T07:36:14.9541915Z ##[group]Determining the checkout info
2025-09-07T07:36:14.9542686Z ##[endgroup]
2025-09-07T07:36:14.9546814Z [command]/usr/bin/git sparse-checkout disable
2025-09-07T07:36:14.9591814Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig
2025-09-07T07:36:14.9622854Z ##[group]Checking out the ref
2025-09-07T07:36:14.9625637Z [command]/usr/bin/git checkout --progress --force 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:36:15.9835850Z Updating files:  84% (16467/19405)
2025-09-07T07:36:15.9980808Z Updating files:  85% (16495/19405)
2025-09-07T07:36:16.0110669Z Updating files:  86% (16689/19405)
2025-09-07T07:36:16.0239408Z Updating files:  87% (16883/19405)
2025-09-07T07:36:16.0341341Z Updating files:  88% (17077/19405)
2025-09-07T07:36:16.0473031Z Updating files:  89% (17271/19405)
2025-09-07T07:36:16.0628738Z Updating files:  90% (17465/19405)
2025-09-07T07:36:16.0741662Z Updating files:  91% (17659/19405)
2025-09-07T07:36:16.0875858Z Updating files:  92% (17853/19405)
2025-09-07T07:36:16.1043926Z Updating files:  93% (18047/19405)
2025-09-07T07:36:16.1229109Z Updating files:  94% (18241/19405)
2025-09-07T07:36:16.1372371Z Updating files:  95% (18435/19405)
2025-09-07T07:36:16.1515991Z Updating files:  96% (18629/19405)
2025-09-07T07:36:16.1679067Z Updating files:  97% (18823/19405)
2025-09-07T07:36:16.1907670Z Updating files:  98% (19017/19405)
2025-09-07T07:36:16.2051187Z Updating files:  99% (19211/19405)
2025-09-07T07:36:16.2052073Z Updating files: 100% (19405/19405)
2025-09-07T07:36:16.2052350Z Updating files: 100% (19405/19405), done.
2025-09-07T07:36:16.2256790Z Note: switching to '93fb23d6fae7c4e82c4239a1033e522088742634'.
2025-09-07T07:36:16.2257014Z 
2025-09-07T07:36:16.2257169Z You are in 'detached HEAD' state. You can look around, make experimental
2025-09-07T07:36:16.2257529Z changes and commit them, and you can discard any commits you make in this
2025-09-07T07:36:16.2257884Z state without impacting any branches by switching back to a branch.
2025-09-07T07:36:16.2258086Z 
2025-09-07T07:36:16.2258218Z If you want to create a new branch to retain commits you create, you may
2025-09-07T07:36:16.2258544Z do so (now or later) by using -c with the switch command. Example:
2025-09-07T07:36:16.2258720Z 
2025-09-07T07:36:16.2258808Z   git switch -c <new-branch-name>
2025-09-07T07:36:16.2258938Z 
2025-09-07T07:36:16.2259011Z Or undo this operation with:
2025-09-07T07:36:16.2259133Z 
2025-09-07T07:36:16.2259195Z   git switch -
2025-09-07T07:36:16.2259291Z 
2025-09-07T07:36:16.2259443Z Turn off this advice by setting config variable advice.detachedHead to false
2025-09-07T07:36:16.2259655Z 
2025-09-07T07:36:16.2259779Z HEAD is now at 93fb23d6fae Build vLLM nightly wheels (#162000)
2025-09-07T07:36:16.2366805Z ##[endgroup]
2025-09-07T07:36:16.2367521Z ##[group]Setting up auth for fetching submodules
2025-09-07T07:36:16.2372264Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic ***
2025-09-07T07:36:16.2419451Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf
2025-09-07T07:36:16.2449630Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com:
2025-09-07T07:36:16.2480981Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com:
2025-09-07T07:36:16.2510873Z ##[endgroup]
2025-09-07T07:36:16.2511190Z ##[group]Fetching submodules
2025-09-07T07:36:16.2513542Z [command]/usr/bin/git submodule sync --recursive
2025-09-07T07:36:16.2883183Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive
2025-09-07T07:36:16.3240483Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni'
2025-09-07T07:36:16.3241603Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16'
2025-09-07T07:36:16.3530798Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv'
2025-09-07T07:36:16.3533669Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK'
2025-09-07T07:36:16.3537111Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX'
2025-09-07T07:36:16.3541302Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator'
2025-09-07T07:36:16.3544811Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK'
2025-09-07T07:36:16.3550310Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter'
2025-09-07T07:36:16.3559223Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark'
2025-09-07T07:36:16.3563437Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel'
2025-09-07T07:36:16.3566848Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib'
2025-09-07T07:36:16.3570726Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo'
2025-09-07T07:36:16.3574693Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend'
2025-09-07T07:36:16.3578608Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass'
2025-09-07T07:36:16.3582653Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm'
2025-09-07T07:36:16.3591564Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention'
2025-09-07T07:36:16.3595616Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers'
2025-09-07T07:36:16.3600054Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt'
2025-09-07T07:36:16.3606977Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp'
2025-09-07T07:36:16.3611302Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo'
2025-09-07T07:36:16.3615755Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest'
2025-09-07T07:36:16.3625052Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep'
2025-09-07T07:36:16.3629727Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi'
2025-09-07T07:36:16.3634274Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto'
2025-09-07T07:36:16.3638904Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai'
2025-09-07T07:36:16.3643664Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc'
2025-09-07T07:36:16.3648345Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann'
2025-09-07T07:36:16.3653122Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx'
2025-09-07T07:36:16.3663296Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp'
2025-09-07T07:36:16.3668223Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft'
2025-09-07T07:36:16.3673265Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf'
2025-09-07T07:36:16.3678271Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd'
2025-09-07T07:36:16.3683681Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool'
2025-09-07T07:36:16.3688806Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11'
2025-09-07T07:36:16.3699526Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy'
2025-09-07T07:36:16.3707736Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef'
2025-09-07T07:36:16.3713451Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe'
2025-09-07T07:36:16.3755089Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/android/libs/fbjni'...
2025-09-07T07:36:16.5768139Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FXdiv'...
2025-09-07T07:36:16.5768654Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FP16'...
2025-09-07T07:36:16.5769088Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/psimd'...
2025-09-07T07:36:16.5769503Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NNPACK'...
2025-09-07T07:36:16.5853254Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NVTX'...
2025-09-07T07:36:16.7254375Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pocketfft'...
2025-09-07T07:36:16.7254938Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pthreadpool'...
2025-09-07T07:36:16.7255427Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/python-peachpy'...
2025-09-07T07:36:16.7255864Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep'...
2025-09-07T07:36:16.7256311Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'...
2025-09-07T07:36:16.7256748Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gloo'...
2025-09-07T07:36:16.7334510Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'...
2025-09-07T07:36:17.3432720Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/benchmark'...
2025-09-07T07:36:17.3433262Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe'...
2025-09-07T07:36:17.3433996Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ittapi'...
2025-09-07T07:36:17.3434435Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kleidiai'...
2025-09-07T07:36:17.3434921Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention'...
2025-09-07T07:36:17.3435374Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpp-httplib'...
2025-09-07T07:36:17.3435798Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpuinfo'...
2025-09-07T07:36:17.3436219Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/googletest'...
2025-09-07T07:36:17.3436630Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/sleef'...
2025-09-07T07:36:17.3437036Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/mimalloc'...
2025-09-07T07:36:17.3437453Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pybind11'...
2025-09-07T07:36:17.3437866Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fmt'...
2025-09-07T07:36:17.3438284Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cudnn_frontend'...
2025-09-07T07:36:17.4432321Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/XNNPACK'...
2025-09-07T07:36:25.3720621Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto'...
2025-09-07T07:36:25.3721172Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flatbuffers'...
2025-09-07T07:36:25.3721615Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm'...
2025-09-07T07:36:25.3722031Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cutlass'...
2025-09-07T07:36:25.3722442Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx'...
2025-09-07T07:36:25.3722928Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/composable_kernel'...
2025-09-07T07:36:25.3723673Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter'...
2025-09-07T07:36:25.3724120Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp'...
2025-09-07T07:36:25.3724566Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/nlohmann'...
2025-09-07T07:36:25.3724981Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf'...
2025-09-07T07:36:25.3903934Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f'
2025-09-07T07:36:25.4053380Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3'
2025-09-07T07:36:25.4166737Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1'
2025-09-07T07:36:25.4441158Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73'
2025-09-07T07:36:25.5195763Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07'
2025-09-07T07:36:25.5744777Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1'
2025-09-07T07:36:26.3173807Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883'
2025-09-07T07:36:26.4668480Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150'
2025-09-07T07:36:26.4696421Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel'
2025-09-07T07:36:26.4734052Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'...
2025-09-07T07:36:29.5181907Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf'
2025-09-07T07:36:29.5453804Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f'
2025-09-07T07:36:29.8723884Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977'
2025-09-07T07:36:29.9207789Z Submodule path 'third_party/cpp-httplib': checked out '89c932f313c6437c38f2982869beacc89c2f2246'
2025-09-07T07:36:30.0132915Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d'
2025-09-07T07:36:30.0580259Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6'
2025-09-07T07:36:30.6629859Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491'
2025-09-07T07:36:30.8094806Z Submodule path 'third_party/fbgemm': checked out '4b39c551efe15e6bbade20565b0ceb2d8ce3352d'
2025-09-07T07:36:30.8123196Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit'
2025-09-07T07:36:30.8125109Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel'
2025-09-07T07:36:30.8127892Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo'
2025-09-07T07:36:30.8130975Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass'
2025-09-07T07:36:30.8134116Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest'
2025-09-07T07:36:30.8137232Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch'
2025-09-07T07:36:30.8140118Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json'
2025-09-07T07:36:30.8179326Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'...
2025-09-07T07:36:31.9259332Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'...
2025-09-07T07:36:31.9259953Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'...
2025-09-07T07:36:31.9260478Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'...
2025-09-07T07:36:31.9261024Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'...
2025-09-07T07:36:32.0259228Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'...
2025-09-07T07:36:32.3684733Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/json'...
2025-09-07T07:36:35.7339121Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea'
2025-09-07T07:36:36.0014104Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9'
2025-09-07T07:36:36.0952008Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349'
2025-09-07T07:36:36.6937053Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '311f3c8e51dc0eb56310cfc6980bf63d0fbd7917'
2025-09-07T07:36:36.7396720Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723'
2025-09-07T07:36:36.7540283Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out '63b6a7b541fa7f08f8475ca7d74054db36ff2691'
2025-09-07T07:36:36.8793600Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03'
2025-09-07T07:36:36.9541418Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5'
2025-09-07T07:36:36.9566066Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel'
2025-09-07T07:36:36.9567494Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass'
2025-09-07T07:36:36.9605734Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'...
2025-09-07T07:36:39.6580802Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'...
2025-09-07T07:36:39.9059795Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33'
2025-09-07T07:36:40.4476927Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420'
2025-09-07T07:36:40.5922681Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757'
2025-09-07T07:36:40.6255916Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21'
2025-09-07T07:36:40.6649258Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350'
2025-09-07T07:36:40.6923704Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2'
2025-09-07T07:36:40.7375120Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723'
2025-09-07T07:36:40.7528198Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3'
2025-09-07T07:36:40.7552022Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn'
2025-09-07T07:36:40.7581541Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'...
2025-09-07T07:36:51.6347597Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d'
2025-09-07T07:36:51.6586986Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959'
2025-09-07T07:36:51.7405919Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658'
2025-09-07T07:36:51.7432348Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog'
2025-09-07T07:36:51.7433590Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt'
2025-09-07T07:36:51.7436639Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest'
2025-09-07T07:36:51.7476457Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'...
2025-09-07T07:36:52.2982732Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'...
2025-09-07T07:36:52.5069937Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'...
2025-09-07T07:36:52.5844902Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e'
2025-09-07T07:36:52.5869090Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-09-07T07:36:52.5870621Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-09-07T07:36:52.5873538Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-09-07T07:36:52.5876531Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-09-07T07:36:52.5879597Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-09-07T07:36:52.5882756Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-09-07T07:36:52.5885882Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-09-07T07:36:52.5889197Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-09-07T07:36:52.5929141Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'...
2025-09-07T07:36:53.6777634Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'...
2025-09-07T07:36:53.6778435Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'...
2025-09-07T07:36:53.6779150Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'...
2025-09-07T07:36:53.6779820Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'...
2025-09-07T07:36:53.6780513Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'...
2025-09-07T07:36:53.6781199Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'...
2025-09-07T07:36:53.7777983Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'...
2025-09-07T07:36:57.6395900Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9'
2025-09-07T07:36:57.6610043Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400'
2025-09-07T07:36:57.6986947Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05'
2025-09-07T07:36:57.7152159Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067'
2025-09-07T07:36:57.7172570Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-09-07T07:36:57.7207817Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'...
2025-09-07T07:36:57.9797793Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4'
2025-09-07T07:36:58.0010909Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446'
2025-09-07T07:36:58.0418781Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850'
2025-09-07T07:36:58.1409429Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5'
2025-09-07T07:36:58.1609239Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150'
2025-09-07T07:36:58.2003452Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164'
2025-09-07T07:36:58.2553729Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347'
2025-09-07T07:36:58.3002853Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7'
2025-09-07T07:36:58.3403005Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e'
2025-09-07T07:36:58.4500561Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72'
2025-09-07T07:36:58.9027768Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83'
2025-09-07T07:36:58.9070153Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/onnx/third_party/pybind11'
2025-09-07T07:36:58.9107208Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx/third_party/pybind11'...
2025-09-07T07:36:59.7029686Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4'
2025-09-07T07:36:59.7808312Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878'
2025-09-07T07:36:59.7834987Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark) registered for path 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T07:36:59.7837090Z Submodule 'third_party/googletest' (https://github.com/google/googletest) registered for path 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T07:36:59.7840366Z Submodule 'third_party/ms-gsl' (https://github.com/microsoft/GSL) registered for path 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T07:36:59.7843417Z Submodule 'third_party/nlohmann-json' (https://github.com/nlohmann/json) registered for path 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T07:36:59.7847225Z Submodule 'third_party/opentelemetry-proto' (https://github.com/open-telemetry/opentelemetry-proto) registered for path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T07:36:59.7849531Z Submodule 'third_party/opentracing-cpp' (https://github.com/opentracing/opentracing-cpp.git) registered for path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T07:36:59.7852518Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T07:36:59.7855728Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T07:36:59.7894902Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'...
2025-09-07T07:37:00.4412695Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'...
2025-09-07T07:37:00.4413472Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'...
2025-09-07T07:37:00.4426744Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'...
2025-09-07T07:37:00.4427437Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'...
2025-09-07T07:37:00.5413129Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'...
2025-09-07T07:37:00.8408843Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'...
2025-09-07T07:37:05.1561839Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'...
2025-09-07T07:37:05.7899992Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2'
2025-09-07T07:37:05.8305468Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1'
2025-09-07T07:37:05.8486088Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa'
2025-09-07T07:37:05.9531937Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d'
2025-09-07T07:37:05.9702381Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce'
2025-09-07T07:37:05.9884424Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5'
2025-09-07T07:37:06.0071797Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d'
2025-09-07T07:37:06.0093672Z Submodule 'civetweb' (https://github.com/civetweb/civetweb.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T07:37:06.0096107Z Submodule 'googletest' (https://github.com/google/googletest.git) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T07:37:06.0131917Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'...
2025-09-07T07:37:07.2930601Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'...
2025-09-07T07:37:07.5165313Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4'
2025-09-07T07:37:07.5632479Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929'
2025-09-07T07:37:08.0931234Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50'
2025-09-07T07:37:08.1076865Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa'
2025-09-07T07:37:08.3696903Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a'
2025-09-07T07:37:08.3726968Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/protobuf/third_party/benchmark'
2025-09-07T07:37:08.3728649Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/protobuf/third_party/googletest'
2025-09-07T07:37:08.3767385Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf/third_party/benchmark'...
2025-09-07T07:37:09.0156792Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf/third_party/googletest'...
2025-09-07T07:37:09.3155309Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8'
2025-09-07T07:37:09.3823220Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081'
2025-09-07T07:37:09.3944802Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900'
2025-09-07T07:37:09.4090803Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8'
2025-09-07T07:37:09.4508337Z Submodule path 'third_party/pybind11': checked out 'f5fbe867d2d26e4a0a9177a51f6e568868ad3dc8'
2025-09-07T07:37:09.4799600Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67'
2025-09-07T07:37:09.5229015Z Submodule path 'third_party/sleef': checked out '5a1d179df9cf652951b59010a2d2075372d67f68'
2025-09-07T07:37:09.5534251Z Submodule path 'third_party/tensorpipe': checked out 'af0118d13e52f5a08841464a768e01a0bf3e3075'
2025-09-07T07:37:09.5558617Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/tensorpipe/third_party/googletest'
2025-09-07T07:37:09.5559839Z Submodule 'third_party/libnop' (https://github.com/google/libnop.git) registered for path 'third_party/tensorpipe/third_party/libnop'
2025-09-07T07:37:09.5562709Z Submodule 'third_party/libuv' (https://github.com/libuv/libuv.git) registered for path 'third_party/tensorpipe/third_party/libuv'
2025-09-07T07:37:09.5565797Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/tensorpipe/third_party/pybind11'
2025-09-07T07:37:09.5603721Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/googletest'...
2025-09-07T07:37:10.7282491Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/libnop'...
2025-09-07T07:37:10.8088852Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/libuv'...
2025-09-07T07:37:10.9051261Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe/third_party/pybind11'...
2025-09-07T07:37:10.9591263Z Submodule path 'third_party/tensorpipe/third_party/googletest': checked out 'aee0f9d9b5b87796ee8a0ab26b7587ec30e8858e'
2025-09-07T07:37:10.9775703Z Submodule path 'third_party/tensorpipe/third_party/libnop': checked out '910b55815be16109f04f4180e9adee14fb4ce281'
2025-09-07T07:37:11.0487206Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '5152db2cbfeb5582e9c27c5ea1dba2cd9e10759b'
2025-09-07T07:37:11.0802299Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef'
2025-09-07T07:37:11.0824705Z Submodule 'tools/clang' (https://github.com/wjakob/clang-cindex-python3) registered for path 'third_party/tensorpipe/third_party/pybind11/tools/clang'
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2025-09-07T07:37:11.5208073Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5'
2025-09-07T07:37:11.5253514Z [command]/usr/bin/git submodule foreach --recursive git config --local gc.auto 0
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2025-09-07T07:37:11.9613665Z ##[endgroup]
2025-09-07T07:37:11.9613972Z ##[group]Persisting credentials for submodules
2025-09-07T07:37:11.9619776Z [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' || :"
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2025-09-07T07:37:12.2857212Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-09-07T07:37:12.2922264Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-09-07T07:37:12.2989948Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-09-07T07:37:12.3052858Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-09-07T07:37:12.3121167Z Entering 'third_party/kleidiai'
2025-09-07T07:37:12.3187331Z Entering 'third_party/mimalloc'
2025-09-07T07:37:12.3253647Z Entering 'third_party/nlohmann'
2025-09-07T07:37:12.3319404Z Entering 'third_party/onnx'
2025-09-07T07:37:12.3401282Z Entering 'third_party/onnx/third_party/pybind11'
2025-09-07T07:37:12.3466824Z Entering 'third_party/opentelemetry-cpp'
2025-09-07T07:37:12.3533180Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T07:37:12.3601091Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T07:37:12.3663835Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T07:37:12.3727962Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T07:37:12.3794898Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T07:37:12.3857562Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T07:37:12.3920208Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T07:37:12.3982849Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T07:37:12.4046536Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T07:37:12.4114819Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T07:37:12.4196042Z Entering 'third_party/pocketfft'
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2025-09-07T07:37:12.4398855Z Entering 'third_party/protobuf/third_party/googletest'
2025-09-07T07:37:12.4467762Z Entering 'third_party/psimd'
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2025-09-07T07:37:12.4663897Z Entering 'third_party/python-peachpy'
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2025-09-07T07:37:12.4794187Z Entering 'third_party/tensorpipe'
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2025-09-07T07:37:12.5114102Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T07:37:12.5201825Z [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"
2025-09-07T07:37:12.5548775Z Entering 'android/libs/fbjni'
2025-09-07T07:37:12.5610201Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config	remote.origin.url
2025-09-07T07:37:12.5631044Z Entering 'third_party/FP16'
2025-09-07T07:37:12.5692454Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config	remote.origin.url
2025-09-07T07:37:12.5711933Z Entering 'third_party/FXdiv'
2025-09-07T07:37:12.5771937Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config	remote.origin.url
2025-09-07T07:37:12.5791280Z Entering 'third_party/NNPACK'
2025-09-07T07:37:12.5855092Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config	remote.origin.url
2025-09-07T07:37:12.5874701Z Entering 'third_party/NVTX'
2025-09-07T07:37:12.5933953Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config	remote.origin.url
2025-09-07T07:37:12.5953873Z Entering 'third_party/VulkanMemoryAllocator'
2025-09-07T07:37:12.6015931Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config	remote.origin.url
2025-09-07T07:37:12.6035425Z Entering 'third_party/XNNPACK'
2025-09-07T07:37:12.6097691Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config	remote.origin.url
2025-09-07T07:37:12.6130273Z Entering 'third_party/aiter'
2025-09-07T07:37:12.6192568Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/aiter/config	remote.origin.url
2025-09-07T07:37:12.6212254Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-09-07T07:37:12.6274521Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config	remote.origin.url
2025-09-07T07:37:12.6303895Z Entering 'third_party/benchmark'
2025-09-07T07:37:12.6364054Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config	remote.origin.url
2025-09-07T07:37:12.6384340Z Entering 'third_party/composable_kernel'
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2025-09-07T07:37:12.6550358Z Entering 'third_party/cpuinfo'
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2025-09-07T07:37:12.6629986Z Entering 'third_party/cudnn_frontend'
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2025-09-07T07:37:12.6711570Z Entering 'third_party/cutlass'
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2025-09-07T07:37:12.6798325Z Entering 'third_party/fbgemm'
2025-09-07T07:37:12.6859408Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config	remote.origin.url
2025-09-07T07:37:12.6881829Z Entering 'third_party/fbgemm/external/asmjit'
2025-09-07T07:37:12.6940716Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config	remote.origin.url
2025-09-07T07:37:12.6959727Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-09-07T07:37:12.7020780Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config	remote.origin.url
2025-09-07T07:37:12.7045794Z Entering 'third_party/fbgemm/external/cpuinfo'
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2025-09-07T07:37:12.7126863Z Entering 'third_party/fbgemm/external/cutlass'
2025-09-07T07:37:12.7185697Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config	remote.origin.url
2025-09-07T07:37:12.7212469Z Entering 'third_party/fbgemm/external/googletest'
2025-09-07T07:37:12.7270008Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config	remote.origin.url
2025-09-07T07:37:12.7292036Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-09-07T07:37:12.7354035Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config	remote.origin.url
2025-09-07T07:37:12.7372411Z Entering 'third_party/fbgemm/external/json'
2025-09-07T07:37:12.7432067Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config	remote.origin.url
2025-09-07T07:37:12.7456219Z Entering 'third_party/flash-attention'
2025-09-07T07:37:12.7519157Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config	remote.origin.url
2025-09-07T07:37:12.7539351Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-09-07T07:37:12.7597275Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config	remote.origin.url
2025-09-07T07:37:12.7622259Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-09-07T07:37:12.7680900Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config	remote.origin.url
2025-09-07T07:37:12.7710967Z Entering 'third_party/flatbuffers'
2025-09-07T07:37:12.7773029Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config	remote.origin.url
2025-09-07T07:37:12.7795880Z Entering 'third_party/fmt'
2025-09-07T07:37:12.7858503Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/fmt/config	remote.origin.url
2025-09-07T07:37:12.7878819Z Entering 'third_party/gemmlowp/gemmlowp'
2025-09-07T07:37:12.7938301Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config	remote.origin.url
2025-09-07T07:37:12.7959437Z Entering 'third_party/gloo'
2025-09-07T07:37:12.8019660Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/gloo/config	remote.origin.url
2025-09-07T07:37:12.8039590Z Entering 'third_party/googletest'
2025-09-07T07:37:12.8100705Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/googletest/config	remote.origin.url
2025-09-07T07:37:12.8118861Z Entering 'third_party/ideep'
2025-09-07T07:37:12.8179735Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/ideep/config	remote.origin.url
2025-09-07T07:37:12.8199517Z Entering 'third_party/ideep/mkl-dnn'
2025-09-07T07:37:12.8258055Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config	remote.origin.url
2025-09-07T07:37:12.8286281Z Entering 'third_party/ittapi'
2025-09-07T07:37:12.8346599Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config	remote.origin.url
2025-09-07T07:37:12.8365568Z Entering 'third_party/kineto'
2025-09-07T07:37:12.8426030Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/config	remote.origin.url
2025-09-07T07:37:12.8445777Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-09-07T07:37:12.8507401Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config	remote.origin.url
2025-09-07T07:37:12.8526351Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-09-07T07:37:12.8586779Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config	remote.origin.url
2025-09-07T07:37:12.8610007Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-09-07T07:37:12.8669199Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config	remote.origin.url
2025-09-07T07:37:12.8690002Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-09-07T07:37:12.8748424Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config	remote.origin.url
2025-09-07T07:37:12.8767925Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-09-07T07:37:12.8830768Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config	remote.origin.url
2025-09-07T07:37:12.8848012Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-09-07T07:37:12.8907760Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config	remote.origin.url
2025-09-07T07:37:12.8929992Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-09-07T07:37:12.8988513Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config	remote.origin.url
2025-09-07T07:37:12.9008551Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-09-07T07:37:12.9067847Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config	remote.origin.url
2025-09-07T07:37:12.9086935Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-09-07T07:37:12.9150778Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/json/config	remote.origin.url
2025-09-07T07:37:12.9170267Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-09-07T07:37:12.9230241Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/pfs/config	remote.origin.url
2025-09-07T07:37:12.9253737Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-09-07T07:37:12.9313955Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/fmt/config	remote.origin.url
2025-09-07T07:37:12.9332440Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-09-07T07:37:12.9391840Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/googletest/config	remote.origin.url
2025-09-07T07:37:12.9415049Z Entering 'third_party/kleidiai'
2025-09-07T07:37:12.9475460Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/kleidiai/config	remote.origin.url
2025-09-07T07:37:12.9498505Z Entering 'third_party/mimalloc'
2025-09-07T07:37:12.9557570Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/mimalloc/config	remote.origin.url
2025-09-07T07:37:12.9578081Z Entering 'third_party/nlohmann'
2025-09-07T07:37:12.9640118Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/nlohmann/config	remote.origin.url
2025-09-07T07:37:12.9660273Z Entering 'third_party/onnx'
2025-09-07T07:37:12.9722885Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/onnx/config	remote.origin.url
2025-09-07T07:37:12.9754235Z Entering 'third_party/onnx/third_party/pybind11'
2025-09-07T07:37:12.9813173Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/onnx/modules/third_party/pybind11/config	remote.origin.url
2025-09-07T07:37:12.9837345Z Entering 'third_party/opentelemetry-cpp'
2025-09-07T07:37:12.9898983Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/config	remote.origin.url
2025-09-07T07:37:12.9918762Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T07:37:12.9977360Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/benchmark/config	remote.origin.url
2025-09-07T07:37:12.9998265Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T07:37:13.0058708Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/googletest/config	remote.origin.url
2025-09-07T07:37:13.0077912Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T07:37:13.0138788Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/ms-gsl/config	remote.origin.url
2025-09-07T07:37:13.0157105Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T07:37:13.0217137Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/nlohmann-json/config	remote.origin.url
2025-09-07T07:37:13.0237360Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T07:37:13.0296093Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentelemetry-proto/config	remote.origin.url
2025-09-07T07:37:13.0316724Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T07:37:13.0375472Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/opentracing-cpp/config	remote.origin.url
2025-09-07T07:37:13.0393630Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T07:37:13.0452846Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/config	remote.origin.url
2025-09-07T07:37:13.0471129Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T07:37:13.0531058Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/civetweb/config	remote.origin.url
2025-09-07T07:37:13.0551556Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T07:37:13.0611231Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/third_party/prometheus-cpp/modules/googletest/config	remote.origin.url
2025-09-07T07:37:13.0633338Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T07:37:13.0690502Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/opentelemetry-cpp/modules/tools/vcpkg/config	remote.origin.url
2025-09-07T07:37:13.0727514Z Entering 'third_party/pocketfft'
2025-09-07T07:37:13.0786928Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/pocketfft/config	remote.origin.url
2025-09-07T07:37:13.0807089Z Entering 'third_party/protobuf'
2025-09-07T07:37:13.0868211Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/protobuf/config	remote.origin.url
2025-09-07T07:37:13.0888946Z Entering 'third_party/protobuf/third_party/benchmark'
2025-09-07T07:37:13.0947251Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/benchmark/config	remote.origin.url
2025-09-07T07:37:13.0966131Z Entering 'third_party/protobuf/third_party/googletest'
2025-09-07T07:37:13.1027985Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/protobuf/modules/third_party/googletest/config	remote.origin.url
2025-09-07T07:37:13.1050994Z Entering 'third_party/psimd'
2025-09-07T07:37:13.1113884Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/psimd/config	remote.origin.url
2025-09-07T07:37:13.1133820Z Entering 'third_party/pthreadpool'
2025-09-07T07:37:13.1194668Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/pthreadpool/config	remote.origin.url
2025-09-07T07:37:13.1214581Z Entering 'third_party/pybind11'
2025-09-07T07:37:13.1274787Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/pybind11/config	remote.origin.url
2025-09-07T07:37:13.1294911Z Entering 'third_party/python-peachpy'
2025-09-07T07:37:13.1355830Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/python-peachpy/config	remote.origin.url
2025-09-07T07:37:13.1376142Z Entering 'third_party/sleef'
2025-09-07T07:37:13.1434589Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/sleef/config	remote.origin.url
2025-09-07T07:37:13.1454770Z Entering 'third_party/tensorpipe'
2025-09-07T07:37:13.1514204Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/config	remote.origin.url
2025-09-07T07:37:13.1534593Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-09-07T07:37:13.1593927Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/googletest/config	remote.origin.url
2025-09-07T07:37:13.1612852Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-09-07T07:37:13.1671626Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libnop/config	remote.origin.url
2025-09-07T07:37:13.1691297Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-09-07T07:37:13.1750565Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/libuv/config	remote.origin.url
2025-09-07T07:37:13.1770514Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-09-07T07:37:13.1830089Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/config	remote.origin.url
2025-09-07T07:37:13.1847329Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T07:37:13.1909067Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/tensorpipe/modules/third_party/pybind11/modules/tools/clang/config	remote.origin.url
2025-09-07T07:37:13.2925590Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'git@github.com:'
2025-09-07T07:37:13.3289332Z Entering 'android/libs/fbjni'
2025-09-07T07:37:13.3340517Z Entering 'third_party/FP16'
2025-09-07T07:37:13.3392434Z Entering 'third_party/FXdiv'
2025-09-07T07:37:13.3443212Z Entering 'third_party/NNPACK'
2025-09-07T07:37:13.3493416Z Entering 'third_party/NVTX'
2025-09-07T07:37:13.3542873Z Entering 'third_party/VulkanMemoryAllocator'
2025-09-07T07:37:13.3591732Z Entering 'third_party/XNNPACK'
2025-09-07T07:37:13.3651789Z Entering 'third_party/aiter'
2025-09-07T07:37:13.3703201Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-09-07T07:37:13.3759450Z Entering 'third_party/benchmark'
2025-09-07T07:37:13.3809134Z Entering 'third_party/composable_kernel'
2025-09-07T07:37:13.3863557Z Entering 'third_party/cpp-httplib'
2025-09-07T07:37:13.3912176Z Entering 'third_party/cpuinfo'
2025-09-07T07:37:13.3960708Z Entering 'third_party/cudnn_frontend'
2025-09-07T07:37:13.4011183Z Entering 'third_party/cutlass'
2025-09-07T07:37:13.4065518Z Entering 'third_party/fbgemm'
2025-09-07T07:37:13.4115155Z Entering 'third_party/fbgemm/external/asmjit'
2025-09-07T07:37:13.4163489Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-09-07T07:37:13.4217029Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-09-07T07:37:13.4265290Z Entering 'third_party/fbgemm/external/cutlass'
2025-09-07T07:37:13.4320024Z Entering 'third_party/fbgemm/external/googletest'
2025-09-07T07:37:13.4366193Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-09-07T07:37:13.4417626Z Entering 'third_party/fbgemm/external/json'
2025-09-07T07:37:13.4469916Z Entering 'third_party/flash-attention'
2025-09-07T07:37:13.4523312Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-09-07T07:37:13.4575793Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-09-07T07:37:13.4635811Z Entering 'third_party/flatbuffers'
2025-09-07T07:37:13.4689072Z Entering 'third_party/fmt'
2025-09-07T07:37:13.4737352Z Entering 'third_party/gemmlowp/gemmlowp'
2025-09-07T07:37:13.4787343Z Entering 'third_party/gloo'
2025-09-07T07:37:13.4835691Z Entering 'third_party/googletest'
2025-09-07T07:37:13.4883088Z Entering 'third_party/ideep'
2025-09-07T07:37:13.4931077Z Entering 'third_party/ideep/mkl-dnn'
2025-09-07T07:37:13.4987329Z Entering 'third_party/ittapi'
2025-09-07T07:37:13.5035540Z Entering 'third_party/kineto'
2025-09-07T07:37:13.5085345Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-09-07T07:37:13.5133611Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-09-07T07:37:13.5182573Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-09-07T07:37:13.5231762Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-09-07T07:37:13.5279898Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-09-07T07:37:13.5329538Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-09-07T07:37:13.5380721Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-09-07T07:37:13.5432893Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-09-07T07:37:13.5479927Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-09-07T07:37:13.5529986Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-09-07T07:37:13.5581127Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-09-07T07:37:13.5630149Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-09-07T07:37:13.5681013Z Entering 'third_party/kleidiai'
2025-09-07T07:37:13.5729482Z Entering 'third_party/mimalloc'
2025-09-07T07:37:13.5777685Z Entering 'third_party/nlohmann'
2025-09-07T07:37:13.5830071Z Entering 'third_party/onnx'
2025-09-07T07:37:13.5891748Z Entering 'third_party/onnx/third_party/pybind11'
2025-09-07T07:37:13.5946836Z Entering 'third_party/opentelemetry-cpp'
2025-09-07T07:37:13.5998432Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T07:37:13.6046014Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T07:37:13.6093932Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T07:37:13.6142019Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T07:37:13.6191171Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T07:37:13.6246020Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T07:37:13.6293884Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T07:37:13.6341133Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T07:37:13.6389908Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T07:37:13.6441557Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T07:37:13.6508721Z Entering 'third_party/pocketfft'
2025-09-07T07:37:13.6557175Z Entering 'third_party/protobuf'
2025-09-07T07:37:13.6608744Z Entering 'third_party/protobuf/third_party/benchmark'
2025-09-07T07:37:13.6656517Z Entering 'third_party/protobuf/third_party/googletest'
2025-09-07T07:37:13.6707624Z Entering 'third_party/psimd'
2025-09-07T07:37:13.6755004Z Entering 'third_party/pthreadpool'
2025-09-07T07:37:13.6806718Z Entering 'third_party/pybind11'
2025-09-07T07:37:13.6853818Z Entering 'third_party/python-peachpy'
2025-09-07T07:37:13.6910244Z Entering 'third_party/sleef'
2025-09-07T07:37:13.6961503Z Entering 'third_party/tensorpipe'
2025-09-07T07:37:13.7011169Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-09-07T07:37:13.7058195Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-09-07T07:37:13.7107274Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-09-07T07:37:13.7154808Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-09-07T07:37:13.7205684Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T07:37:13.7274041Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:'
2025-09-07T07:37:13.7634578Z Entering 'android/libs/fbjni'
2025-09-07T07:37:13.7682643Z Entering 'third_party/FP16'
2025-09-07T07:37:13.7733325Z Entering 'third_party/FXdiv'
2025-09-07T07:37:13.7784889Z Entering 'third_party/NNPACK'
2025-09-07T07:37:13.7836486Z Entering 'third_party/NVTX'
2025-09-07T07:37:13.7887077Z Entering 'third_party/VulkanMemoryAllocator'
2025-09-07T07:37:13.7936809Z Entering 'third_party/XNNPACK'
2025-09-07T07:37:13.7997394Z Entering 'third_party/aiter'
2025-09-07T07:37:13.8050798Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-09-07T07:37:13.8106562Z Entering 'third_party/benchmark'
2025-09-07T07:37:13.8155755Z Entering 'third_party/composable_kernel'
2025-09-07T07:37:13.8212739Z Entering 'third_party/cpp-httplib'
2025-09-07T07:37:13.8260523Z Entering 'third_party/cpuinfo'
2025-09-07T07:37:13.8309502Z Entering 'third_party/cudnn_frontend'
2025-09-07T07:37:13.8357707Z Entering 'third_party/cutlass'
2025-09-07T07:37:13.8416857Z Entering 'third_party/fbgemm'
2025-09-07T07:37:13.8470577Z Entering 'third_party/fbgemm/external/asmjit'
2025-09-07T07:37:13.8517890Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-09-07T07:37:13.8572134Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-09-07T07:37:13.8622527Z Entering 'third_party/fbgemm/external/cutlass'
2025-09-07T07:37:13.8680863Z Entering 'third_party/fbgemm/external/googletest'
2025-09-07T07:37:13.8733057Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-09-07T07:37:13.8780953Z Entering 'third_party/fbgemm/external/json'
2025-09-07T07:37:13.8836291Z Entering 'third_party/flash-attention'
2025-09-07T07:37:13.8888068Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-09-07T07:37:13.8942413Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-09-07T07:37:13.9001448Z Entering 'third_party/flatbuffers'
2025-09-07T07:37:13.9054403Z Entering 'third_party/fmt'
2025-09-07T07:37:13.9103535Z Entering 'third_party/gemmlowp/gemmlowp'
2025-09-07T07:37:13.9152491Z Entering 'third_party/gloo'
2025-09-07T07:37:13.9203237Z Entering 'third_party/googletest'
2025-09-07T07:37:13.9252455Z Entering 'third_party/ideep'
2025-09-07T07:37:13.9302500Z Entering 'third_party/ideep/mkl-dnn'
2025-09-07T07:37:13.9355911Z Entering 'third_party/ittapi'
2025-09-07T07:37:13.9404212Z Entering 'third_party/kineto'
2025-09-07T07:37:13.9452484Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-09-07T07:37:13.9501714Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-09-07T07:37:13.9552316Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-09-07T07:37:13.9600751Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-09-07T07:37:13.9646474Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-09-07T07:37:13.9698062Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-09-07T07:37:13.9752726Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-09-07T07:37:13.9802654Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-09-07T07:37:13.9850550Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-09-07T07:37:13.9902313Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-09-07T07:37:13.9952788Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-09-07T07:37:13.9999077Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-09-07T07:37:14.0051615Z Entering 'third_party/kleidiai'
2025-09-07T07:37:14.0105346Z Entering 'third_party/mimalloc'
2025-09-07T07:37:14.0152650Z Entering 'third_party/nlohmann'
2025-09-07T07:37:14.0203776Z Entering 'third_party/onnx'
2025-09-07T07:37:14.0265289Z Entering 'third_party/onnx/third_party/pybind11'
2025-09-07T07:37:14.0317440Z Entering 'third_party/opentelemetry-cpp'
2025-09-07T07:37:14.0371755Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T07:37:14.0423909Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T07:37:14.0473543Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T07:37:14.0521732Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T07:37:14.0570072Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T07:37:14.0617256Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T07:37:14.0664544Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T07:37:14.0715362Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T07:37:14.0765861Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T07:37:14.0817377Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T07:37:14.0882607Z Entering 'third_party/pocketfft'
2025-09-07T07:37:14.0933548Z Entering 'third_party/protobuf'
2025-09-07T07:37:14.0985300Z Entering 'third_party/protobuf/third_party/benchmark'
2025-09-07T07:37:14.1033384Z Entering 'third_party/protobuf/third_party/googletest'
2025-09-07T07:37:14.1084766Z Entering 'third_party/psimd'
2025-09-07T07:37:14.1135097Z Entering 'third_party/pthreadpool'
2025-09-07T07:37:14.1183985Z Entering 'third_party/pybind11'
2025-09-07T07:37:14.1235315Z Entering 'third_party/python-peachpy'
2025-09-07T07:37:14.1286218Z Entering 'third_party/sleef'
2025-09-07T07:37:14.1335145Z Entering 'third_party/tensorpipe'
2025-09-07T07:37:14.1384555Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-09-07T07:37:14.1432926Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-09-07T07:37:14.1480055Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-09-07T07:37:14.1527780Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-09-07T07:37:14.1575814Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T07:37:14.1642619Z ##[endgroup]
2025-09-07T07:37:14.1683003Z [command]/usr/bin/git log -1 --format=%H
2025-09-07T07:37:14.1710145Z 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:37:14.1810983Z ##[group]Run cd "${GITHUB_WORKSPACE}"
2025-09-07T07:37:14.1811237Z cd "${GITHUB_WORKSPACE}"
2025-09-07T07:37:14.1811442Z # Clean stale submodule dirs
2025-09-07T07:37:14.1811668Z if [ -z "${NO_SUDO}" ]; then
2025-09-07T07:37:14.1811910Z   sudo git submodule foreach --recursive git clean -ffdx
2025-09-07T07:37:14.1812153Z else
2025-09-07T07:37:14.1812529Z   git submodule foreach --recursive git clean -ffdx
2025-09-07T07:37:14.1812760Z fi
2025-09-07T07:37:14.1824361Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:14.1824604Z env:
2025-09-07T07:37:14.1824755Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:14.1824930Z   NO_SUDO: true
2025-09-07T07:37:14.1825080Z ##[endgroup]
2025-09-07T07:37:14.2212410Z Entering 'android/libs/fbjni'
2025-09-07T07:37:14.2252290Z Entering 'third_party/FP16'
2025-09-07T07:37:14.2291666Z Entering 'third_party/FXdiv'
2025-09-07T07:37:14.2329650Z Entering 'third_party/NNPACK'
2025-09-07T07:37:14.2368654Z Entering 'third_party/NVTX'
2025-09-07T07:37:14.2412821Z Entering 'third_party/VulkanMemoryAllocator'
2025-09-07T07:37:14.2450580Z Entering 'third_party/XNNPACK'
2025-09-07T07:37:14.2575363Z Entering 'third_party/aiter'
2025-09-07T07:37:14.2623119Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-09-07T07:37:14.2740631Z Entering 'third_party/benchmark'
2025-09-07T07:37:14.2780410Z Entering 'third_party/composable_kernel'
2025-09-07T07:37:14.2907648Z Entering 'third_party/cpp-httplib'
2025-09-07T07:37:14.2947667Z Entering 'third_party/cpuinfo'
2025-09-07T07:37:14.2991028Z Entering 'third_party/cudnn_frontend'
2025-09-07T07:37:14.3030356Z Entering 'third_party/cutlass'
2025-09-07T07:37:14.3134001Z Entering 'third_party/fbgemm'
2025-09-07T07:37:14.3201181Z Entering 'third_party/fbgemm/external/asmjit'
2025-09-07T07:37:14.3237253Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-09-07T07:37:14.3351602Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-09-07T07:37:14.3395733Z Entering 'third_party/fbgemm/external/cutlass'
2025-09-07T07:37:14.3500301Z Entering 'third_party/fbgemm/external/googletest'
2025-09-07T07:37:14.3539502Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-09-07T07:37:14.3574003Z Entering 'third_party/fbgemm/external/json'
2025-09-07T07:37:14.3625337Z Entering 'third_party/flash-attention'
2025-09-07T07:37:14.3671655Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-09-07T07:37:14.3781017Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-09-07T07:37:14.3874586Z Entering 'third_party/flatbuffers'
2025-09-07T07:37:14.3956580Z Entering 'third_party/fmt'
2025-09-07T07:37:14.3996518Z Entering 'third_party/gemmlowp/gemmlowp'
2025-09-07T07:37:14.4049279Z Entering 'third_party/gloo'
2025-09-07T07:37:14.4074372Z Entering 'third_party/googletest'
2025-09-07T07:37:14.4118492Z Entering 'third_party/ideep'
2025-09-07T07:37:14.4153598Z Entering 'third_party/ideep/mkl-dnn'
2025-09-07T07:37:14.4244956Z Entering 'third_party/ittapi'
2025-09-07T07:37:14.4284461Z Entering 'third_party/kineto'
2025-09-07T07:37:14.4325919Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-09-07T07:37:14.4366016Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-09-07T07:37:14.4417811Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-09-07T07:37:14.4455915Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-09-07T07:37:14.4494982Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-09-07T07:37:14.4532166Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-09-07T07:37:14.4569569Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-09-07T07:37:14.4609216Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-09-07T07:37:14.4646541Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-09-07T07:37:14.4692134Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-09-07T07:37:14.4733761Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-09-07T07:37:14.4770531Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-09-07T07:37:14.4811492Z Entering 'third_party/kleidiai'
2025-09-07T07:37:14.4855085Z Entering 'third_party/mimalloc'
2025-09-07T07:37:14.4893419Z Entering 'third_party/nlohmann'
2025-09-07T07:37:14.4944120Z Entering 'third_party/onnx'
2025-09-07T07:37:14.5311638Z Entering 'third_party/onnx/third_party/pybind11'
2025-09-07T07:37:14.5357238Z Entering 'third_party/opentelemetry-cpp'
2025-09-07T07:37:14.5422350Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T07:37:14.5462443Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T07:37:14.5500460Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T07:37:14.5535463Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T07:37:14.5584680Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T07:37:14.5623206Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T07:37:14.5658794Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T07:37:14.5697645Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T07:37:14.5753141Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T07:37:14.5794928Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T07:37:14.6081749Z Entering 'third_party/pocketfft'
2025-09-07T07:37:14.6120793Z Entering 'third_party/protobuf'
2025-09-07T07:37:14.6210758Z Entering 'third_party/protobuf/third_party/benchmark'
2025-09-07T07:37:14.6249016Z Entering 'third_party/protobuf/third_party/googletest'
2025-09-07T07:37:14.6292833Z Entering 'third_party/psimd'
2025-09-07T07:37:14.6332304Z Entering 'third_party/pthreadpool'
2025-09-07T07:37:14.6368931Z Entering 'third_party/pybind11'
2025-09-07T07:37:14.6411927Z Entering 'third_party/python-peachpy'
2025-09-07T07:37:14.6448746Z Entering 'third_party/sleef'
2025-09-07T07:37:14.6488893Z Entering 'third_party/tensorpipe'
2025-09-07T07:37:14.6529131Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-09-07T07:37:14.6566432Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-09-07T07:37:14.6602040Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-09-07T07:37:14.6641330Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-09-07T07:37:14.6676410Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T07:37:14.6818401Z Prepare all required actions
2025-09-07T07:37:14.6818803Z Getting action download info
2025-09-07T07:37:14.7968628Z ##[group]Run ./.github/actions/setup-linux
2025-09-07T07:37:14.7968859Z env:
2025-09-07T07:37:14.7969012Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:14.7969184Z ##[endgroup]
2025-09-07T07:37:14.8000298Z ##[group]Run set -euo pipefail
2025-09-07T07:37:14.8000543Z set -euo pipefail
2025-09-07T07:37:14.8000749Z function get_ec2_metadata() {
2025-09-07T07:37:14.8001005Z   # Pulled from instance metadata endpoint for EC2
2025-09-07T07:37:14.8001432Z   # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html
2025-09-07T07:37:14.8001787Z   category=$1
2025-09-07T07:37:14.8002030Z   # If it is GCP runner (runner name contains gcp), do not run this
2025-09-07T07:37:14.8002307Z   runner_name_str=i-04e43c8796a0bfd2e
2025-09-07T07:37:14.8002577Z   if [[ -f /.inarc ]]; then
2025-09-07T07:37:14.8002813Z     echo "ARC Runner, no info on ec2 metadata"
2025-09-07T07:37:14.8003061Z   elif [[ $runner_name_str == *"gcp"* ]]; then
2025-09-07T07:37:14.8003363Z     echo "Runner is from Google Cloud Platform, No info on ec2 metadata"
2025-09-07T07:37:14.8003641Z   else
2025-09-07T07:37:14.8004179Z     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}"
2025-09-07T07:37:14.8004736Z   fi
2025-09-07T07:37:14.8004875Z }
2025-09-07T07:37:14.8005051Z echo "ami-id: $(get_ec2_metadata ami-id)"
2025-09-07T07:37:14.8005330Z echo "instance-id: $(get_ec2_metadata instance-id)"
2025-09-07T07:37:14.8005633Z echo "instance-type: $(get_ec2_metadata instance-type)"
2025-09-07T07:37:14.8005891Z echo "system info $(uname -a)"
2025-09-07T07:37:14.8013265Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:14.8013508Z env:
2025-09-07T07:37:14.8013668Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:14.8013841Z ##[endgroup]
2025-09-07T07:37:14.8180306Z ami-id: ami-05ffe3c48a9991133
2025-09-07T07:37:14.8295800Z instance-id: i-04e43c8796a0bfd2e
2025-09-07T07:37:14.8410853Z instance-type: m7a.24xlarge
2025-09-07T07:37:14.8424447Z system info Linux ip-10-0-74-111.ec2.internal 6.1.141-155.222.amzn2023.x86_64 #1 SMP PREEMPT_DYNAMIC Tue Jun 17 10:29:47 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux
2025-09-07T07:37:14.8444417Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-09-07T07:37:14.8445045Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-09-07T07:37:14.8453486Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:14.8453759Z env:
2025-09-07T07:37:14.8453909Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:14.8454091Z ##[endgroup]
2025-09-07T07:37:14.8523598Z ##[group]Run if systemctl is-active --quiet docker; then
2025-09-07T07:37:14.8523894Z if systemctl is-active --quiet docker; then
2025-09-07T07:37:14.8524150Z     echo "Docker daemon is running...";
2025-09-07T07:37:14.8524372Z else
2025-09-07T07:37:14.8524604Z     echo "Starting docker daemon..." && sudo systemctl start docker;
2025-09-07T07:37:14.8525043Z fi
2025-09-07T07:37:14.8531810Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:14.8532063Z env:
2025-09-07T07:37:14.8532204Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:14.8532378Z ##[endgroup]
2025-09-07T07:37:14.8617703Z Docker daemon is running...
2025-09-07T07:37:14.8649549Z ##[group]Run nick-fields/retry@v3.0.0
2025-09-07T07:37:14.8649771Z with:
2025-09-07T07:37:14.8649910Z   shell: bash
2025-09-07T07:37:14.8650278Z   timeout_minutes: 5
2025-09-07T07:37:14.8650445Z   max_attempts: 3
2025-09-07T07:37:14.8650611Z   retry_wait_seconds: 30
2025-09-07T07:37:14.8652068Z   command: AWS_ACCOUNT_ID=$(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

2025-09-07T07:37:14.8653514Z   polling_interval_seconds: 1
2025-09-07T07:37:14.8653705Z   warning_on_retry: true
2025-09-07T07:37:14.8653874Z   continue_on_error: false
2025-09-07T07:37:14.8654048Z env:
2025-09-07T07:37:14.8654195Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:14.8654372Z   AWS_RETRY_MODE: standard
2025-09-07T07:37:14.8654534Z   AWS_MAX_ATTEMPTS: 5
2025-09-07T07:37:14.8654707Z   AWS_DEFAULT_REGION: us-east-1
2025-09-07T07:37:14.8654890Z ##[endgroup]
2025-09-07T07:37:15.9105627Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-09-07T07:37:15.9106060Z Configure a credential helper to remove this warning. See
2025-09-07T07:37:15.9106450Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-09-07T07:37:15.9106743Z 
2025-09-07T07:37:15.9106834Z Login Succeeded
2025-09-07T07:37:16.0691264Z Command completed after 1 attempt(s).
2025-09-07T07:37:16.0746406Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-09-07T07:37:16.0746769Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-09-07T07:37:16.0747065Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-09-07T07:37:16.0755868Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:16.0756112Z env:
2025-09-07T07:37:16.0756270Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:16.0756455Z ##[endgroup]
2025-09-07T07:37:16.0849999Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty
2025-09-07T07:37:16.0850388Z # ignore expansion of "docker ps -q" since it could be empty
2025-09-07T07:37:16.0850666Z # shellcheck disable=SC2046
2025-09-07T07:37:16.0850891Z docker stop $(docker ps -q) || true
2025-09-07T07:37:16.0851124Z # Prune all of the docker images
2025-09-07T07:37:16.0851351Z docker system prune -af
2025-09-07T07:37:16.0858605Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:16.0858853Z env:
2025-09-07T07:37:16.0859010Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:16.0859189Z ##[endgroup]
2025-09-07T07:37:16.1386612Z "docker stop" requires at least 1 argument.
2025-09-07T07:37:16.1386922Z See 'docker stop --help'.
2025-09-07T07:37:16.1387080Z 
2025-09-07T07:37:16.1387270Z Usage:  docker stop [OPTIONS] CONTAINER [CONTAINER...]
2025-09-07T07:37:16.1387444Z 
2025-09-07T07:37:16.1387519Z Stop one or more running containers
2025-09-07T07:37:16.1601769Z Total reclaimed space: 0B
2025-09-07T07:37:16.1634565Z ##[group]Run set +e
2025-09-07T07:37:16.1634774Z set +e
2025-09-07T07:37:16.1634939Z set -x
2025-09-07T07:37:16.1635086Z 
2025-09-07T07:37:16.1635248Z PT_DOMAIN=download.pytorch.org
2025-09-07T07:37:16.1635621Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400,
2025-09-07T07:37:16.1636260Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last
2025-09-07T07:37:16.1636587Z # one is returned at random
2025-09-07T07:37:16.1636839Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1)
2025-09-07T07:37:16.1637078Z 
2025-09-07T07:37:16.1637394Z if [ -z "${RESOLVED_IP}" ]; then
2025-09-07T07:37:16.1637675Z   echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..."
2025-09-07T07:37:16.1637992Z   RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1)
2025-09-07T07:37:16.1638229Z 
2025-09-07T07:37:16.1638384Z   if [ -z "${RESOLVED_IP}" ]; then
2025-09-07T07:37:16.1638625Z     echo "Couldn't resolve ${PT_DOMAIN}, exiting..."
2025-09-07T07:37:16.1638848Z     exit 1
2025-09-07T07:37:16.1638997Z   fi
2025-09-07T07:37:16.1639146Z fi
2025-09-07T07:37:16.1639284Z 
2025-09-07T07:37:16.1639450Z if grep -r "${PT_DOMAIN}" /etc/hosts; then
2025-09-07T07:37:16.1639675Z   # Clean up any old records first
2025-09-07T07:37:16.1639899Z   sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts
2025-09-07T07:37:16.1640100Z fi
2025-09-07T07:37:16.1640239Z 
2025-09-07T07:37:16.1640438Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts
2025-09-07T07:37:16.1640685Z cat /etc/hosts
2025-09-07T07:37:16.1647917Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:16.1648158Z env:
2025-09-07T07:37:16.1648314Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:16.1648503Z ##[endgroup]
2025-09-07T07:37:16.1674508Z + PT_DOMAIN=download.pytorch.org
2025-09-07T07:37:16.1681193Z ++ dig -4 +short download.pytorch.org
2025-09-07T07:37:16.1682297Z ++ tail -n1
2025-09-07T07:37:16.2286953Z + RESOLVED_IP=18.160.10.28
2025-09-07T07:37:16.2287215Z + '[' -z 18.160.10.28 ']'
2025-09-07T07:37:16.2287409Z + grep -r download.pytorch.org /etc/hosts
2025-09-07T07:37:16.2307709Z + echo '18.160.10.28 download.pytorch.org'
2025-09-07T07:37:16.2308916Z + sudo tee -a /etc/hosts
2025-09-07T07:37:16.6387777Z 18.160.10.28 download.pytorch.org
2025-09-07T07:37:16.6406144Z + cat /etc/hosts
2025-09-07T07:37:16.6419818Z 127.0.0.1   localhost localhost.localdomain localhost4 localhost4.localdomain4
2025-09-07T07:37:16.6424605Z ::1         localhost6 localhost6.localdomain6
2025-09-07T07:37:16.6424860Z 18.160.10.28 download.pytorch.org
2025-09-07T07:37:16.6532660Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main
2025-09-07T07:37:16.6532982Z with:
2025-09-07T07:37:16.6533520Z   docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6534093Z   use-custom-docker-registry: true
2025-09-07T07:37:16.6534292Z   docker-build-dir: .ci/docker
2025-09-07T07:37:16.6534505Z   docker-build-script: ./build.sh
2025-09-07T07:37:16.6534695Z   working-directory: .
2025-09-07T07:37:16.6534925Z   docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:16.6535171Z   force-push: false
2025-09-07T07:37:16.6535324Z env:
2025-09-07T07:37:16.6535468Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:16.6535640Z ##[endgroup]
2025-09-07T07:37:16.6549113Z ##[group]Run set -ex
2025-09-07T07:37:16.6549330Z set -ex
2025-09-07T07:37:16.6549484Z 
2025-09-07T07:37:16.6549771Z # If the docker build directory or the build script doesn't exist, the action will
2025-09-07T07:37:16.6550174Z # gracefully return the docker image name as it is.  Pulling docker image in Linux
2025-09-07T07:37:16.6550515Z # job could then download the pre-built image as usual
2025-09-07T07:37:16.6550936Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then
2025-09-07T07:37:16.6551481Z   echo "skip=false" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6551692Z else
2025-09-07T07:37:16.6551865Z   echo "skip=true" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6552139Z   echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6552388Z 
2025-09-07T07:37:16.6552732Z   echo "Not using custom ECR registry.  Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..."
2025-09-07T07:37:16.6553120Z   exit 0
2025-09-07T07:37:16.6553262Z fi
2025-09-07T07:37:16.6553398Z 
2025-09-07T07:37:16.6553616Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then
2025-09-07T07:37:16.6553983Z   # The docker image name already includes the ECR prefix and tag, so we can just
2025-09-07T07:37:16.6554311Z   # use it as it is, but first let's extract the tag
2025-09-07T07:37:16.6554604Z   DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}')
2025-09-07T07:37:16.6554918Z   echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6555214Z   echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6555461Z else
2025-09-07T07:37:16.6555635Z   if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then
2025-09-07T07:37:16.6555865Z     CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:}
2025-09-07T07:37:16.6556110Z     DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*}
2025-09-07T07:37:16.6556317Z   fi
2025-09-07T07:37:16.6556599Z   DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}")
2025-09-07T07:37:16.6556961Z   echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6557340Z   echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6557762Z   echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6558024Z fi
2025-09-07T07:37:16.6568586Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:16.6568824Z env:
2025-09-07T07:37:16.6568977Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:16.6569157Z   REPO_NAME: pytorch
2025-09-07T07:37:16.6569816Z   DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6570397Z   DOCKER_BUILD_DIR: .ci/docker
2025-09-07T07:37:16.6570581Z   DOCKER_BUILD_SCRIPT: ./build.sh
2025-09-07T07:37:16.6570842Z   DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:16.6571109Z   USE_CUSTOM_DOCKER_REGISTRY: true
2025-09-07T07:37:16.6571295Z   CUSTOM_TAG_PREFIX: 
2025-09-07T07:37:16.6571457Z ##[endgroup]
2025-09-07T07:37:16.6596431Z + [[ -d .ci/docker ]]
2025-09-07T07:37:16.6596626Z + [[ -f .ci/docker/./build.sh ]]
2025-09-07T07:37:16.6596818Z + [[ true == \t\r\u\e ]]
2025-09-07T07:37:16.6596975Z + echo skip=false
2025-09-07T07:37:16.6597779Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-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* ]]
2025-09-07T07:37:16.6605512Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6606056Z ++ awk -F '[:,]' '{print $2}'
2025-09-07T07:37:16.6633139Z + DOCKER_TAG=pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6633754Z + echo docker-tag=pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6634713Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6657081Z ##[group]Run set +e
2025-09-07T07:37:16.6657299Z set +e
2025-09-07T07:37:16.6657458Z set -x
2025-09-07T07:37:16.6657604Z 
2025-09-07T07:37:16.6657752Z login() {
2025-09-07T07:37:16.6658059Z   aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1"
2025-09-07T07:37:16.6658392Z }
2025-09-07T07:37:16.6658530Z 
2025-09-07T07:37:16.6658668Z retry () {
2025-09-07T07:37:16.6658848Z   $*  || (sleep 1 && $*) || (sleep 2 && $*)
2025-09-07T07:37:16.6659052Z }
2025-09-07T07:37:16.6659185Z 
2025-09-07T07:37:16.6659344Z retry login "${DOCKER_REGISTRY}"
2025-09-07T07:37:16.6659536Z 
2025-09-07T07:37:16.6659681Z START_TIME=$(date +%s)
2025-09-07T07:37:16.6659885Z # Wait up to 120 minutes
2025-09-07T07:37:16.6660122Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do
2025-09-07T07:37:16.6660424Z   # Check if image already exists, if it does then skip building it
2025-09-07T07:37:16.6660723Z   if docker manifest inspect "${DOCKER_IMAGE}"; then
2025-09-07T07:37:16.6660948Z     exit 0
2025-09-07T07:37:16.6661107Z   fi
2025-09-07T07:37:16.6661256Z 
2025-09-07T07:37:16.6661510Z   # NB: This flag is used by Docker build workflow to push the image to ECR, so we can
2025-09-07T07:37:16.6661913Z   # use this to differentiate between the Docker build and regular build jobs. For the
2025-09-07T07:37:16.6662303Z   # latter, it will wait for the Docker images to become available before continuing
2025-09-07T07:37:16.6662624Z   if [ "${DOCKER_PUSH:-false}" == "true" ]; then
2025-09-07T07:37:16.6662877Z     # It's a Docker build job, let's build the image
2025-09-07T07:37:16.6663110Z     break
2025-09-07T07:37:16.6663260Z   else
2025-09-07T07:37:16.6663479Z     # It's a regular build job, wait for the image to become available
2025-09-07T07:37:16.6663730Z     sleep 300
2025-09-07T07:37:16.6663888Z   fi
2025-09-07T07:37:16.6664025Z done
2025-09-07T07:37:16.6664168Z 
2025-09-07T07:37:16.6664392Z # NB: This part requires a full checkout. Otherwise, the merge base will
2025-09-07T07:37:16.6664894Z # be empty.  The default action would be to continue rebuild the image
2025-09-07T07:37:16.6665215Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then
2025-09-07T07:37:16.6665487Z   # if we're on the base branch then use the parent commit
2025-09-07T07:37:16.6665812Z   MERGE_BASE=$(git rev-parse HEAD~)
2025-09-07T07:37:16.6666007Z else
2025-09-07T07:37:16.6666219Z   # otherwise we're on a PR, so use the most recent base commit
2025-09-07T07:37:16.6666518Z   MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION")
2025-09-07T07:37:16.6666745Z fi
2025-09-07T07:37:16.6666887Z 
2025-09-07T07:37:16.6667044Z if [[ -z "${MERGE_BASE}" ]]; then
2025-09-07T07:37:16.6667282Z   echo "rebuild=true" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6667499Z 
2025-09-07T07:37:16.6667793Z   echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..."
2025-09-07T07:37:16.6668130Z   exit 0
2025-09-07T07:37:16.6668284Z fi
2025-09-07T07:37:16.6668417Z 
2025-09-07T07:37:16.6668622Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then
2025-09-07T07:37:16.6669030Z   echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit"
2025-09-07T07:37:16.6669383Z   exit 1
2025-09-07T07:37:16.6669634Z fi
2025-09-07T07:37:16.6669780Z 
2025-09-07T07:37:16.6670012Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}")
2025-09-07T07:37:16.6670411Z # If no image exists but the hash is the same as the previous hash then we should error out here
2025-09-07T07:37:16.6670774Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then
2025-09-07T07:37:16.6671185Z   echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch"
2025-09-07T07:37:16.6671643Z   echo "         Will re-build docker image to store in local cache, TTS may be longer"
2025-09-07T07:37:16.6671920Z fi
2025-09-07T07:37:16.6672064Z 
2025-09-07T07:37:16.6672240Z echo "rebuild=true" >> "${GITHUB_OUTPUT}"
2025-09-07T07:37:16.6679323Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:16.6679569Z env:
2025-09-07T07:37:16.6679736Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:16.6679922Z   DOCKER_BUILD_DIR: .ci/docker
2025-09-07T07:37:16.6680141Z   BASE_REVISION: 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:37:16.6680734Z   DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6681472Z   DOCKER_TAG: pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:16.6681933Z   DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:16.6682181Z   DOCKER_PUSH: 
2025-09-07T07:37:16.6682334Z ##[endgroup]
2025-09-07T07:37:16.6708152Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:16.6708450Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:16.6711283Z + aws ecr get-login-password --region us-east-1
2025-09-07T07:37:16.6712529Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:17.0832491Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-09-07T07:37:17.0832888Z Configure a credential helper to remove this warning. See
2025-09-07T07:37:17.0833249Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-09-07T07:37:17.0833483Z 
2025-09-07T07:37:17.0834402Z Login Succeeded
2025-09-07T07:37:17.0857831Z ++ date +%s
2025-09-07T07:37:17.0869606Z + START_TIME=1757230637
2025-09-07T07:37:17.0874615Z ++ date +%s
2025-09-07T07:37:17.0887105Z + [[ 1757223437 -lt 1757230637 ]]
2025-09-07T07:37:17.0887719Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:17.3096268Z {
2025-09-07T07:37:17.3096493Z 	"schemaVersion": 2,
2025-09-07T07:37:17.3096810Z 	"mediaType": "application/vnd.docker.distribution.manifest.v2+json",
2025-09-07T07:37:17.3097153Z 	"config": {
2025-09-07T07:37:17.3097376Z 		"mediaType": "application/vnd.docker.container.image.v1+json",
2025-09-07T07:37:17.3097628Z 		"size": 30269,
2025-09-07T07:37:17.3097893Z 		"digest": "sha256:662d8c9dfc7db2f5d004293de4f2b7647941dee4c916479ef082d17fcdfd9c47"
2025-09-07T07:37:17.3098183Z 	},
2025-09-07T07:37:17.3098316Z 	"layers": [
2025-09-07T07:37:17.3098454Z 		{
2025-09-07T07:37:17.3098662Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3099102Z 			"size": 30448359,
2025-09-07T07:37:17.3099394Z 			"digest": "sha256:e6fdc8487bfe6d764301ef3634bc6c043841dc3ab05ca14f81e69c0f92562d46"
2025-09-07T07:37:17.3099698Z 		},
2025-09-07T07:37:17.3099821Z 		{
2025-09-07T07:37:17.3100038Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3100294Z 			"size": 1554,
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2025-09-07T07:37:17.3100839Z 		},
2025-09-07T07:37:17.3101289Z 		{
2025-09-07T07:37:17.3101490Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3101750Z 			"size": 313297813,
2025-09-07T07:37:17.3102008Z 			"digest": "sha256:572424b92528ee46c84fdf3e9e1f5fd75e302621ad75dcf4257ad06778885094"
2025-09-07T07:37:17.3102356Z 		},
2025-09-07T07:37:17.3102482Z 		{
2025-09-07T07:37:17.3102684Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3102925Z 			"size": 793,
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2025-09-07T07:37:17.3103469Z 		},
2025-09-07T07:37:17.3103593Z 		{
2025-09-07T07:37:17.3103788Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3104036Z 			"size": 106,
2025-09-07T07:37:17.3104301Z 			"digest": "sha256:68c20f3c23bb0bddb9b69e6ce2e45bcd5b1fcfd9b37dbe3de26b8a5f0e81ff13"
2025-09-07T07:37:17.3104598Z 		},
2025-09-07T07:37:17.3104716Z 		{
2025-09-07T07:37:17.3104920Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3105169Z 			"size": 704,
2025-09-07T07:37:17.3105423Z 			"digest": "sha256:7efa39950d3273a15b20bc5f6659373b2b4eb62e36328d96b289834c48d2e408"
2025-09-07T07:37:17.3105752Z 		},
2025-09-07T07:37:17.3105883Z 		{
2025-09-07T07:37:17.3106087Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3106337Z 			"size": 1214,
2025-09-07T07:37:17.3106587Z 			"digest": "sha256:a10eb16a7271e996ea9f1d769ba6bd2ec69358f2a79cf26649595a8cea38275f"
2025-09-07T07:37:17.3106872Z 		},
2025-09-07T07:37:17.3106997Z 		{
2025-09-07T07:37:17.3107197Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3107435Z 			"size": 485,
2025-09-07T07:37:17.3107675Z 			"digest": "sha256:7d52cf57965449440c17f257fe4c522f9685019961eaa9853d7c820cfe39f5cc"
2025-09-07T07:37:17.3107953Z 		},
2025-09-07T07:37:17.3108075Z 		{
2025-09-07T07:37:17.3108267Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3108519Z 			"size": 110343705,
2025-09-07T07:37:17.3108785Z 			"digest": "sha256:cb6a20fcf4e24ec2e1f72ecf361b26e058f3e6194947a9b3a25312223d43516e"
2025-09-07T07:37:17.3109071Z 		},
2025-09-07T07:37:17.3109186Z 		{
2025-09-07T07:37:17.3109388Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3109633Z 			"size": 4787,
2025-09-07T07:37:17.3109888Z 			"digest": "sha256:46fb6a8b3e1d4eac9b3a21577824410003ed38f194b4b1486b747e324b32ef6a"
2025-09-07T07:37:17.3110163Z 		},
2025-09-07T07:37:17.3110451Z 		{
2025-09-07T07:37:17.3110656Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3110906Z 			"size": 1709,
2025-09-07T07:37:17.3111155Z 			"digest": "sha256:5ad6977cc38e4ea8a6545d6a4fc0e2fdde705a7af96eb496cfe20f264fbc1e74"
2025-09-07T07:37:17.3111442Z 		},
2025-09-07T07:37:17.3111570Z 		{
2025-09-07T07:37:17.3111767Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3112011Z 			"size": 724,
2025-09-07T07:37:17.3112256Z 			"digest": "sha256:da63046995a2e510b7146776371a14bff4b31002cc3ef0322e45a3932fba2031"
2025-09-07T07:37:17.3112533Z 		},
2025-09-07T07:37:17.3112654Z 		{
2025-09-07T07:37:17.3112845Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3113097Z 			"size": 543,
2025-09-07T07:37:17.3113345Z 			"digest": "sha256:78243fdb9906cb588921ddaa67a3ca915aa9447ca675faac1a9ebc420a561d83"
2025-09-07T07:37:17.3113628Z 		},
2025-09-07T07:37:17.3113752Z 		{
2025-09-07T07:37:17.3113942Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3114192Z 			"size": 3395447162,
2025-09-07T07:37:17.3114454Z 			"digest": "sha256:6f70d5d50abaab8988f460b5590d92b6d1d340575ddee981662c24034d7d20af"
2025-09-07T07:37:17.3114728Z 		},
2025-09-07T07:37:17.3114842Z 		{
2025-09-07T07:37:17.3115042Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3115290Z 			"size": 32,
2025-09-07T07:37:17.3115625Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-09-07T07:37:17.3115907Z 		},
2025-09-07T07:37:17.3116032Z 		{
2025-09-07T07:37:17.3116224Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3116471Z 			"size": 380,
2025-09-07T07:37:17.3116712Z 			"digest": "sha256:69715d3ad3c493436abde51f5a575e79f7d55b46c653f5607f3c7722ad9a05db"
2025-09-07T07:37:17.3116996Z 		},
2025-09-07T07:37:17.3117121Z 		{
2025-09-07T07:37:17.3117322Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3117562Z 			"size": 235844,
2025-09-07T07:37:17.3117815Z 			"digest": "sha256:7ace90c063f3f3ce8f04b541afe935088868930e5c074824af2b2c327779a3b5"
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2025-09-07T07:37:17.3180649Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3180895Z 			"size": 104,
2025-09-07T07:37:17.3181137Z 			"digest": "sha256:41619248f604c60e038a02bfd462af96ee2996b77be5f59f05e9ac5fe4790e5a"
2025-09-07T07:37:17.3181414Z 		},
2025-09-07T07:37:17.3181537Z 		{
2025-09-07T07:37:17.3181734Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3181972Z 			"size": 407,
2025-09-07T07:37:17.3182224Z 			"digest": "sha256:be86f8c4f654b9ae64a20eb7f960e6ce4baa5b46e0a1f5e1312b11492a40bcd4"
2025-09-07T07:37:17.3182506Z 		},
2025-09-07T07:37:17.3182630Z 		{
2025-09-07T07:37:17.3182822Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3183071Z 			"size": 32,
2025-09-07T07:37:17.3183318Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-09-07T07:37:17.3183598Z 		},
2025-09-07T07:37:17.3183721Z 		{
2025-09-07T07:37:17.3183912Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3184153Z 			"size": 109,
2025-09-07T07:37:17.3184403Z 			"digest": "sha256:ef1340e22a4bc8cf42e1d40961cb32d183cd3da8f0b785b5425c32ee067690c1"
2025-09-07T07:37:17.3184770Z 		},
2025-09-07T07:37:17.3184884Z 		{
2025-09-07T07:37:17.3185084Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3185328Z 			"size": 1897,
2025-09-07T07:37:17.3185626Z 			"digest": "sha256:da8d8b696333cbf6b9f339ab859639c905d6752d7e65fea14c23c3c2dcba553e"
2025-09-07T07:37:17.3185928Z + exit 0
2025-09-07T07:37:17.3186055Z 		},
2025-09-07T07:37:17.3186174Z 		{
2025-09-07T07:37:17.3186374Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3186617Z 			"size": 243443118,
2025-09-07T07:37:17.3186881Z 			"digest": "sha256:386b0c49c4982a821fb6f427fbc7d9c7d2012e97c96a514a9c7a09304e76b935"
2025-09-07T07:37:17.3187159Z 		},
2025-09-07T07:37:17.3187280Z 		{
2025-09-07T07:37:17.3187471Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3187714Z 			"size": 106,
2025-09-07T07:37:17.3187966Z 			"digest": "sha256:2b1d0ea7efe0bf86e86df804d2cddbf83b113fdecd03f3ddfca728da30546f34"
2025-09-07T07:37:17.3188257Z 		},
2025-09-07T07:37:17.3188371Z 		{
2025-09-07T07:37:17.3188570Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3188848Z 			"size": 163,
2025-09-07T07:37:17.3189091Z 			"digest": "sha256:04c04be7408f20625b1bd8454e5a08c91fcf04d4f79ab3ec1b75ae6b1824174d"
2025-09-07T07:37:17.3189353Z 		},
2025-09-07T07:37:17.3189464Z 		{
2025-09-07T07:37:17.3189646Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3189882Z 			"size": 7943,
2025-09-07T07:37:17.3190169Z 			"digest": "sha256:f8690caa3ac5e845f2dcc25ad12815b5c7452285c3838a87c780bd03ecf072a3"
2025-09-07T07:37:17.3190443Z 		},
2025-09-07T07:37:17.3190554Z 		{
2025-09-07T07:37:17.3190736Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3190963Z 			"size": 8074,
2025-09-07T07:37:17.3191200Z 			"digest": "sha256:2908d6baaa6b21331dee5f210472cae0874d22b98b0a35420cad4fd753ed215f"
2025-09-07T07:37:17.3191475Z 		},
2025-09-07T07:37:17.3191583Z 		{
2025-09-07T07:37:17.3191767Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3191996Z 			"size": 303,
2025-09-07T07:37:17.3192223Z 			"digest": "sha256:37e2336101eba2c73995d34431e4fae8782d9e9700c42621777922490b2158ed"
2025-09-07T07:37:17.3192496Z 		},
2025-09-07T07:37:17.3192608Z 		{
2025-09-07T07:37:17.3192811Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3193051Z 			"size": 32,
2025-09-07T07:37:17.3193383Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-09-07T07:37:17.3193666Z 		},
2025-09-07T07:37:17.3193781Z 		{
2025-09-07T07:37:17.3193972Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3194210Z 			"size": 108,
2025-09-07T07:37:17.3194444Z 			"digest": "sha256:f1ac881fde33994861be4324231269058643168b9aee60c699552d0d92d965da"
2025-09-07T07:37:17.3194722Z 		},
2025-09-07T07:37:17.3194832Z 		{
2025-09-07T07:37:17.3195019Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3195254Z 			"size": 54145699,
2025-09-07T07:37:17.3195504Z 			"digest": "sha256:43b14c67347e2813c5f63e928c14db60dbb35c330ccc865510cf79739d8b78a1"
2025-09-07T07:37:17.3195769Z 		},
2025-09-07T07:37:17.3195881Z 		{
2025-09-07T07:37:17.3196062Z 			"mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip",
2025-09-07T07:37:17.3196302Z 			"size": 32,
2025-09-07T07:37:17.3196550Z 			"digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1"
2025-09-07T07:37:17.3196832Z 		}
2025-09-07T07:37:17.3196940Z 	]
2025-09-07T07:37:17.3197068Z }
2025-09-07T07:37:17.3219290Z ##[group]Run set -eux
2025-09-07T07:37:17.3219479Z set -eux
2025-09-07T07:37:17.3219736Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have
2025-09-07T07:37:17.3220423Z 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
2025-09-07T07:37:17.3229116Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:17.3229345Z env:
2025-09-07T07:37:17.3229488Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:17.3229663Z ##[endgroup]
2025-09-07T07:37:17.3260807Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token
2025-09-07T07:37:17.3261967Z + jq --raw-output .SecretString
2025-09-07T07:37:17.3262811Z + jq -r .docker_hub_readonly_token
2025-09-07T07:37:17.3264393Z + docker login --username pytorchbot --password-stdin
2025-09-07T07:37:17.7822298Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-09-07T07:37:17.7822711Z Configure a credential helper to remove this warning. See
2025-09-07T07:37:17.7823090Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-09-07T07:37:17.7823366Z 
2025-09-07T07:37:17.7823540Z Login Succeeded
2025-09-07T07:37:17.7907696Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:}
2025-09-07T07:37:17.7907970Z tag=${ECR_DOCKER_IMAGE##*:}
2025-09-07T07:37:17.7908231Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
2025-09-07T07:37:17.7915251Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:17.7915499Z env:
2025-09-07T07:37:17.7915659Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:17.7916214Z   ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:17.7916769Z ##[endgroup]
2025-09-07T07:37:17.7944401Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:17.7980235Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main
2025-09-07T07:37:17.7980536Z with:
2025-09-07T07:37:17.7981080Z   docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:17.7981690Z   docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:17.7981940Z env:
2025-09-07T07:37:17.7982089Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:17.7982266Z ##[endgroup]
2025-09-07T07:37:17.7993492Z ##[group]Run set -x
2025-09-07T07:37:17.7993688Z set -x
2025-09-07T07:37:17.7993839Z set +e
2025-09-07T07:37:17.7993983Z 
2025-09-07T07:37:17.7994115Z login() {
2025-09-07T07:37:17.7994420Z   aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1"
2025-09-07T07:37:17.7994736Z }
2025-09-07T07:37:17.7994876Z 
2025-09-07T07:37:17.7995043Z retry () {
2025-09-07T07:37:17.7995222Z   $*  || (sleep 1 && $*) || (sleep 2 && $*)
2025-09-07T07:37:17.7995423Z }
2025-09-07T07:37:17.7995562Z 
2025-09-07T07:37:17.7995715Z retry login "${DOCKER_REGISTRY}"
2025-09-07T07:37:17.7995910Z 
2025-09-07T07:37:17.7996200Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024')
2025-09-07T07:37:17.7996601Z echo "Compressed size of image in MB: ${IMAGE_SIZE}"
2025-09-07T07:37:17.7996828Z 
2025-09-07T07:37:17.7996964Z set -e
2025-09-07T07:37:17.7997175Z # ignore output since only exit code is used for conditional
2025-09-07T07:37:17.7997479Z # only pull docker image if it's not available locally
2025-09-07T07:37:17.7997804Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then
2025-09-07T07:37:17.7998121Z   retry docker pull "${DOCKER_IMAGE}"
2025-09-07T07:37:17.7998323Z fi
2025-09-07T07:37:17.8005527Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:37:17.8005915Z env:
2025-09-07T07:37:17.8006065Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:37:17.8006604Z   DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:17.8007204Z   DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:17.8007452Z ##[endgroup]
2025-09-07T07:37:17.8034034Z + set +e
2025-09-07T07:37:17.8034256Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:17.8034532Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:17.8038267Z + aws ecr get-login-password --region us-east-1
2025-09-07T07:37:17.8039607Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com
2025-09-07T07:37:18.2219988Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json.
2025-09-07T07:37:18.2220395Z Configure a credential helper to remove this warning. See
2025-09-07T07:37:18.2220779Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store
2025-09-07T07:37:18.2221035Z 
2025-09-07T07:37:18.2221439Z Login Succeeded
2025-09-07T07:37:18.2247718Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:18.2248374Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024'
2025-09-07T07:37:18.4451432Z + IMAGE_SIZE=28579.020259857178
2025-09-07T07:37:18.4451693Z + echo 'Compressed size of image in MB: 28579.020259857178'
2025-09-07T07:37:18.4451933Z + set -e
2025-09-07T07:37:18.4452110Z Compressed size of image in MB: 28579.020259857178
2025-09-07T07:37:18.4452995Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:18.4596481Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:18.4597451Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:37:18.7126913Z pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77: Pulling from pytorch/ci-image
2025-09-07T07:37:18.7129658Z e6fdc8487bfe: Pulling fs layer
2025-09-07T07:37:18.7129895Z 18a5ee5b0e2e: Pulling fs layer
2025-09-07T07:37:18.7130081Z 572424b92528: Pulling fs layer
2025-09-07T07:37:18.7130249Z 1c35b7d4b67c: Pulling fs layer
2025-09-07T07:37:18.7130422Z 68c20f3c23bb: Pulling fs layer
2025-09-07T07:37:18.7130602Z 7efa39950d32: Pulling fs layer
2025-09-07T07:37:18.7130816Z a10eb16a7271: Pulling fs layer
2025-09-07T07:37:18.7130992Z 7d52cf579654: Pulling fs layer
2025-09-07T07:37:18.7131203Z cb6a20fcf4e2: Pulling fs layer
2025-09-07T07:37:18.7131400Z 46fb6a8b3e1d: Pulling fs layer
2025-09-07T07:37:18.7131576Z 5ad6977cc38e: Pulling fs layer
2025-09-07T07:37:18.7131795Z da63046995a2: Pulling fs layer
2025-09-07T07:37:18.7131964Z 78243fdb9906: Pulling fs layer
2025-09-07T07:37:18.7132141Z 6f70d5d50aba: Pulling fs layer
2025-09-07T07:37:18.7132312Z 4f4fb700ef54: Pulling fs layer
2025-09-07T07:37:18.7132484Z 69715d3ad3c4: Pulling fs layer
2025-09-07T07:37:18.7132643Z 7ace90c063f3: Pulling fs layer
2025-09-07T07:37:18.7132813Z acbd5447dd14: Pulling fs layer
2025-09-07T07:37:18.7132984Z 744523d9b7f5: Pulling fs layer
2025-09-07T07:37:18.7133155Z 5bd615a7b945: Pulling fs layer
2025-09-07T07:37:18.7133332Z f4986a00e3ae: Pulling fs layer
2025-09-07T07:37:18.7133511Z 21902f6e4f8c: Pulling fs layer
2025-09-07T07:37:18.7133687Z d80602abf3cc: Pulling fs layer
2025-09-07T07:37:18.7133858Z 3c51bf0bc362: Pulling fs layer
2025-09-07T07:37:18.7134035Z 119ab3bceafa: Pulling fs layer
2025-09-07T07:37:18.7134208Z af8eadc9eaab: Pulling fs layer
2025-09-07T07:37:18.7134614Z e7769b0d7a82: Pulling fs layer
2025-09-07T07:37:18.7134774Z ba263639b0f4: Pulling fs layer
2025-09-07T07:37:18.7134947Z a5ab7a280382: Pulling fs layer
2025-09-07T07:37:18.7135114Z 80b2232d952f: Pulling fs layer
2025-09-07T07:37:18.7135297Z cc93cd65e90f: Pulling fs layer
2025-09-07T07:37:18.7135470Z 0eed4c15712b: Pulling fs layer
2025-09-07T07:37:18.7135642Z 092516f71fe3: Pulling fs layer
2025-09-07T07:37:18.7135816Z 8c0825014a62: Pulling fs layer
2025-09-07T07:37:18.7135984Z 8e0d2f63da0a: Pulling fs layer
2025-09-07T07:37:18.7136146Z 73aae7958ba1: Pulling fs layer
2025-09-07T07:37:18.7136323Z ac6077ec9fa5: Pulling fs layer
2025-09-07T07:37:18.7136489Z bf4ee4e45e92: Pulling fs layer
2025-09-07T07:37:18.7136657Z c1b766f9b961: Pulling fs layer
2025-09-07T07:37:18.7136824Z 6e726ef07b5d: Pulling fs layer
2025-09-07T07:37:18.7137000Z 364070434a64: Pulling fs layer
2025-09-07T07:37:18.7137167Z 71f708151a84: Pulling fs layer
2025-09-07T07:37:18.7137338Z 622d8cfb39ea: Pulling fs layer
2025-09-07T07:37:18.7137502Z 284119a92cb1: Pulling fs layer
2025-09-07T07:37:18.7137667Z 96695940d842: Pulling fs layer
2025-09-07T07:37:18.7137837Z 7ddca6c4c050: Pulling fs layer
2025-09-07T07:37:18.7138009Z a95e1f2f1aad: Pulling fs layer
2025-09-07T07:37:18.7138170Z 8085756b0cc0: Pulling fs layer
2025-09-07T07:37:18.7138342Z 7e9ff0c6f103: Pulling fs layer
2025-09-07T07:37:18.7138511Z a625cbbc05b9: Pulling fs layer
2025-09-07T07:37:18.7138680Z 4e2848642431: Pulling fs layer
2025-09-07T07:37:18.7138841Z 5e944f1ed1be: Pulling fs layer
2025-09-07T07:37:18.7139025Z 41619248f604: Pulling fs layer
2025-09-07T07:37:18.7139229Z be86f8c4f654: Pulling fs layer
2025-09-07T07:37:18.7139400Z ef1340e22a4b: Pulling fs layer
2025-09-07T07:37:18.7139570Z da8d8b696333: Pulling fs layer
2025-09-07T07:37:18.7139732Z 386b0c49c498: Pulling fs layer
2025-09-07T07:37:18.7140075Z 2b1d0ea7efe0: Pulling fs layer
2025-09-07T07:37:18.7140250Z 04c04be7408f: Pulling fs layer
2025-09-07T07:37:18.7140427Z f8690caa3ac5: Pulling fs layer
2025-09-07T07:37:18.7140598Z 2908d6baaa6b: Pulling fs layer
2025-09-07T07:37:18.7140767Z 37e2336101eb: Pulling fs layer
2025-09-07T07:37:18.7140935Z f1ac881fde33: Pulling fs layer
2025-09-07T07:37:18.7141101Z 43b14c67347e: Pulling fs layer
2025-09-07T07:37:18.7141258Z 7d52cf579654: Waiting
2025-09-07T07:37:18.7141445Z 46fb6a8b3e1d: Waiting
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2025-09-07T07:43:47.2667930Z Digest: sha256:383efb45082f20b8c808cb0ba4df693a01359592233f641f1f486911ac320a9a
2025-09-07T07:43:47.3568669Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:43:47.4134811Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:43:47.4195675Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-09-07T07:43:47.4196307Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-09-07T07:43:47.4207609Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:43:47.4207871Z env:
2025-09-07T07:43:47.4208036Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:47.4208213Z ##[endgroup]
2025-09-07T07:43:47.4292633Z Prepare all required actions
2025-09-07T07:43:47.4319124Z ##[group]Run ./.github/actions/get-workflow-job-id
2025-09-07T07:43:47.4319362Z with:
2025-09-07T07:43:47.4319940Z   github-token: ***
2025-09-07T07:43:47.4320100Z env:
2025-09-07T07:43:47.4320251Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:47.4320434Z ##[endgroup]
2025-09-07T07:43:47.4452559Z ##[group]Run set -eux
2025-09-07T07:43:47.4452749Z set -eux
2025-09-07T07:43:47.4453038Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}"
2025-09-07T07:43:47.4460271Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:43:47.4460519Z env:
2025-09-07T07:43:47.4460673Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:47.4461035Z   GITHUB_TOKEN: ***
2025-09-07T07:43:47.4461207Z ##[endgroup]
2025-09-07T07:43:47.4488909Z + python3 .github/scripts/get_workflow_job_id.py 17525294857 i-04e43c8796a0bfd2e
2025-09-07T07:43:47.9359758Z Setting output job-id=49775530523
2025-09-07T07:43:47.9360293Z Setting output job-name=inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:43:47.9495162Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
2025-09-07T07:43:47.9495665Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84
2025-09-07T07:43:47.9496259Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
2025-09-07T07:43:47.9496796Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
2025-09-07T07:43:47.9504751Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:43:47.9505003Z env:
2025-09-07T07:43:47.9505153Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:47.9505356Z   JOB_ID: 49775530523
2025-09-07T07:43:47.9505725Z   JOB_NAME: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:43:47.9506113Z   WORKFLOW_NAME: inductor-perf-nightly-x86-zen
2025-09-07T07:43:47.9506385Z   WORKFLOW_RUN_ID: 17525294857
2025-09-07T07:43:47.9506576Z   MONITOR_LOG_INTERVAL: 15
2025-09-07T07:43:47.9506751Z   MONITOR_DATA_COLLECT_INTERVAL: 4
2025-09-07T07:43:47.9506941Z ##[endgroup]
2025-09-07T07:43:48.6151170Z Defaulting to user installation because normal site-packages is not writeable
2025-09-07T07:43:48.8752180Z Collecting psutil==5.9.8
2025-09-07T07:43:48.8910496Z   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)
2025-09-07T07:43:49.0924141Z Collecting dataclasses_json==0.6.7
2025-09-07T07:43:49.0955163Z   Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB)
2025-09-07T07:43:49.1429586Z Collecting nvidia-ml-py==11.525.84
2025-09-07T07:43:49.1466954Z   Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB)
2025-09-07T07:43:49.2159711Z Collecting typing-inspect<1,>=0.4.0
2025-09-07T07:43:49.2188778Z   Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)
2025-09-07T07:43:49.3802169Z Collecting marshmallow<4.0.0,>=3.18.0
2025-09-07T07:43:49.3832469Z   Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB)
2025-09-07T07:43:49.4965877Z Collecting packaging>=17.0
2025-09-07T07:43:49.4995152Z   Downloading packaging-25.0-py3-none-any.whl (66 kB)
2025-09-07T07:43:49.6576988Z Collecting typing-extensions>=3.7.4
2025-09-07T07:43:49.6607211Z   Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB)
2025-09-07T07:43:49.7697500Z Collecting mypy-extensions>=0.3.0
2025-09-07T07:43:49.7728229Z   Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB)
2025-09-07T07:43:49.9866892Z Installing collected packages: typing-extensions, packaging, mypy-extensions, typing-inspect, marshmallow, psutil, nvidia-ml-py, dataclasses-json
2025-09-07T07:43:50.5608568Z 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
2025-09-07T07:43:50.7686967Z Prepare all required actions
2025-09-07T07:43:50.7687260Z Getting action download info
2025-09-07T07:43:50.9232281Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6)
2025-09-07T07:43:51.5682838Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093)
2025-09-07T07:43:53.2541199Z ##[group]Run ./.github/actions/download-build-artifacts
2025-09-07T07:43:53.2541462Z with:
2025-09-07T07:43:53.2541638Z   name: linux-jammy-py3.9-gcc11-build
2025-09-07T07:43:53.2541850Z   s3-bucket: gha-artifacts
2025-09-07T07:43:53.2542036Z env:
2025-09-07T07:43:53.2542182Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:53.2542361Z ##[endgroup]
2025-09-07T07:43:53.2640447Z ##[group]Run seemethere/download-artifact-s3@v4
2025-09-07T07:43:53.2640692Z with:
2025-09-07T07:43:53.2640858Z   name: linux-jammy-py3.9-gcc11-build
2025-09-07T07:43:53.2641069Z   s3-bucket: gha-artifacts
2025-09-07T07:43:53.2641291Z   region: us-east-1
2025-09-07T07:43:53.2641443Z env:
2025-09-07T07:43:53.2641588Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:53.2641761Z ##[endgroup]
2025-09-07T07:43:53.8707512Z (node:57309) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023.
2025-09-07T07:43:53.8707851Z 
2025-09-07T07:43:53.8707983Z Please migrate your code to use AWS SDK for JavaScript (v3).
2025-09-07T07:43:53.8708342Z For more information, check the migration guide at https://a.co/7PzMCcy
2025-09-07T07:43:53.8708712Z (Use `node --trace-warnings ...` to show where the warning was created)
2025-09-07T07:43:55.2328919Z Found 1 objects with prefix pytorch/pytorch/17525294857/linux-jammy-py3.9-gcc11-build/
2025-09-07T07:43:55.2329423Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip
2025-09-07T07:43:59.8206827Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip
2025-09-07T07:43:59.8211565Z Artifact download has finished successfully
2025-09-07T07:43:59.8495089Z ##[group]Run unzip -o artifacts.zip
2025-09-07T07:43:59.8495338Z unzip -o artifacts.zip
2025-09-07T07:43:59.8502915Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:43:59.8503165Z env:
2025-09-07T07:43:59.8503319Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:43:59.8503497Z ##[endgroup]
2025-09-07T07:43:59.8835535Z Archive:  artifacts.zip
2025-09-07T07:43:59.8836120Z    creating: dist/
2025-09-07T07:44:00.8679356Z   inflating: dist/torch-2.9.0a0+git93fb23d-cp39-cp39-linux_x86_64.whl  
2025-09-07T07:44:00.8786689Z   inflating: dist/.ninja_log         
2025-09-07T07:44:00.8787653Z    creating: build/custom_test_artifacts/
2025-09-07T07:44:00.8788020Z    creating: build/custom_test_artifacts/custom-op-build/
2025-09-07T07:44:00.8788784Z    creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/
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2025-09-07T07:44:00.8792086Z   inflating: build/custom_test_artifacts/custom-op-build/CMakeFiles/CMakeConfigureLog.yaml  
2025-09-07T07:44:00.8792515Z    creating: build/custom_test_artifacts/custom-op-build/CMakeFiles/4.0.0/
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2025-09-07T07:44:05.7143809Z   inflating: build/bin/xla_tensor_test  
2025-09-07T07:44:05.7198358Z   inflating: build/bin/IListRef_test  
2025-09-07T07:44:05.7292708Z   inflating: build/bin/List_test     
2025-09-07T07:44:05.7352881Z   inflating: build/bin/KernelFunction_test  
2025-09-07T07:44:05.7459296Z   inflating: build/bin/kernel_function_legacy_test  
2025-09-07T07:44:05.7543578Z   inflating: build/bin/kernel_function_test  
2025-09-07T07:44:05.7653987Z   inflating: build/bin/kernel_lambda_legacy_test  
2025-09-07T07:44:05.7744481Z   inflating: build/bin/kernel_lambda_test  
2025-09-07T07:44:05.7799675Z   inflating: build/bin/kernel_stackbased_test  
2025-09-07T07:44:05.7883505Z   inflating: build/bin/make_boxed_from_unboxed_functor_test  
2025-09-07T07:44:05.7931055Z   inflating: build/bin/CppSignature_test  
2025-09-07T07:44:05.7981810Z   inflating: build/bin/backend_fallback_test  
2025-09-07T07:44:05.8027363Z   inflating: build/bin/op_allowlist_test  
2025-09-07T07:44:05.8295004Z   inflating: build/bin/op_registration_test  
2025-09-07T07:44:05.8355928Z   inflating: build/bin/inline_container_test  
2025-09-07T07:44:05.9288427Z   inflating: build/bin/test_jit      
2025-09-07T07:44:05.9337948Z   inflating: build/bin/FileStoreTest  
2025-09-07T07:44:05.9386349Z   inflating: build/bin/BackoffTest   
2025-09-07T07:44:05.9438954Z   inflating: build/bin/TCPStoreTest  
2025-09-07T07:44:05.9759794Z   inflating: build/bin/test_nativert  
2025-09-07T07:44:05.9809658Z   inflating: build/bin/HashStoreTest  
2025-09-07T07:44:05.9869545Z   inflating: build/bin/ProcessGroupGlooTest  
2025-09-07T07:44:05.9872194Z   inflating: build/bin/example_allreduce  
2025-09-07T07:44:05.9923037Z   inflating: build/bin/test_dist_autograd  
2025-09-07T07:44:05.9984358Z   inflating: build/bin/test_cpp_rpc  
2025-09-07T07:44:06.0947705Z   inflating: build/bin/test_api      
2025-09-07T07:44:06.0949910Z   inflating: build/bin/parallel_benchmark  
2025-09-07T07:44:06.1244999Z   inflating: build/bin/test_lazy     
2025-09-07T07:44:06.1248762Z   inflating: build/bin/torch_shm_manager  
2025-09-07T07:44:06.1249048Z    creating: .additional_ci_files/
2025-09-07T07:44:06.1324196Z   inflating: .additional_ci_files/test-times.json  
2025-09-07T07:44:06.1607919Z   inflating: .additional_ci_files/test-class-times.json  
2025-09-07T07:44:06.1664317Z ##[group]Run rm artifacts.zip
2025-09-07T07:44:06.1664561Z rm artifacts.zip
2025-09-07T07:44:06.1671720Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:06.1671969Z env:
2025-09-07T07:44:06.1672120Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:06.1672299Z ##[endgroup]
2025-09-07T07:44:06.3917627Z ##[group]Run df -H
2025-09-07T07:44:06.3917824Z df -H
2025-09-07T07:44:06.3924932Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:06.3925165Z env:
2025-09-07T07:44:06.3925311Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:06.3925483Z ##[endgroup]
2025-09-07T07:44:06.3975114Z Filesystem        Size  Used Avail Use% Mounted on
2025-09-07T07:44:06.3975405Z devtmpfs          4.2M     0  4.2M   0% /dev
2025-09-07T07:44:06.3975622Z tmpfs             199G     0  199G   0% /dev/shm
2025-09-07T07:44:06.3976155Z tmpfs              80G  1.3M   80G   1% /run
2025-09-07T07:44:06.3976364Z /dev/nvme0n1p1    215G   72G  144G  34% /
2025-09-07T07:44:06.3976587Z tmpfs             199G   13k  199G   1% /tmp
2025-09-07T07:44:06.3976806Z /dev/nvme0n1p128   11M  1.4M  9.2M  13% /boot/efi
2025-09-07T07:44:06.4004581Z Prepare all required actions
2025-09-07T07:44:06.4005388Z Getting action download info
2025-09-07T07:44:06.5468380Z ##[group]Run ./.github/actions/download-td-artifacts
2025-09-07T07:44:06.5468615Z with:
2025-09-07T07:44:06.5468753Z env:
2025-09-07T07:44:06.5468902Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:06.5469069Z ##[endgroup]
2025-09-07T07:44:07.9840544Z ##[group]Run seemethere/download-artifact-s3@v4
2025-09-07T07:44:07.9840781Z with:
2025-09-07T07:44:07.9840921Z   name: td_results
2025-09-07T07:44:07.9841088Z   s3-bucket: gha-artifacts
2025-09-07T07:44:07.9841265Z   region: us-east-1
2025-09-07T07:44:07.9841409Z env:
2025-09-07T07:44:07.9841550Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:07.9841743Z ##[endgroup]
2025-09-07T07:44:08.3446589Z (node:57335) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023.
2025-09-07T07:44:08.3446917Z 
2025-09-07T07:44:08.3447131Z Please migrate your code to use AWS SDK for JavaScript (v3).
2025-09-07T07:44:08.3447488Z For more information, check the migration guide at https://a.co/7PzMCcy
2025-09-07T07:44:08.3447839Z (Use `node --trace-warnings ...` to show where the warning was created)
2025-09-07T07:44:08.4272727Z Found 0 objects with prefix pytorch/pytorch/17525294857/td_results/
2025-09-07T07:44:08.4277765Z Artifact download has finished successfully
2025-09-07T07:44:08.4546906Z ##[group]Run mkdir -p .additional_ci_files
2025-09-07T07:44:08.4547165Z mkdir -p .additional_ci_files
2025-09-07T07:44:08.4547434Z mv td_results.json .additional_ci_files/td_results.json || true
2025-09-07T07:44:08.4554823Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:08.4555080Z env:
2025-09-07T07:44:08.4555232Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:08.4555403Z ##[endgroup]
2025-09-07T07:44:08.4616569Z mv: cannot stat 'td_results.json': No such file or directory
2025-09-07T07:44:08.4759949Z ##[group]Run .github/scripts/parse_ref.py
2025-09-07T07:44:08.4760218Z .github/scripts/parse_ref.py
2025-09-07T07:44:08.4767493Z shell: /usr/bin/bash -e {0}
2025-09-07T07:44:08.4767680Z env:
2025-09-07T07:44:08.4767826Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:08.4767996Z ##[endgroup]
2025-09-07T07:44:08.5371429Z Setting output branch=main
2025-09-07T07:44:08.5458782Z Prepare all required actions
2025-09-07T07:44:08.5459084Z Getting action download info
2025-09-07T07:44:08.6729103Z ##[group]Run ./.github/actions/filter-test-configs
2025-09-07T07:44:08.6729343Z with:
2025-09-07T07:44:08.6729751Z   github-token: ***
2025-09-07T07:44:08.6732264Z   test-matrix: {"include": [{"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 1, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 2, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 3, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 1, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 2, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 3, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 4, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 5, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 1, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 2, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 3, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 4, "num_shards": 4, "runner": "linux.24xlarge.amd"}]}
2025-09-07T07:44:08.6735210Z   job-name: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:44:08.6735553Z env:
2025-09-07T07:44:08.6735701Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:08.6735878Z ##[endgroup]
2025-09-07T07:44:08.6785601Z ##[group]Run nick-fields/retry@v3.0.0
2025-09-07T07:44:08.6785809Z with:
2025-09-07T07:44:08.6785955Z   shell: bash
2025-09-07T07:44:08.6786110Z   timeout_minutes: 10
2025-09-07T07:44:08.6786271Z   max_attempts: 5
2025-09-07T07:44:08.6786430Z   retry_wait_seconds: 30
2025-09-07T07:44:08.6786914Z   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

2025-09-07T07:44:08.6787428Z   polling_interval_seconds: 1
2025-09-07T07:44:08.6787616Z   warning_on_retry: true
2025-09-07T07:44:08.6787790Z   continue_on_error: false
2025-09-07T07:44:08.6787956Z env:
2025-09-07T07:44:08.6788095Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:08.6788377Z   GITHUB_TOKEN: ***
2025-09-07T07:44:08.6788545Z ##[endgroup]
2025-09-07T07:44:08.8444871Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2
2025-09-07T07:44:09.0173181Z Defaulting to user installation because normal site-packages is not writeable
2025-09-07T07:44:09.1468312Z Collecting requests==2.27.1
2025-09-07T07:44:09.1589043Z   Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)
2025-09-07T07:44:09.3567721Z Collecting pyyaml==6.0.2
2025-09-07T07:44:09.3597338Z   Downloading PyYAML-6.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (737 kB)
2025-09-07T07:44:09.4364530Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (1.25.10)
2025-09-07T07:44:09.5310338Z Collecting certifi>=2017.4.17
2025-09-07T07:44:09.5340157Z   Downloading certifi-2025.8.3-py3-none-any.whl (161 kB)
2025-09-07T07:44:09.6031341Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (2.10)
2025-09-07T07:44:09.8987014Z Collecting charset-normalizer~=2.0.0
2025-09-07T07:44:09.9017094Z   Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB)
2025-09-07T07:44:10.0254411Z Installing collected packages: charset-normalizer, certifi, requests, pyyaml
2025-09-07T07:44:10.5482325Z Successfully installed certifi-2025.8.3 charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1
2025-09-07T07:44:10.7379781Z Command completed after 1 attempt(s).
2025-09-07T07:44:10.7455660Z ##[group]Run set -x
2025-09-07T07:44:10.7455858Z set -x
2025-09-07T07:44:10.7456008Z 
2025-09-07T07:44:10.7456254Z # Use relative path here as this could be checked out anywhere, not necessarily
2025-09-07T07:44:10.7456562Z # in runner workspace
2025-09-07T07:44:10.7456845Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py"
2025-09-07T07:44:10.7464122Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:10.7464361Z env:
2025-09-07T07:44:10.7464504Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:10.7464679Z ##[endgroup]
2025-09-07T07:44:10.7493352Z + python3 /home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py
2025-09-07T07:44:10.7641767Z Setting output branch=main
2025-09-07T07:44:10.7698106Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}"
2025-09-07T07:44:10.7698398Z echo "Workflow: ${GITHUB_WORKFLOW}"
2025-09-07T07:44:10.7698627Z echo "Job name: ${JOB_NAME}"
2025-09-07T07:44:10.7699003Z 
2025-09-07T07:44:10.7699245Z # Use relative path here as this could be checked out anywhere, not necessarily
2025-09-07T07:44:10.7699544Z # in runner workspace
2025-09-07T07:44:10.7700003Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \
2025-09-07T07:44:10.7700310Z   --workflow "${GITHUB_WORKFLOW}" \
2025-09-07T07:44:10.7700518Z   --job-name "${JOB_NAME}" \
2025-09-07T07:44:10.7703032Z   --test-matrix "{"include": [{"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 1, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 2, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 3, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 1, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 2, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 3, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 4, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 5, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 1, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 2, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 3, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 4, "num_shards": 4, "runner": "linux.24xlarge.amd"}]}" \
2025-09-07T07:44:10.7705675Z   --selected-test-configs "" \
2025-09-07T07:44:10.7705897Z   --pr-number "${PR_NUMBER}" \
2025-09-07T07:44:10.7706101Z   --tag "${TAG}" \
2025-09-07T07:44:10.7706288Z   --event-name "${EVENT_NAME}" \
2025-09-07T07:44:10.7706494Z   --schedule "${SCHEDULE}" \
2025-09-07T07:44:10.7706694Z   --branch "${HEAD_BRANCH}"
2025-09-07T07:44:10.7713811Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:10.7714049Z env:
2025-09-07T07:44:10.7714202Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:10.7714666Z   GITHUB_TOKEN: ***
2025-09-07T07:44:10.7714998Z   JOB_NAME: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:44:10.7715341Z   PR_NUMBER: 
2025-09-07T07:44:10.7715485Z   TAG: 
2025-09-07T07:44:10.7715632Z   EVENT_NAME: schedule
2025-09-07T07:44:10.7715810Z   SCHEDULE: 0 7 * * *
2025-09-07T07:44:10.7715978Z   HEAD_BRANCH: main
2025-09-07T07:44:10.7716331Z ##[endgroup]
2025-09-07T07:44:10.7743127Z Workflow: inductor-perf-nightly-x86-zen
2025-09-07T07:44:10.7743566Z Job name: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:44:10.9364436Z Setting output keep-going=True
2025-09-07T07:44:10.9364706Z Setting output ci-verbose-test-logs=False
2025-09-07T07:44:10.9364935Z Setting output ci-test-showlocals=False
2025-09-07T07:44:10.9365206Z Setting output ci-no-test-timeout=False
2025-09-07T07:44:10.9365415Z Setting output ci-no-td=False
2025-09-07T07:44:10.9365614Z Setting output ci-td-distributed=False
2025-09-07T07:44:10.9365820Z Setting output is-unstable=False
2025-09-07T07:44:10.9366018Z Setting output reenabled-issues=
2025-09-07T07:44:10.9368578Z Setting output test-matrix={"include": [{"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 1, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 2, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 3, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 1, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 2, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 3, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 4, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 5, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 1, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 2, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 3, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 4, "num_shards": 4, "runner": "linux.24xlarge.amd"}]}
2025-09-07T07:44:10.9371560Z Setting output is-test-matrix-empty=False
2025-09-07T07:44:10.9497329Z ##[group]Run echo "Filtered matrix:"
2025-09-07T07:44:10.9497579Z echo "Filtered matrix:"
2025-09-07T07:44:10.9500284Z echo "{"include": [{"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 1, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 2, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_huggingface_perf_cpu_x86_zen", "shard": 3, "num_shards": 3, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 1, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 2, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 3, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 4, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_timm_perf_cpu_x86_zen", "shard": 5, "num_shards": 5, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 1, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 2, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 3, "num_shards": 4, "runner": "linux.24xlarge.amd"}, {"config": "inductor_torchbench_perf_cpu_x86_zen", "shard": 4, "num_shards": 4, "runner": "linux.24xlarge.amd"}]}"
2025-09-07T07:44:10.9502887Z 
2025-09-07T07:44:10.9503025Z echo
2025-09-07T07:44:10.9503209Z echo "Is the current job unstable? False"
2025-09-07T07:44:10.9503490Z 
2025-09-07T07:44:10.9503627Z echo
2025-09-07T07:44:10.9503787Z echo "Is keep-going label set? True"
2025-09-07T07:44:10.9504177Z 
2025-09-07T07:44:10.9504317Z echo
2025-09-07T07:44:10.9504473Z echo "Reenabled issues? "
2025-09-07T07:44:10.9511735Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:10.9511978Z env:
2025-09-07T07:44:10.9512132Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:10.9512309Z ##[endgroup]
2025-09-07T07:44:10.9538056Z Filtered matrix:
2025-09-07T07:44:10.9541247Z {include: [{config: inductor_huggingface_perf_cpu_x86_zen, shard: 1, num_shards: 3, runner: linux.24xlarge.amd}, {config: inductor_huggingface_perf_cpu_x86_zen, shard: 2, num_shards: 3, runner: linux.24xlarge.amd}, {config: inductor_huggingface_perf_cpu_x86_zen, shard: 3, num_shards: 3, runner: linux.24xlarge.amd}, {config: inductor_timm_perf_cpu_x86_zen, shard: 1, num_shards: 5, runner: linux.24xlarge.amd}, {config: inductor_timm_perf_cpu_x86_zen, shard: 2, num_shards: 5, runner: linux.24xlarge.amd}, {config: inductor_timm_perf_cpu_x86_zen, shard: 3, num_shards: 5, runner: linux.24xlarge.amd}, {config: inductor_timm_perf_cpu_x86_zen, shard: 4, num_shards: 5, runner: linux.24xlarge.amd}, {config: inductor_timm_perf_cpu_x86_zen, shard: 5, num_shards: 5, runner: linux.24xlarge.amd}, {config: inductor_torchbench_perf_cpu_x86_zen, shard: 1, num_shards: 4, runner: linux.24xlarge.amd}, {config: inductor_torchbench_perf_cpu_x86_zen, shard: 2, num_shards: 4, runner: linux.24xlarge.amd}, {config: inductor_torchbench_perf_cpu_x86_zen, shard: 3, num_shards: 4, runner: linux.24xlarge.amd}, {config: inductor_torchbench_perf_cpu_x86_zen, shard: 4, num_shards: 4, runner: linux.24xlarge.amd}]}
2025-09-07T07:44:10.9543958Z 
2025-09-07T07:44:10.9544056Z Is the current job unstable? False
2025-09-07T07:44:10.9544189Z 
2025-09-07T07:44:10.9544270Z Is keep-going label set? True
2025-09-07T07:44:10.9544389Z 
2025-09-07T07:44:10.9544453Z Reenabled issues? 
2025-09-07T07:44:10.9676933Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
2025-09-07T07:44:10.9677272Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
2025-09-07T07:44:10.9683580Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:10.9683823Z env:
2025-09-07T07:44:10.9683975Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:10.9684147Z   JOB_TIMEOUT: 720
2025-09-07T07:44:10.9684295Z ##[endgroup]
2025-09-07T07:44:10.9830720Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-09-07T07:44:10.9831090Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-09-07T07:44:10.9831369Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
2025-09-07T07:44:10.9838371Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T07:44:10.9838617Z env:
2025-09-07T07:44:10.9838769Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:10.9838940Z ##[endgroup]
2025-09-07T07:44:10.9960620Z ##[group]Run set -x
2025-09-07T07:44:10.9960868Z set -x
2025-09-07T07:44:10.9961013Z 
2025-09-07T07:44:10.9961181Z if [[ $TEST_CONFIG == 'multigpu' ]]; then
2025-09-07T07:44:10.9961443Z   TEST_COMMAND=.ci/pytorch/multigpu-test.sh
2025-09-07T07:44:10.9961700Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then
2025-09-07T07:44:10.9961925Z   TEST_COMMAND=.ci/onnx/test.sh
2025-09-07T07:44:10.9962121Z else
2025-09-07T07:44:10.9962289Z   TEST_COMMAND=.ci/pytorch/test.sh
2025-09-07T07:44:10.9962482Z fi
2025-09-07T07:44:10.9962633Z 
2025-09-07T07:44:10.9962807Z # Leaving 1GB for the runner and other things
2025-09-07T07:44:10.9963164Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo)
2025-09-07T07:44:10.9963716Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap
2025-09-07T07:44:10.9964147Z # comes from https://github.com/pytorch/test-infra/pull/6058
2025-09-07T07:44:10.9964481Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3))
2025-09-07T07:44:10.9964741Z 
2025-09-07T07:44:10.9964923Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
2025-09-07T07:44:10.9965137Z   SHM_OPTS=
2025-09-07T07:44:10.9965309Z   JENKINS_USER=
2025-09-07T07:44:10.9965531Z   # ensure that docker container cleanly exits in 12 hours
2025-09-07T07:44:10.9965828Z   # if for some reason cleanup action doesn't stop container
2025-09-07T07:44:10.9966083Z   # when job is cancelled
2025-09-07T07:44:10.9966277Z   DOCKER_SHELL_CMD="sleep 12h"
2025-09-07T07:44:10.9966470Z else
2025-09-07T07:44:10.9966639Z   SHM_OPTS="--shm-size=${SHM_SIZE}"
2025-09-07T07:44:10.9966853Z   JENKINS_USER="--user jenkins"
2025-09-07T07:44:10.9967048Z   DOCKER_SHELL_CMD=
2025-09-07T07:44:10.9967220Z fi
2025-09-07T07:44:10.9967360Z 
2025-09-07T07:44:10.9967573Z # detached container should get cleaned up by teardown_ec2_linux
2025-09-07T07:44:10.9967890Z # TODO: Stop building test binaries as part of the build phase
2025-09-07T07:44:10.9968258Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice
2025-09-07T07:44:10.9968580Z # shellcheck disable=SC2086,SC2090
2025-09-07T07:44:10.9968796Z container_name=$(docker run \
2025-09-07T07:44:10.9969000Z   ${GPU_FLAG:-} \
2025-09-07T07:44:10.9969345Z   ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \
2025-09-07T07:44:10.9969568Z   -e BUILD_ENVIRONMENT \
2025-09-07T07:44:10.9969763Z   -e PR_NUMBER \
2025-09-07T07:44:10.9969939Z   -e GITHUB_ACTIONS \
2025-09-07T07:44:10.9970130Z   -e GITHUB_REPOSITORY \
2025-09-07T07:44:10.9970343Z   -e GITHUB_WORKFLOW \
2025-09-07T07:44:10.9970545Z   -e GITHUB_JOB \
2025-09-07T07:44:10.9970726Z   -e GITHUB_RUN_ID \
2025-09-07T07:44:10.9970904Z   -e GITHUB_RUN_NUMBER \
2025-09-07T07:44:10.9971099Z   -e GITHUB_RUN_ATTEMPT \
2025-09-07T07:44:10.9971292Z   -e JOB_ID \
2025-09-07T07:44:10.9971462Z   -e JOB_NAME \
2025-09-07T07:44:10.9971622Z   -e BASE_SHA \
2025-09-07T07:44:10.9971786Z   -e BRANCH \
2025-09-07T07:44:10.9971945Z   -e SHA1 \
2025-09-07T07:44:10.9972113Z   -e AWS_DEFAULT_REGION \
2025-09-07T07:44:10.9972301Z   -e IN_WHEEL_TEST \
2025-09-07T07:44:10.9972481Z   -e SHARD_NUMBER \
2025-09-07T07:44:10.9972661Z   -e TEST_CONFIG \
2025-09-07T07:44:10.9972845Z   -e NUM_TEST_SHARDS \
2025-09-07T07:44:10.9973024Z   -e REENABLED_ISSUES \
2025-09-07T07:44:10.9973220Z   -e CONTINUE_THROUGH_ERROR \
2025-09-07T07:44:10.9973525Z   -e VERBOSE_TEST_LOGS \
2025-09-07T07:44:10.9973720Z   -e TEST_SHOWLOCALS \
2025-09-07T07:44:10.9973897Z   -e NO_TEST_TIMEOUT \
2025-09-07T07:44:10.9974091Z   -e NO_TD \
2025-09-07T07:44:10.9974261Z   -e TD_DISTRIBUTED \
2025-09-07T07:44:10.9974441Z   -e PR_LABELS \
2025-09-07T07:44:10.9974633Z   -e MAX_JOBS="$(nproc --ignore=2)" \
2025-09-07T07:44:10.9974845Z   -e SCCACHE_BUCKET \
2025-09-07T07:44:10.9975022Z   -e SCCACHE_REGION \
2025-09-07T07:44:10.9975199Z   -e XLA_CUDA \
2025-09-07T07:44:10.9975380Z   -e XLA_CLANG_CACHE_S3_BUCKET_NAME \
2025-09-07T07:44:10.9975611Z   -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \
2025-09-07T07:44:10.9975843Z   -e PYTORCH_TEST_RERUN_DISABLED_TESTS \
2025-09-07T07:44:10.9976072Z   -e SKIP_SCCACHE_INITIALIZATION=1 \
2025-09-07T07:44:10.9976291Z   -e HUGGING_FACE_HUB_TOKEN \
2025-09-07T07:44:10.9976496Z   -e VLLM_TEST_HUGGING_FACE_TOKEN \
2025-09-07T07:44:10.9976719Z   -e SCRIBE_GRAPHQL_ACCESS_TOKEN \
2025-09-07T07:44:10.9976927Z   -e DASHBOARD_TAG \
2025-09-07T07:44:10.9977114Z   -e ARTIFACTS_FILE_SUFFIX \
2025-09-07T07:44:10.9977340Z   --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \
2025-09-07T07:44:10.9977604Z   --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \
2025-09-07T07:44:10.9977862Z   --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
2025-09-07T07:44:10.9978111Z   --security-opt seccomp=unconfined \
2025-09-07T07:44:10.9978324Z   --cap-add=SYS_PTRACE \
2025-09-07T07:44:10.9978518Z   --ipc=host \
2025-09-07T07:44:10.9978688Z   ${SHM_OPTS} \
2025-09-07T07:44:10.9978860Z   --tty \
2025-09-07T07:44:10.9979012Z   --detach \
2025-09-07T07:44:10.9979189Z   --name="${container_name}" \
2025-09-07T07:44:10.9979387Z   ${JENKINS_USER} \
2025-09-07T07:44:10.9979613Z   -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
2025-09-07T07:44:10.9979865Z   -w /var/lib/jenkins/workspace \
2025-09-07T07:44:10.9980064Z   "${DOCKER_IMAGE}" \
2025-09-07T07:44:10.9993066Z   ${DOCKER_SHELL_CMD}
2025-09-07T07:44:10.9993262Z )
2025-09-07T07:44:10.9993472Z # Propagate download.pytorch.org IP to container
2025-09-07T07:44:10.9993888Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts"
2025-09-07T07:44:10.9994318Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
2025-09-07T07:44:10.9994706Z 
2025-09-07T07:44:10.9994881Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
2025-09-07T07:44:10.9995240Z   docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt"
2025-09-07T07:44:10.9995558Z fi
2025-09-07T07:44:10.9995693Z 
2025-09-07T07:44:10.9995998Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}"
2025-09-07T07:44:11.0003589Z shell: /usr/bin/bash -e {0}
2025-09-07T07:44:11.0003765Z env:
2025-09-07T07:44:11.0003908Z   GIT_DEFAULT_BRANCH: main
2025-09-07T07:44:11.0004120Z   BUILD_ENVIRONMENT: linux-jammy-py3.9-gcc11-build
2025-09-07T07:44:11.0004340Z   PR_NUMBER: 
2025-09-07T07:44:11.0004496Z   GITHUB_REPOSITORY: pytorch/pytorch
2025-09-07T07:44:11.0004731Z   GITHUB_WORKFLOW: inductor-perf-nightly-x86-zen
2025-09-07T07:44:11.0004952Z   GITHUB_JOB: test
2025-09-07T07:44:11.0005109Z   GITHUB_RUN_ID: 17525294857
2025-09-07T07:44:11.0005280Z   GITHUB_RUN_NUMBER: 91
2025-09-07T07:44:11.0005446Z   GITHUB_RUN_ATTEMPT: 1
2025-09-07T07:44:11.0005605Z   JOB_ID: 49775530523
2025-09-07T07:44:11.0005917Z   JOB_NAME: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:44:11.0006246Z   BRANCH: main
2025-09-07T07:44:11.0006571Z   SHA1: 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:44:11.0006814Z   BASE_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:44:11.0007060Z   TEST_CONFIG: inductor_torchbench_perf_cpu_x86_zen
2025-09-07T07:44:11.0007275Z   SHARD_NUMBER: 1
2025-09-07T07:44:11.0007421Z   NUM_TEST_SHARDS: 4
2025-09-07T07:44:11.0007572Z   REENABLED_ISSUES: 
2025-09-07T07:44:11.0007737Z   CONTINUE_THROUGH_ERROR: True
2025-09-07T07:44:11.0007920Z   VERBOSE_TEST_LOGS: False
2025-09-07T07:44:11.0008085Z   TEST_SHOWLOCALS: False
2025-09-07T07:44:11.0008255Z   NO_TEST_TIMEOUT: False
2025-09-07T07:44:11.0008422Z   NO_TD: False
2025-09-07T07:44:11.0008577Z   TD_DISTRIBUTED: False
2025-09-07T07:44:11.0008771Z   SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
2025-09-07T07:44:11.0008998Z   SCCACHE_REGION: us-east-1
2025-09-07T07:44:11.0009176Z   SHM_SIZE: 1g
2025-09-07T07:44:11.0009687Z   DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:44:11.0010215Z   XLA_CUDA: 
2025-09-07T07:44:11.0010443Z   XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla
2025-09-07T07:44:11.0010745Z   PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0
2025-09-07T07:44:11.0010951Z   PYTORCH_TEST_RERUN_DISABLED_TESTS: 0
2025-09-07T07:44:11.0011364Z   DASHBOARD_TAG: training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true
2025-09-07T07:44:11.0011921Z   VLLM_TEST_HUGGING_FACE_TOKEN: ***
2025-09-07T07:44:11.0012196Z   HUGGING_FACE_HUB_TOKEN: ***
2025-09-07T07:44:11.0012461Z   SCRIBE_GRAPHQL_ACCESS_TOKEN: ***
2025-09-07T07:44:11.0012798Z   ARTIFACTS_FILE_SUFFIX: test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T07:44:11.0013137Z ##[endgroup]
2025-09-07T07:44:11.0037179Z + [[ inductor_torchbench_perf_cpu_x86_zen == \m\u\l\t\i\g\p\u ]]
2025-09-07T07:44:11.0037485Z + [[ linux-jammy-py3.9-gcc11-build == *onnx* ]]
2025-09-07T07:44:11.0037740Z + TEST_COMMAND=.ci/pytorch/test.sh
2025-09-07T07:44:11.0040954Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo
2025-09-07T07:44:11.0062455Z + TOTAL_AVAILABLE_MEMORY_IN_GB='368.765 '
2025-09-07T07:44:11.0062781Z + TOTAL_MEMORY_WITH_SWAP=371
2025-09-07T07:44:11.0063044Z + [[ linux-jammy-py3.9-gcc11-build == *\s\3\9\0\x* ]]
2025-09-07T07:44:11.0063281Z + SHM_OPTS=--shm-size=1g
2025-09-07T07:44:11.0063462Z + JENKINS_USER='--user jenkins'
2025-09-07T07:44:11.0063641Z + DOCKER_SHELL_CMD=
2025-09-07T07:44:11.0072457Z +++ nproc --ignore=2
2025-09-07T07:44:11.0328495Z ++ docker run -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=94 -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=368g --memory-swap=371g --env-file=/tmp/github_env_17525294857 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=1g --tty --detach --name= --user jenkins -v /home/ec2-user/actions-runner/_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-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T07:46:55.8098705Z + container_name=79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T07:46:55.8104609Z + grep download.pytorch.org /etc/hosts
2025-09-07T07:46:55.8106997Z + docker exec -i 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8 sudo bash -c '/bin/cat >> /etc/hosts'
2025-09-07T07:46:55.9685859Z + echo DOCKER_CONTAINER_ID=79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T07:46:55.9687028Z + [[ linux-jammy-py3.9-gcc11-build == *\s\3\9\0\x* ]]
2025-09-07T07:46:55.9692322Z ++ echo dist/torch-2.9.0a0+git93fb23d-cp39-cp39-linux_x86_64.whl
2025-09-07T07:46:55.9694828Z + docker exec -t 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8 sh -c 'python3 -m pip install dist/torch-2.9.0a0+git93fb23d-cp39-cp39-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh'
2025-09-07T07:46:56.3234938Z Processing ./dist/torch-2.9.0a0+git93fb23d-cp39-cp39-linux_x86_64.whl (from torch==2.9.0a0+git93fb23d)
2025-09-07T07:46:56.5252229Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.19.1)
2025-09-07T07:46:56.5253536Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (4.15.0)
2025-09-07T07:46:56.5256413Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.13.3)
2025-09-07T07:46:56.5259438Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (2.8.8)
2025-09-07T07:46:56.5261508Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.1.6)
2025-09-07T07:46:56.5264326Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (2025.3.0)
2025-09-07T07:46:56.5275163Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.3.0)
2025-09-07T07:46:56.5538376Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from opt-einsum>=3.3->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.22.4)
2025-09-07T07:46:56.5551951Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from sympy>=1.13.3->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (1.3.0)
2025-09-07T07:46:56.5580165Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from jinja2->torch==2.9.0a0+git93fb23d->torch==2.9.0a0+git93fb23d) (3.0.2)
2025-09-07T07:46:57.2685292Z Installing collected packages: torch
2025-09-07T07:47:04.4524677Z 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.
2025-09-07T07:47:04.4525310Z dall-e 0.1 requires torchvision, which is not installed.
2025-09-07T07:47:04.4525585Z effdet 0.4.1 requires torchvision, which is not installed.
2025-09-07T07:47:04.4525932Z pytorch-labs-segment-anything-fast 0.2 requires torchao, which is not installed.
2025-09-07T07:47:04.4526399Z pytorch-labs-segment-anything-fast 0.2 requires torchvision>=0.17.0.dev20231026, which is not installed.
2025-09-07T07:47:04.4526870Z timm 1.0.14 requires torchvision, which is not installed.
2025-09-07T07:47:04.4527207Z Successfully installed torch-2.9.0a0+git93fb23d
2025-09-07T07:47:04.5320759Z + export TERM=vt100
2025-09-07T07:47:04.5321015Z + TERM=vt100
2025-09-07T07:47:04.5323531Z ++ dirname .ci/pytorch/test.sh
2025-09-07T07:47:04.5334210Z + source .ci/pytorch/common.sh
2025-09-07T07:47:04.5338533Z +++ dirname .ci/pytorch/common.sh
2025-09-07T07:47:04.5349627Z ++ source .ci/pytorch/common_utils.sh
2025-09-07T07:47:04.5349852Z +++ declare -f -t trap_add
2025-09-07T07:47:04.5353182Z ++ set -ex -o pipefail
2025-09-07T07:47:04.5353383Z ++ [[ linux-jammy-py3.9-gcc11-build == *rocm* ]]
2025-09-07T07:47:04.5353594Z ++ BUILD_TEST_LIBTORCH=0
2025-09-07T07:47:04.5357390Z ++ dirname .ci/pytorch/test.sh
2025-09-07T07:47:04.5367259Z + source .ci/pytorch/common-build.sh
2025-09-07T07:47:04.5368522Z ++ [[ linux-jammy-py3.9-gcc11-build != *win-* ]]
2025-09-07T07:47:04.5377110Z ++++ dirname .ci/pytorch/common-build.sh
2025-09-07T07:47:04.5387110Z +++ cd .ci/pytorch
2025-09-07T07:47:04.5387474Z +++ pwd -P
2025-09-07T07:47:04.5389943Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch
2025-09-07T07:47:04.5390233Z ++ [[ linux-jammy-py3.9-gcc11-build == *-pch* ]]
2025-09-07T07:47:04.5390455Z ++ which sccache
2025-09-07T07:47:04.5412065Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]]
2025-09-07T07:47:04.5412292Z ++ sccache --stop-server
2025-09-07T07:47:04.5444118Z ++ true
2025-09-07T07:47:04.5444286Z ++ rm -f /var/lib/jenkins/sccache_error.log
2025-09-07T07:47:04.5454343Z ++ trap_add sccache_epilogue EXIT
2025-09-07T07:47:04.5454558Z ++ trap_add_cmd=sccache_epilogue
2025-09-07T07:47:04.5454736Z ++ shift
2025-09-07T07:47:04.5454888Z ++ for trap_add_name in "$@"
2025-09-07T07:47:04.5461776Z ++++ trap -p EXIT
2025-09-07T07:47:04.5464655Z +++ eval 'extract_trap_cmd '
2025-09-07T07:47:04.5464835Z ++++ extract_trap_cmd
2025-09-07T07:47:04.5465003Z ++++ printf '%s\n' ''
2025-09-07T07:47:04.5465385Z +++ printf '%s\n' sccache_epilogue
2025-09-07T07:47:04.5467389Z ++ trap -- '
2025-09-07T07:47:04.5467551Z sccache_epilogue' EXIT
2025-09-07T07:47:04.5467766Z ++ [[ -n 1 ]]
2025-09-07T07:47:04.5468018Z ++ echo 'Skipping sccache server initialization, setting environment variables'
2025-09-07T07:47:04.5468398Z Skipping sccache server initialization, setting environment variables
2025-09-07T07:47:04.5468680Z ++ export SCCACHE_IDLE_TIMEOUT=0
2025-09-07T07:47:04.5468868Z ++ SCCACHE_IDLE_TIMEOUT=0
2025-09-07T07:47:04.5469102Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-09-07T07:47:04.5469380Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-09-07T07:47:04.5469657Z ++ export RUST_LOG=sccache::server=error
2025-09-07T07:47:04.5469867Z ++ RUST_LOG=sccache::server=error
2025-09-07T07:47:04.5470047Z ++ sccache --zero-stats
2025-09-07T07:47:04.7072815Z Statistics zeroed.
2025-09-07T07:47:04.7081335Z ++ which ccache
2025-09-07T07:47:04.7106658Z + [[ linux-jammy-py3.9-gcc11-build != *rocm* ]]
2025-09-07T07:47:04.7106923Z + [[ linux-jammy-py3.9-gcc11-build != *s390x* ]]
2025-09-07T07:47:04.7107166Z + [[ -d /var/lib/jenkins/workspace ]]
2025-09-07T07:47:04.7110353Z ++ stat -c %u /var/lib/jenkins/workspace
2025-09-07T07:47:04.7128026Z + WORKSPACE_ORIGINAL_OWNER_ID=1000
2025-09-07T07:47:04.7128239Z + trap_add cleanup_workspace EXIT
2025-09-07T07:47:04.7128437Z + trap_add_cmd=cleanup_workspace
2025-09-07T07:47:04.7128624Z + shift
2025-09-07T07:47:04.7128776Z + for trap_add_name in "$@"
2025-09-07T07:47:04.7135619Z +++ trap -p EXIT
2025-09-07T07:47:04.7138414Z ++ eval 'extract_trap_cmd trap -- '\''
2025-09-07T07:47:04.7138919Z sccache_epilogue'\'' EXIT'
2025-09-07T07:47:04.7139172Z +++ extract_trap_cmd trap -- '
2025-09-07T07:47:04.7139373Z sccache_epilogue' EXIT
2025-09-07T07:47:04.7139532Z +++ printf '%s\n' '
2025-09-07T07:47:04.7139691Z sccache_epilogue'
2025-09-07T07:47:04.7139861Z ++ printf '%s\n' cleanup_workspace
2025-09-07T07:47:04.7141574Z + trap -- '
2025-09-07T07:47:04.7141759Z sccache_epilogue
2025-09-07T07:47:04.7141932Z cleanup_workspace' EXIT
2025-09-07T07:47:04.7142164Z + sudo chown -R jenkins /var/lib/jenkins/workspace
2025-09-07T07:47:05.5242317Z + git config --global --add safe.directory /var/lib/jenkins/workspace
2025-09-07T07:47:05.5263536Z + echo 'Environment variables:'
2025-09-07T07:47:05.5263737Z Environment variables:
2025-09-07T07:47:05.5263885Z + env
2025-09-07T07:47:05.5274968Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-09-07T07:47:05.5275293Z CONTINUE_THROUGH_ERROR=True
2025-09-07T07:47:05.5275521Z BUILD_ENVIRONMENT=linux-jammy-py3.9-gcc11-build
2025-09-07T07:47:05.5276421Z VLLM_TEST_HUGGING_FACE_TOKEN=***
2025-09-07T07:47:05.5276613Z HOSTNAME=79fc4b4803c2
2025-09-07T07:47:05.5276982Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5277362Z GITHUB_ACTION=__run_2
2025-09-07T07:47:05.5277536Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0
2025-09-07T07:47:05.5277721Z GITHUB_RUN_NUMBER=91
2025-09-07T07:47:05.5277911Z TEST_CONFIG=inductor_torchbench_perf_cpu_x86_zen
2025-09-07T07:47:05.5278139Z GITHUB_REPOSITORY_OWNER_ID=21003710
2025-09-07T07:47:05.5278354Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all
2025-09-07T07:47:05.5278567Z SCCACHE_IDLE_TIMEOUT=0
2025-09-07T07:47:05.5278818Z SCRIBE_GRAPHQL_ACCESS_TOKEN=***
2025-09-07T07:47:05.5279048Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot
2025-09-07T07:47:05.5279248Z GITHUB_REF_TYPE=branch
2025-09-07T07:47:05.5279438Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5279650Z XLA_CUDA=
2025-09-07T07:47:05.5279809Z NCCL_LIB_DIR=/usr/local/cuda/lib64/
2025-09-07T07:47:05.5280107Z HUGGING_FACE_HUB_TOKEN=***
2025-09-07T07:47:05.5284475Z ***
2025-09-07T07:47:05.5284638Z GITHUB_REPOSITORY_ID=65600975
2025-09-07T07:47:05.5284838Z GITHUB_ACTIONS=true
2025-09-07T07:47:05.5285032Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-09-07T07:47:05.5285283Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5285519Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5285941Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-x86-zen.yml@refs/heads/main
2025-09-07T07:47:05.5286313Z UCC_HOME=/usr
2025-09-07T07:47:05.5286480Z VERBOSE_TEST_LOGS=False
2025-09-07T07:47:05.5286654Z GITHUB_REF=refs/heads/main
2025-09-07T07:47:05.5286823Z SHARD_NUMBER=1
2025-09-07T07:47:05.5286973Z GITHUB_REF_PROTECTED=true
2025-09-07T07:47:05.5287141Z HOME=/var/lib/jenkins
2025-09-07T07:47:05.5287327Z GITHUB_API_URL=https://api.github.com
2025-09-07T07:47:05.5287544Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0
2025-09-07T07:47:05.5287731Z UCX_COMMIT=
2025-09-07T07:47:05.5287869Z USE_SYSTEM_NCCL=1
2025-09-07T07:47:05.5288020Z NUM_TEST_SHARDS=4
2025-09-07T07:47:05.5288153Z UCX_HOME=/usr
2025-09-07T07:47:05.5288515Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5289057Z JOB_NAME=inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:47:05.5289581Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5290261Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json
2025-09-07T07:47:05.5290556Z GITHUB_EVENT_NAME=schedule
2025-09-07T07:47:05.5290952Z DASHBOARD_TAG=training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true
2025-09-07T07:47:05.5291359Z GITHUB_RUN_ID=17525294857
2025-09-07T07:47:05.5291527Z INSTALLED_OPENBLAS=
2025-09-07T07:47:05.5291904Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5292316Z GITHUB_ACTOR=pytorchmergebot
2025-09-07T07:47:05.5292492Z PR_NUMBER=
2025-09-07T07:47:05.5292634Z DESIRED_CUDA=
2025-09-07T07:47:05.5292781Z GITHUB_RUN_ATTEMPT=1
2025-09-07T07:47:05.5292942Z ANACONDA_PYTHON_VERSION=3.9
2025-09-07T07:47:05.5293158Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql
2025-09-07T07:47:05.5293393Z TERM=vt100
2025-09-07T07:47:05.5293529Z INSTALLED_VISION=yes
2025-09-07T07:47:05.5293673Z BRANCH=main
2025-09-07T07:47:05.5293820Z SCCACHE_REGION=us-east-1
2025-09-07T07:47:05.5293997Z OPENSSL_ROOT_DIR=/opt/openssl
2025-09-07T07:47:05.5294179Z CUDA_PATH=/usr/local/cuda
2025-09-07T07:47:05.5294493Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux
2025-09-07T07:47:05.5294848Z GITHUB_SERVER_URL=https://github.com
2025-09-07T07:47:05.5295036Z UCC_COMMIT=
2025-09-07T07:47:05.5296352Z REENABLED_ISSUES=
2025-09-07T07:47:05.5296518Z DOCS=yes
2025-09-07T07:47:05.5296656Z SHLVL=1
2025-09-07T07:47:05.5296784Z MAX_JOBS=94
2025-09-07T07:47:05.5296926Z GITHUB_ACTOR_ID=97764156
2025-09-07T07:47:05.5297139Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5297377Z GITHUB_REF_NAME=main
2025-09-07T07:47:05.5297620Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla
2025-09-07T07:47:05.5297885Z GITHUB_JOB=test
2025-09-07T07:47:05.5298028Z NO_TEST_TIMEOUT=False
2025-09-07T07:47:05.5298185Z TD_DISTRIBUTED=False
2025-09-07T07:47:05.5298362Z GITHUB_REPOSITORY=pytorch/pytorch
2025-09-07T07:47:05.5298563Z GITHUB_RETENTION_DAYS=90
2025-09-07T07:47:05.5298923Z OPENSSL_DIR=/opt/openssl
2025-09-07T07:47:05.5299103Z GITHUB_ACTION_REPOSITORY=
2025-09-07T07:47:05.5299575Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.9/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-09-07T07:47:05.5300062Z GITHUB_BASE_REF=
2025-09-07T07:47:05.5300208Z INSTALLED_ACL=
2025-09-07T07:47:05.5300507Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T07:47:05.5300835Z CI=true
2025-09-07T07:47:05.5300987Z GITHUB_REPOSITORY_OWNER=pytorch
2025-09-07T07:47:05.5301208Z RUST_LOG=sccache::server=error
2025-09-07T07:47:05.5301381Z JOB_ID=49775530523
2025-09-07T07:47:05.5301530Z GITHUB_HEAD_REF=
2025-09-07T07:47:05.5301678Z GITHUB_ACTION_REF=
2025-09-07T07:47:05.5301862Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
2025-09-07T07:47:05.5302084Z TEST_SHOWLOCALS=False
2025-09-07T07:47:05.5302284Z GITHUB_WORKFLOW=inductor-perf-nightly-x86-zen
2025-09-07T07:47:05.5302509Z DEBIAN_FRONTEND=noninteractive
2025-09-07T07:47:05.5302888Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5303280Z NO_TD=False
2025-09-07T07:47:05.5303435Z SKIP_SCCACHE_INITIALIZATION=1
2025-09-07T07:47:05.5303631Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/
2025-09-07T07:47:05.5303818Z _=/usr/bin/env
2025-09-07T07:47:05.5304029Z ++ python -c 'import site; print(site.getsitepackages()[0])'
2025-09-07T07:47:05.5540505Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch
2025-09-07T07:47:05.5540895Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/bin
2025-09-07T07:47:05.5541245Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/lib
2025-09-07T07:47:05.5541586Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/test
2025-09-07T07:47:05.5542091Z + BUILD_DIR=build
2025-09-07T07:47:05.5542262Z + BUILD_RENAMED_DIR=build_renamed
2025-09-07T07:47:05.5542457Z + BUILD_BIN_DIR=build/bin
2025-09-07T07:47:05.5542620Z + SHARD_NUMBER=1
2025-09-07T07:47:05.5542778Z + NUM_TEST_SHARDS=4
2025-09-07T07:47:05.5542951Z + export TORCH_SERIALIZATION_DEBUG=1
2025-09-07T07:47:05.5543152Z + TORCH_SERIALIZATION_DEBUG=1
2025-09-07T07:47:05.5543335Z + export VALGRIND=ON
2025-09-07T07:47:05.5543495Z + VALGRIND=ON
2025-09-07T07:47:05.5543681Z + [[ linux-jammy-py3.9-gcc11-build == *clang9* ]]
2025-09-07T07:47:05.5543923Z + [[ linux-jammy-py3.9-gcc11-build == *xpu* ]]
2025-09-07T07:47:05.5544119Z + detect_cuda_arch
2025-09-07T07:47:05.5544299Z + [[ linux-jammy-py3.9-gcc11-build == *cuda* ]]
2025-09-07T07:47:05.5544537Z + [[ linux-jammy-py3.9-gcc11-build == *s390x* ]]
2025-09-07T07:47:05.5544738Z + [[ 0 == \1 ]]
2025-09-07T07:47:05.5544876Z + [[ True == \1 ]]
2025-09-07T07:47:05.5545047Z + [[ linux-jammy-py3.9-gcc11-build != *bazel* ]]
2025-09-07T07:47:05.5546164Z ++ realpath build/custom_test_artifacts
2025-09-07T07:47:05.5557951Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts
2025-09-07T07:47:05.5558408Z + [[ -n '' ]]
2025-09-07T07:47:05.5558559Z + echo 'Environment variables'
2025-09-07T07:47:05.5558742Z Environment variables
2025-09-07T07:47:05.5558899Z + env
2025-09-07T07:47:05.5578606Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-09-07T07:47:05.5578873Z CONTINUE_THROUGH_ERROR=True
2025-09-07T07:47:05.5579104Z BUILD_ENVIRONMENT=linux-jammy-py3.9-gcc11-build
2025-09-07T07:47:05.5579448Z VLLM_TEST_HUGGING_FACE_TOKEN=***
2025-09-07T07:47:05.5579634Z HOSTNAME=79fc4b4803c2
2025-09-07T07:47:05.5579993Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5580371Z GITHUB_ACTION=__run_2
2025-09-07T07:47:05.5580543Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0
2025-09-07T07:47:05.5580732Z GITHUB_RUN_NUMBER=91
2025-09-07T07:47:05.5580926Z TEST_CONFIG=inductor_torchbench_perf_cpu_x86_zen
2025-09-07T07:47:05.5581146Z GITHUB_REPOSITORY_OWNER_ID=21003710
2025-09-07T07:47:05.5581357Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all
2025-09-07T07:47:05.5581551Z SCCACHE_IDLE_TIMEOUT=0
2025-09-07T07:47:05.5581797Z SCRIBE_GRAPHQL_ACCESS_TOKEN=***
2025-09-07T07:47:05.5581997Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot
2025-09-07T07:47:05.5582197Z GITHUB_REF_TYPE=branch
2025-09-07T07:47:05.5582386Z BASE_SHA=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5582600Z XLA_CUDA=
2025-09-07T07:47:05.5582754Z NCCL_LIB_DIR=/usr/local/cuda/lib64/
2025-09-07T07:47:05.5583047Z HUGGING_FACE_HUB_TOKEN=***
2025-09-07T07:47:05.5583254Z ***
2025-09-07T07:47:05.5583394Z GITHUB_REPOSITORY_ID=65600975
2025-09-07T07:47:05.5583574Z GITHUB_ACTIONS=true
2025-09-07T07:47:05.5583762Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log
2025-09-07T07:47:05.5584008Z SHA1=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5584235Z GITHUB_SHA=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5584650Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/inductor-perf-test-nightly-x86-zen.yml@refs/heads/main
2025-09-07T07:47:05.5585026Z UCC_HOME=/usr
2025-09-07T07:47:05.5585174Z TORCH_SERIALIZATION_DEBUG=1
2025-09-07T07:47:05.5585350Z VERBOSE_TEST_LOGS=False
2025-09-07T07:47:05.5585519Z GITHUB_REF=refs/heads/main
2025-09-07T07:47:05.5585729Z SHARD_NUMBER=1
2025-09-07T07:47:05.5585875Z GITHUB_REF_PROTECTED=true
2025-09-07T07:47:05.5586042Z HOME=/var/lib/jenkins
2025-09-07T07:47:05.5586220Z GITHUB_API_URL=https://api.github.com
2025-09-07T07:47:05.5586432Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0
2025-09-07T07:47:05.5586612Z UCX_COMMIT=
2025-09-07T07:47:05.5586754Z USE_SYSTEM_NCCL=1
2025-09-07T07:47:05.5586904Z NUM_TEST_SHARDS=4
2025-09-07T07:47:05.5587041Z UCX_HOME=/usr
2025-09-07T07:47:05.5587427Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5588053Z JOB_NAME=inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T07:47:05.5588570Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5589053Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json
2025-09-07T07:47:05.5589360Z GITHUB_EVENT_NAME=schedule
2025-09-07T07:47:05.5589754Z DASHBOARD_TAG=training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true
2025-09-07T07:47:05.5590158Z GITHUB_RUN_ID=17525294857
2025-09-07T07:47:05.5590326Z INSTALLED_OPENBLAS=
2025-09-07T07:47:05.5590702Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5591118Z GITHUB_ACTOR=pytorchmergebot
2025-09-07T07:47:05.5591291Z PR_NUMBER=
2025-09-07T07:47:05.5591427Z DESIRED_CUDA=
2025-09-07T07:47:05.5591576Z GITHUB_RUN_ATTEMPT=1
2025-09-07T07:47:05.5591735Z VALGRIND=ON
2025-09-07T07:47:05.5591879Z ANACONDA_PYTHON_VERSION=3.9
2025-09-07T07:47:05.5592091Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql
2025-09-07T07:47:05.5592306Z TERM=vt100
2025-09-07T07:47:05.5592445Z INSTALLED_VISION=yes
2025-09-07T07:47:05.5592591Z BRANCH=main
2025-09-07T07:47:05.5592738Z SCCACHE_REGION=us-east-1
2025-09-07T07:47:05.5593009Z OPENSSL_ROOT_DIR=/opt/openssl
2025-09-07T07:47:05.5593187Z CUDA_PATH=/usr/local/cuda
2025-09-07T07:47:05.5593507Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux
2025-09-07T07:47:05.5593856Z GITHUB_SERVER_URL=https://github.com
2025-09-07T07:47:05.5594046Z UCC_COMMIT=
2025-09-07T07:47:05.5594184Z REENABLED_ISSUES=
2025-09-07T07:47:05.5594326Z DOCS=yes
2025-09-07T07:47:05.5594455Z SHLVL=1
2025-09-07T07:47:05.5594589Z MAX_JOBS=94
2025-09-07T07:47:05.5594724Z GITHUB_ACTOR_ID=97764156
2025-09-07T07:47:05.5594942Z GITHUB_WORKFLOW_SHA=93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T07:47:05.5595179Z GITHUB_REF_NAME=main
2025-09-07T07:47:05.5595427Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla
2025-09-07T07:47:05.5595686Z GITHUB_JOB=test
2025-09-07T07:47:05.5595845Z NO_TEST_TIMEOUT=False
2025-09-07T07:47:05.5596008Z TD_DISTRIBUTED=False
2025-09-07T07:47:05.5596178Z GITHUB_REPOSITORY=pytorch/pytorch
2025-09-07T07:47:05.5596366Z GITHUB_RETENTION_DAYS=90
2025-09-07T07:47:05.5596539Z OPENSSL_DIR=/opt/openssl
2025-09-07T07:47:05.5596710Z GITHUB_ACTION_REPOSITORY=
2025-09-07T07:47:05.5597181Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.9/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-09-07T07:47:05.5597652Z GITHUB_BASE_REF=
2025-09-07T07:47:05.5597796Z INSTALLED_ACL=
2025-09-07T07:47:05.5598090Z ARTIFACTS_FILE_SUFFIX=test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T07:47:05.5598418Z CI=true
2025-09-07T07:47:05.5598564Z GITHUB_REPOSITORY_OWNER=pytorch
2025-09-07T07:47:05.5598904Z RUST_LOG=sccache::server=error
2025-09-07T07:47:05.5599082Z JOB_ID=49775530523
2025-09-07T07:47:05.5599231Z GITHUB_HEAD_REF=
2025-09-07T07:47:05.5599372Z GITHUB_ACTION_REF=
2025-09-07T07:47:05.5599558Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2
2025-09-07T07:47:05.5599777Z TEST_SHOWLOCALS=False
2025-09-07T07:47:05.5599973Z GITHUB_WORKFLOW=inductor-perf-nightly-x86-zen
2025-09-07T07:47:05.5600189Z DEBIAN_FRONTEND=noninteractive
2025-09-07T07:47:05.5600578Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_e02bbb43-c1df-4636-a27c-5259dc7f3157
2025-09-07T07:47:05.5600958Z NO_TD=False
2025-09-07T07:47:05.5601110Z SKIP_SCCACHE_INITIALIZATION=1
2025-09-07T07:47:05.5601304Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/
2025-09-07T07:47:05.5601491Z _=/usr/bin/env
2025-09-07T07:47:05.5601641Z + echo 'Testing pytorch'
2025-09-07T07:47:05.5601808Z Testing pytorch
2025-09-07T07:47:05.5601958Z + export LANG=C.UTF-8
2025-09-07T07:47:05.5602109Z + LANG=C.UTF-8
2025-09-07T07:47:05.5602369Z + PR_NUMBER=
2025-09-07T07:47:05.5602566Z + [[ inductor_torchbench_perf_cpu_x86_zen == \d\e\f\a\u\l\t ]]
2025-09-07T07:47:05.5602868Z + [[ inductor_torchbench_perf_cpu_x86_zen == \d\i\s\t\r\i\b\u\t\e\d ]]
2025-09-07T07:47:05.5603142Z + [[ inductor_torchbench_perf_cpu_x86_zen == \s\l\o\w ]]
2025-09-07T07:47:05.5603418Z + [[ linux-jammy-py3.9-gcc11-build == *slow-gradcheck* ]]
2025-09-07T07:47:05.5603672Z + [[ linux-jammy-py3.9-gcc11-build == *cuda* ]]
2025-09-07T07:47:05.5603900Z + [[ linux-jammy-py3.9-gcc11-build == *rocm* ]]
2025-09-07T07:47:05.5604116Z + [[ linux-jammy-py3.9-gcc11-build == *xpu* ]]
2025-09-07T07:47:05.5604371Z + [[ inductor_torchbench_perf_cpu_x86_zen == *crossref* ]]
2025-09-07T07:47:05.5604617Z + [[ linux-jammy-py3.9-gcc11-build == *rocm* ]]
2025-09-07T07:47:05.5604861Z + [[ linux-jammy-py3.9-gcc11-build == *xpu* ]]
2025-09-07T07:47:05.5605088Z + [[ linux-jammy-py3.9-gcc11-build != *-bazel-* ]]
2025-09-07T07:47:05.5605316Z + pip_install ninja==1.10.2
2025-09-07T07:47:05.5605550Z + pip_install_pkg='python3 -m pip install --progress-bar off'
2025-09-07T07:47:05.5605838Z + python3 -m pip install --progress-bar off ninja==1.10.2
2025-09-07T07:47:05.9433617Z Collecting ninja==1.10.2
2025-09-07T07:47:05.9760138Z   Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB)
2025-09-07T07:47:05.9926206Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB)
2025-09-07T07:47:06.6913025Z Installing collected packages: ninja
2025-09-07T07:47:06.6913319Z   Attempting uninstall: ninja
2025-09-07T07:47:06.6920424Z     Found existing installation: ninja 1.11.1.3
2025-09-07T07:47:06.6941718Z     Uninstalling ninja-1.11.1.3:
2025-09-07T07:47:06.7029593Z       Successfully uninstalled ninja-1.11.1.3
2025-09-07T07:47:06.7727013Z Successfully installed ninja-1.10.2
2025-09-07T07:47:06.8618633Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.9/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-09-07T07:47:06.8619633Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.9/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
2025-09-07T07:47:06.8620215Z + [[ linux-jammy-py3.9-gcc11-build == *aarch64* ]]
2025-09-07T07:47:06.8620511Z + [[ linux-jammy-py3.9-gcc11-build == *asan* ]]
2025-09-07T07:47:06.8620751Z + [[ linux-jammy-py3.9-gcc11-build == *-debug* ]]
2025-09-07T07:47:06.8620986Z + [[ linux-jammy-py3.9-gcc11-build != *-bazel-* ]]
2025-09-07T07:47:06.8621337Z + echo 'We are not in debug mode: linux-jammy-py3.9-gcc11-build. Expect the assertion to pass'
2025-09-07T07:47:06.8621757Z We are not in debug mode: linux-jammy-py3.9-gcc11-build. Expect the assertion to pass
2025-09-07T07:47:06.8622393Z + cd test
2025-09-07T07:47:06.8623076Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)'
2025-09-07T07:47:07.1437067Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:47:07.1437965Z   import pynvml  # type: ignore[import]
2025-09-07T07:47:07.9680961Z + [[ inductor_torchbench_perf_cpu_x86_zen == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]]
2025-09-07T07:47:07.9681340Z + [[ inductor_torchbench_perf_cpu_x86_zen == \n\o\g\p\u\_\A\V\X\5\1\2 ]]
2025-09-07T07:47:07.9681697Z + [[ inductor_torchbench_perf_cpu_x86_zen == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]]
2025-09-07T07:47:07.9683580Z + DYNAMO_BENCHMARK_FLAGS=()
2025-09-07T07:47:07.9684434Z + [[ inductor_torchbench_perf_cpu_x86_zen == *pr_time_benchmarks* ]]
2025-09-07T07:47:07.9684791Z + [[ inductor_torchbench_perf_cpu_x86_zen == *dynamo_eager* ]]
2025-09-07T07:47:07.9685086Z + [[ inductor_torchbench_perf_cpu_x86_zen == *aot_eager* ]]
2025-09-07T07:47:07.9685854Z + [[ inductor_torchbench_perf_cpu_x86_zen == *aot_inductor* ]]
2025-09-07T07:47:07.9686193Z + [[ inductor_torchbench_perf_cpu_x86_zen == *max_autotune_inductor* ]]
2025-09-07T07:47:07.9686485Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor* ]]
2025-09-07T07:47:07.9686739Z + [[ inductor_torchbench_perf_cpu_x86_zen != *perf* ]]
2025-09-07T07:47:07.9687005Z + [[ inductor_torchbench_perf_cpu_x86_zen == *dynamic* ]]
2025-09-07T07:47:07.9687255Z + [[ inductor_torchbench_perf_cpu_x86_zen == *cpu* ]]
2025-09-07T07:47:07.9687496Z + DYNAMO_BENCHMARK_FLAGS+=(--device cpu)
2025-09-07T07:47:07.9808937Z + [[ linux-jammy-py3.9-gcc11-build == *libtorch* ]]
2025-09-07T07:47:07.9809202Z + [[ linux-jammy-py3.9-gcc11-build == *-bazel-* ]]
2025-09-07T07:47:07.9812488Z + cd test
2025-09-07T07:47:07.9813259Z + python -c 'import torch; print(torch.__config__.show())'
2025-09-07T07:47:08.2538263Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:47:08.2539289Z   import pynvml  # type: ignore[import]
2025-09-07T07:47:08.8865949Z PyTorch built with:
2025-09-07T07:47:08.8866178Z   - GCC 11.4
2025-09-07T07:47:08.8868015Z   - C++ Version: 201703
2025-09-07T07:47:08.8868426Z   - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications
2025-09-07T07:47:08.8868868Z   - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d)
2025-09-07T07:47:08.8869150Z   - OpenMP 201511 (a.k.a. OpenMP 4.5)
2025-09-07T07:47:08.8869375Z   - LAPACK is enabled (usually provided by MKL)
2025-09-07T07:47:08.8869579Z   - NNPACK is enabled
2025-09-07T07:47:08.8869754Z   - CPU capability usage: AVX512
2025-09-07T07:47:08.8872546Z   - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=93fb23d6fae7c4e82c4239a1033e522088742634, CXX_COMPILER=/opt/cache/bin/c++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -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=range-loop-construct -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, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.9.0, USE_CUDA=OFF, USE_CUDNN=OFF, USE_CUSPARSELT=OFF, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 
2025-09-07T07:47:08.8875300Z 
2025-09-07T07:47:09.0736568Z + cd test
2025-09-07T07:47:09.0736862Z + python -c 'import torch; print(torch.__config__.parallel_info())'
2025-09-07T07:47:09.3456642Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:47:09.3457507Z   import pynvml  # type: ignore[import]
2025-09-07T07:47:09.9801363Z ATen/Parallel:
2025-09-07T07:47:09.9801624Z 	at::get_num_threads() : 96
2025-09-07T07:47:09.9801839Z 	at::get_num_interop_threads() : 96
2025-09-07T07:47:09.9802053Z OpenMP 201511 (a.k.a. OpenMP 4.5)
2025-09-07T07:47:09.9802254Z 	omp_get_max_threads() : 96
2025-09-07T07:47:09.9802609Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications
2025-09-07T07:47:09.9803420Z 	mkl_get_max_threads() : 96
2025-09-07T07:47:09.9803677Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d)
2025-09-07T07:47:09.9803960Z std::thread::hardware_concurrency() : 96
2025-09-07T07:47:09.9804168Z Environment variables:
2025-09-07T07:47:09.9804348Z 	OMP_NUM_THREADS : [not set]
2025-09-07T07:47:09.9804546Z 	MKL_NUM_THREADS : [not set]
2025-09-07T07:47:09.9804734Z ATen parallel backend: OpenMP
2025-09-07T07:47:09.9804850Z 
2025-09-07T07:47:10.1595808Z + [[ inductor_torchbench_perf_cpu_x86_zen == *numpy_2* ]]
2025-09-07T07:47:10.1596106Z + [[ linux-jammy-py3.9-gcc11-build == *aarch64* ]]
2025-09-07T07:47:10.1596393Z + [[ inductor_torchbench_perf_cpu_x86_zen == *backward* ]]
2025-09-07T07:47:10.1596655Z + [[ inductor_torchbench_perf_cpu_x86_zen == *xla* ]]
2025-09-07T07:47:10.1596906Z + [[ inductor_torchbench_perf_cpu_x86_zen == *vllm* ]]
2025-09-07T07:47:10.1597173Z + [[ inductor_torchbench_perf_cpu_x86_zen == *executorch* ]]
2025-09-07T07:47:10.1597486Z + [[ inductor_torchbench_perf_cpu_x86_zen == \j\i\t\_\l\e\g\a\c\y ]]
2025-09-07T07:47:10.1597768Z + [[ linux-jammy-py3.9-gcc11-build == *libtorch* ]]
2025-09-07T07:47:10.1598029Z + [[ inductor_torchbench_perf_cpu_x86_zen == distributed ]]
2025-09-07T07:47:10.1598323Z + [[ inductor_torchbench_perf_cpu_x86_zen == *operator_benchmark* ]]
2025-09-07T07:47:10.1599149Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor_distributed* ]]
2025-09-07T07:47:10.1599491Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor-halide* ]]
2025-09-07T07:47:10.1599802Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor-triton-cpu* ]]
2025-09-07T07:47:10.1600134Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor-micro-benchmark* ]]
2025-09-07T07:47:10.1600450Z + [[ inductor_torchbench_perf_cpu_x86_zen == *huggingface* ]]
2025-09-07T07:47:10.1600710Z + [[ inductor_torchbench_perf_cpu_x86_zen == *timm* ]]
2025-09-07T07:47:10.1600967Z + [[ inductor_torchbench_perf_cpu_x86_zen == cachebench ]]
2025-09-07T07:47:10.1601249Z + [[ inductor_torchbench_perf_cpu_x86_zen == verify_cachebench ]]
2025-09-07T07:47:10.1601530Z + [[ inductor_torchbench_perf_cpu_x86_zen == *torchbench* ]]
2025-09-07T07:47:10.1601751Z + install_torchaudio
2025-09-07T07:47:10.1601921Z + local commit
2025-09-07T07:47:10.1602076Z ++ get_pinned_commit audio
2025-09-07T07:47:10.1602262Z ++ cat .github/ci_commit_pins/audio.txt
2025-09-07T07:47:10.2061193Z + commit=2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:10.2061671Z + pip_build_and_install git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8 dist/audio
2025-09-07T07:47:10.2062210Z + local build_target=git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:10.2062554Z + local wheel_dir=dist/audio
2025-09-07T07:47:10.2062728Z + local found_whl=0
2025-09-07T07:47:10.2062888Z + for file in "${wheel_dir}"/*.whl
2025-09-07T07:47:10.2063087Z + [[ -f dist/audio/*.whl ]]
2025-09-07T07:47:10.2063261Z + '[' 0 == 0 ']'
2025-09-07T07:47:10.2063741Z + python3 -m pip wheel --no-build-isolation --no-deps --no-use-pep517 -w dist/audio git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:10.5007588Z Collecting git+https://github.com/pytorch/audio.git@2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:10.5010559Z   Cloning https://github.com/pytorch/audio.git (to revision 2e300559e4e123928a22187b8f59a5b56f57ddc8) to /tmp/pip-req-build-r8fh4r0b
2025-09-07T07:47:10.7146951Z   Running command git clone --filter=blob:none --quiet https://github.com/pytorch/audio.git /tmp/pip-req-build-r8fh4r0b
2025-09-07T07:47:13.0426197Z   Running command git rev-parse -q --verify 'sha^2e300559e4e123928a22187b8f59a5b56f57ddc8'
2025-09-07T07:47:13.0469713Z   Running command git fetch -q https://github.com/pytorch/audio.git 2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:13.1603581Z   Running command git checkout -q 2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:13.2913750Z   Resolved https://github.com/pytorch/audio.git to commit 2e300559e4e123928a22187b8f59a5b56f57ddc8
2025-09-07T07:47:13.2914206Z   Running command git submodule update --init --recursive -q
2025-09-07T07:47:14.6805946Z   Preparing metadata (setup.py) ... [?25l- \ done
2025-09-07T07:47:14.6844184Z [?25hBuilding wheels for collected packages: torchaudio
2025-09-07T07:47:14.6954068Z   DEPRECATION: Building 'torchaudio' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'torchaudio'. Discussion can be found at https://github.com/pypa/pip/issues/6334
2025-09-07T07:47:36.6467323Z   Building wheel for torchaudio (setup.py) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | done
2025-09-07T07:47:36.6481138Z [?25h  Created wheel for torchaudio: filename=torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl size=491190 sha256=bc7d99bf7c3425fe29660e4aafb3d35e943ce0f70e006a6ac1bdfb4f970fa90e
2025-09-07T07:47:36.6482456Z   Stored in directory: /var/lib/jenkins/.cache/pip/wheels/18/53/66/85c241150a0c0641633cdbd6ae534ee172017679f2ef448df1
2025-09-07T07:47:36.6514213Z Successfully built torchaudio
2025-09-07T07:47:36.7651413Z + for file in "${wheel_dir}"/*.whl
2025-09-07T07:47:36.7651792Z + pip_install_whl dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl
2025-09-07T07:47:36.7652193Z + args=('dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl')
2025-09-07T07:47:36.7652468Z + local args
2025-09-07T07:47:36.7652724Z + [[ dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl == *\ * ]]
2025-09-07T07:47:36.7653029Z + for path in "${args[@]}"
2025-09-07T07:47:36.7653320Z + echo 'Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl'
2025-09-07T07:47:36.7653754Z Installing dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl
2025-09-07T07:47:36.7654213Z + python3 -mpip install --no-index --no-deps dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl
2025-09-07T07:47:37.0678694Z Processing ./dist/audio/torchaudio-2.8.0a0+2e30055-cp39-cp39-linux_x86_64.whl
2025-09-07T07:47:37.0728651Z Installing collected packages: torchaudio
2025-09-07T07:47:37.2408898Z Successfully installed torchaudio-2.8.0a0+2e30055
2025-09-07T07:47:37.2720791Z + install_torchvision
2025-09-07T07:47:37.2720982Z + local orig_preload
2025-09-07T07:47:37.2721140Z + local commit
2025-09-07T07:47:37.2725958Z ++ get_pinned_commit vision
2025-09-07T07:47:37.2726217Z ++ cat .github/ci_commit_pins/vision.txt
2025-09-07T07:47:37.2740695Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:37.2740914Z + orig_preload=
2025-09-07T07:47:37.2741082Z + '[' -n '' ']'
2025-09-07T07:47:37.2741271Z + [[ linux-jammy-py3.9-gcc11-build == *cuda* ]]
2025-09-07T07:47:37.2741749Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision
2025-09-07T07:47:37.2742307Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:37.2742663Z + local wheel_dir=dist/vision
2025-09-07T07:47:37.2742857Z + local found_whl=0
2025-09-07T07:47:37.2743026Z + for file in "${wheel_dir}"/*.whl
2025-09-07T07:47:37.2743226Z + [[ -f dist/vision/*.whl ]]
2025-09-07T07:47:37.2743392Z + '[' 0 == 0 ']'
2025-09-07T07:47:37.2743854Z + python3 -m pip wheel --no-build-isolation --no-deps --no-use-pep517 -w dist/vision git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:37.5692874Z Collecting git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:37.5697768Z   Cloning https://github.com/pytorch/vision.git (to revision 966da7e46f65d6d49df3e31214470a4fe5cc8e66) to /tmp/pip-req-build-sdv1tcpj
2025-09-07T07:47:37.5748257Z   Running command git clone --filter=blob:none --quiet https://github.com/pytorch/vision.git /tmp/pip-req-build-sdv1tcpj
2025-09-07T07:47:38.9556080Z   Running command git rev-parse -q --verify 'sha^966da7e46f65d6d49df3e31214470a4fe5cc8e66'
2025-09-07T07:47:38.9601306Z   Running command git fetch -q https://github.com/pytorch/vision.git 966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:39.0823969Z   Running command git checkout -q 966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:39.3690871Z   Resolved https://github.com/pytorch/vision.git to commit 966da7e46f65d6d49df3e31214470a4fe5cc8e66
2025-09-07T07:47:40.8733801Z   Preparing metadata (setup.py) ... [?25l- \ | / done
2025-09-07T07:47:40.8775319Z [?25hBuilding wheels for collected packages: torchvision
2025-09-07T07:47:40.8885253Z   DEPRECATION: Building 'torchvision' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'torchvision'. Discussion can be found at https://github.com/pypa/pip/issues/6334
2025-09-07T07:48:09.5286764Z   Building wheel for torchvision (setup.py) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / done
2025-09-07T07:48:09.5310380Z [?25h  Created wheel for torchvision: filename=torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl size=1301745 sha256=2cd2521d705cc576f59a91cc8b83e319148b9df3b9f7daacc5c303dd13c19942
2025-09-07T07:48:09.5311173Z   Stored in directory: /var/lib/jenkins/.cache/pip/wheels/33/6d/2f/9f3e65c401a351a98a00d9d72c4434fdbd3e10256b2d832157
2025-09-07T07:48:09.5350132Z Successfully built torchvision
2025-09-07T07:48:09.6249741Z + for file in "${wheel_dir}"/*.whl
2025-09-07T07:48:09.6250193Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl
2025-09-07T07:48:09.6250612Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl')
2025-09-07T07:48:09.6250897Z + local args
2025-09-07T07:48:09.6251157Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl == *\ * ]]
2025-09-07T07:48:09.6251478Z + for path in "${args[@]}"
2025-09-07T07:48:09.6251782Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl'
2025-09-07T07:48:09.6252194Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl
2025-09-07T07:48:09.6252667Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl
2025-09-07T07:48:09.9272240Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp39-cp39-linux_x86_64.whl
2025-09-07T07:48:09.9357855Z Installing collected packages: torchvision
2025-09-07T07:48:10.3073489Z Successfully installed torchvision-0.22.0a0+966da7e
2025-09-07T07:48:10.3410034Z + '[' -n '' ']'
2025-09-07T07:48:10.3410217Z + id=0
2025-09-07T07:48:10.3410404Z + pip_install opencv-python==4.8.0.74
2025-09-07T07:48:10.3410664Z + pip_install_pkg='python3 -m pip install --progress-bar off'
2025-09-07T07:48:10.3410983Z + python3 -m pip install --progress-bar off opencv-python==4.8.0.74
2025-09-07T07:48:10.7089103Z Collecting opencv-python==4.8.0.74
2025-09-07T07:48:10.7363793Z   Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (19 kB)
2025-09-07T07:48:10.7434246Z Requirement already satisfied: numpy>=1.17.0 in /opt/conda/envs/py_3.9/lib/python3.9/site-packages (from opencv-python==4.8.0.74) (1.22.4)
2025-09-07T07:48:10.7546429Z Downloading opencv_python-4.8.0.74-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.7 MB)
2025-09-07T07:48:11.8377551Z Installing collected packages: opencv-python
2025-09-07T07:48:11.8377861Z   Attempting uninstall: opencv-python
2025-09-07T07:48:11.8387987Z     Found existing installation: opencv-python 4.11.0.86
2025-09-07T07:48:11.8468384Z     Uninstalling opencv-python-4.11.0.86:
2025-09-07T07:48:11.9666807Z       Successfully uninstalled opencv-python-4.11.0.86
2025-09-07T07:48:12.6876120Z Successfully installed opencv-python-4.8.0.74
2025-09-07T07:48:12.7758922Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor_torchbench_smoketest_perf* ]]
2025-09-07T07:48:12.7759359Z + [[ inductor_torchbench_perf_cpu_x86_zen == *inductor_torchbench_cpu_smoketest_perf* ]]
2025-09-07T07:48:12.7759727Z + [[ inductor_torchbench_perf_cpu_x86_zen == *torchbench_gcp_smoketest* ]]
2025-09-07T07:48:12.7760032Z + [[ inductor_torchbench_perf_cpu_x86_zen != *cpu* ]]
2025-09-07T07:48:12.7760264Z + PYTHONPATH=/torchbench
2025-09-07T07:48:12.7760450Z + test_dynamo_benchmark torchbench 0
2025-09-07T07:48:12.7764705Z ++ pwd
2025-09-07T07:48:12.7767279Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports
2025-09-07T07:48:12.7767558Z + local suite=torchbench
2025-09-07T07:48:12.7767722Z + shift
2025-09-07T07:48:12.7767855Z + local shard_id=0
2025-09-07T07:48:12.7768009Z + shift
2025-09-07T07:48:12.7768210Z + [[ inductor_torchbench_perf_cpu_x86_zen == *perf_compare* ]]
2025-09-07T07:48:12.7768487Z + [[ inductor_torchbench_perf_cpu_x86_zen == *perf* ]]
2025-09-07T07:48:12.7770244Z + [[ inductor_torchbench_perf_cpu_x86_zen == *b200* ]]
2025-09-07T07:48:12.7770538Z + test_single_dynamo_benchmark dashboard torchbench 0
2025-09-07T07:48:12.7772844Z ++ pwd
2025-09-07T07:48:12.7775608Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports
2025-09-07T07:48:12.7775915Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports
2025-09-07T07:48:12.7797018Z + local name=dashboard
2025-09-07T07:48:12.7797177Z + shift
2025-09-07T07:48:12.7797315Z + local suite=torchbench
2025-09-07T07:48:12.7797476Z + shift
2025-09-07T07:48:12.7797615Z + local shard_id=0
2025-09-07T07:48:12.7797769Z + shift
2025-09-07T07:48:12.7797909Z + partition_flags=()
2025-09-07T07:48:12.7798090Z + local partition_flags
2025-09-07T07:48:12.7798246Z + [[ -n 4 ]]
2025-09-07T07:48:12.7798388Z + [[ -n 0 ]]
2025-09-07T07:48:12.7798641Z + partition_flags=(--total-partitions "$NUM_TEST_SHARDS" --partition-id "$shard_id")
2025-09-07T07:48:12.7799178Z + [[ inductor_torchbench_perf_cpu_x86_zen == *perf_compare* ]]
2025-09-07T07:48:12.7799448Z + [[ inductor_torchbench_perf_cpu_x86_zen == *perf* ]]
2025-09-07T07:48:12.7799789Z + test_perf_for_dashboard torchbench --device cpu --total-partitions 4 --partition-id 0
2025-09-07T07:48:12.7802702Z ++ pwd
2025-09-07T07:48:12.7805639Z + TEST_REPORTS_DIR=/var/lib/jenkins/workspace/test/test-reports
2025-09-07T07:48:12.7805948Z + mkdir -p /var/lib/jenkins/workspace/test/test-reports
2025-09-07T07:48:12.7825051Z + local suite=torchbench
2025-09-07T07:48:12.7825226Z + shift
2025-09-07T07:48:12.7825367Z + local backend=inductor
2025-09-07T07:48:12.7825569Z + modes=()
2025-09-07T07:48:12.7825707Z + local modes
2025-09-07T07:48:12.7826131Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *training-true* ]]
2025-09-07T07:48:12.7826855Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *inference-true* ]]
2025-09-07T07:48:12.7827319Z + modes+=(inference)
2025-09-07T07:48:12.7827500Z + targets=('accuracy' 'performance')
2025-09-07T07:48:12.7827693Z + local targets
2025-09-07T07:48:12.7827848Z + local device=cuda
2025-09-07T07:48:12.7828049Z + [[ inductor_torchbench_perf_cpu_x86_zen == *cpu* ]]
2025-09-07T07:48:12.7828315Z + [[ inductor_torchbench_perf_cpu_x86_zen == *cpu_x86_zen* ]]
2025-09-07T07:48:12.7828543Z + device=cpu_x86_zen
2025-09-07T07:48:12.7828713Z + test_inductor_set_cpu_affinity
2025-09-07T07:48:12.7830497Z ++ find /usr/lib -name libjemalloc.so.2
2025-09-07T07:48:12.8185745Z + JEMALLOC_LIB=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2
2025-09-07T07:48:12.8186065Z + export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2:
2025-09-07T07:48:12.8186663Z + LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2:
2025-09-07T07:48:12.8187072Z + export MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1
2025-09-07T07:48:12.8187611Z + MALLOC_CONF=oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1
2025-09-07T07:48:12.8188015Z + [[ inductor_torchbench_perf_cpu_x86_zen != *aarch64* ]]
2025-09-07T07:48:12.8194362Z +++ which python
2025-09-07T07:48:12.8220671Z ++ dirname /opt/conda/envs/py_3.9/bin/python
2025-09-07T07:48:12.8255210Z + IOMP_LIB=/opt/conda/envs/py_3.9/bin/../lib/libiomp5.so
2025-09-07T07:48:12.8255942Z + export LD_PRELOAD=/opt/conda/envs/py_3.9/bin/../lib/libiomp5.so:/usr/lib/x86_64-linux-gnu/libjemalloc.so.2:
2025-09-07T07:48:12.8256508Z + LD_PRELOAD=/opt/conda/envs/py_3.9/bin/../lib/libiomp5.so:/usr/lib/x86_64-linux-gnu/libjemalloc.so.2:
2025-09-07T07:48:12.8256906Z + export KMP_AFFINITY=granularity=fine,compact,1,0
2025-09-07T07:48:12.8257151Z + KMP_AFFINITY=granularity=fine,compact,1,0
2025-09-07T07:48:12.8257389Z + export KMP_BLOCKTIME=1
2025-09-07T07:48:12.8257562Z + KMP_BLOCKTIME=1
2025-09-07T07:48:12.8260122Z ++ nproc
2025-09-07T07:48:12.8293358Z + cpus=96
2025-09-07T07:48:12.8301398Z ++ lscpu
2025-09-07T07:48:12.8302544Z ++ grep 'Thread(s) per core:'
2025-09-07T07:48:12.8303946Z ++ awk '{print $4}'
2025-09-07T07:48:12.8914053Z + thread_per_core=1
2025-09-07T07:48:12.8914244Z + cores=96
2025-09-07T07:48:12.8914441Z + [[ inductor_torchbench_perf_cpu_x86_zen == *aarch64* ]]
2025-09-07T07:48:12.8914683Z + export OMP_NUM_THREADS=96
2025-09-07T07:48:12.8914862Z + OMP_NUM_THREADS=96
2025-09-07T07:48:12.8918833Z ++ python -c 'import os; print(min(os.sched_getaffinity(0)))'
2025-09-07T07:48:12.9176991Z + start_cpu=0
2025-09-07T07:48:12.9181489Z ++ python -c 'import os; print(max(os.sched_getaffinity(0)))'
2025-09-07T07:48:12.9444513Z + end_cpu=94
2025-09-07T07:48:12.9444720Z + export 'TASKSET=taskset -c 0-94'
2025-09-07T07:48:12.9444929Z + TASKSET='taskset -c 0-94'
2025-09-07T07:48:12.9445132Z + for mode in "${modes[@]}"
2025-09-07T07:48:12.9445317Z + [[ inference == \i\n\f\e\r\e\n\c\e ]]
2025-09-07T07:48:12.9445526Z + [[ cpu_x86_zen == \c\p\u\_\x\8\6 ]]
2025-09-07T07:48:12.9445719Z + dtype=bfloat16
2025-09-07T07:48:12.9445880Z + for target in "${targets[@]}"
2025-09-07T07:48:12.9446066Z + target_flag=('--accuracy')
2025-09-07T07:48:12.9446250Z + local target_flag
2025-09-07T07:48:12.9446423Z + [[ accuracy == \p\e\r\f\o\r\m\a\n\c\e ]]
2025-09-07T07:48:12.9446617Z + [[ accuracy == \a\c\c\u\r\a\c\y ]]
2025-09-07T07:48:12.9446828Z + target_flag+=(--no-translation-validation)
2025-09-07T07:48:12.9447292Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *freezing-true* ]]
2025-09-07T07:48:12.9447976Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *default-true* ]]
2025-09-07T07:48:12.9449169Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv
2025-09-07T07:48:13.3441123Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:48:13.3442024Z   import pynvml  # type: ignore[import]
2025-09-07T07:48:15.8376555Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:48:15.8377433Z   import pynvml  # type: ignore[import]
2025-09-07T07:48:17.8439563Z 
2025-09-07T07:48:19.7505589Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:48:19.7505907Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:48:19.7719314Z cpu  eval  BERT_pytorch                       
2025-09-07T07:48:20.2566246Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:48:20.5671574Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:48:20.8192058Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:48:47.8804400Z pass
2025-09-07T07:48:47.8804818Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:48:50.0798592Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:48:50.0799638Z   import pynvml  # type: ignore[import]
2025-09-07T07:48:52.0876829Z 
2025-09-07T07:48:54.4669448Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:48:54.4669775Z loading model: 0it [00:02, ?it/s]
2025-09-07T07:48:54.4766374Z cpu  eval  Background_Matting                 
2025-09-07T07:48:54.5850505Z pass_due_to_skip
2025-09-07T07:48:54.5850871Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:48:55.9254655Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:48:55.9255556Z   import pynvml  # type: ignore[import]
2025-09-07T07:48:57.9317158Z 
2025-09-07T07:48:59.9303311Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:48:59.9303675Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:48:59.9343352Z cpu  eval  LearningToPaint                    
2025-09-07T07:49:00.1790559Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:49:00.2209222Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:49:00.2560857Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:49:18.1945710Z pass
2025-09-07T07:49:18.1948270Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:49:20.4475646Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:49:20.4476566Z   import pynvml  # type: ignore[import]
2025-09-07T07:49:22.4591311Z 
2025-09-07T07:49:23.4167826Z 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
2025-09-07T07:49:23.4287781Z 
2025-09-07T07:49:23.4287867Z 
2025-09-07T07:49:23.5290391Z   0% 0.00/528M [00:00<?, ?B/s]
2025-09-07T07:49:23.5290585Z 
2025-09-07T07:49:23.6291577Z  10% 51.4M/528M [00:00<00:00, 538MB/s]
2025-09-07T07:49:23.6291767Z 
2025-09-07T07:49:23.7291842Z  20% 106M/528M [00:00<00:00, 558MB/s] 
2025-09-07T07:49:23.7292021Z 
2025-09-07T07:49:23.8294069Z  30% 160M/528M [00:00<00:00, 563MB/s]
2025-09-07T07:49:23.8294258Z 
2025-09-07T07:49:23.9295444Z  41% 215M/528M [00:00<00:00, 565MB/s]
2025-09-07T07:49:23.9295613Z 
2025-09-07T07:49:24.0296665Z  51% 269M/528M [00:00<00:00, 567MB/s]
2025-09-07T07:49:24.0296850Z 
2025-09-07T07:49:24.1296784Z  61% 323M/528M [00:00<00:00, 567MB/s]
2025-09-07T07:49:24.1297526Z 
2025-09-07T07:49:24.2297013Z  72% 378M/528M [00:00<00:00, 568MB/s]
2025-09-07T07:49:24.2297189Z 
2025-09-07T07:49:24.3298151Z  82% 432M/528M [00:00<00:00, 568MB/s]
2025-09-07T07:49:24.3298321Z 
2025-09-07T07:49:24.4065874Z  92% 486M/528M [00:00<00:00, 569MB/s]
2025-09-07T07:49:24.4066101Z 100% 528M/528M [00:00<00:00, 566MB/s]
2025-09-07T07:49:24.8835633Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T07:49:25.2794414Z 
2025-09-07T07:49:25.2794867Z loading model: 0it [00:02, ?it/s]
2025-09-07T07:49:25.2795263Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T07:49:25.2795617Z cpu  eval  Super_SloMo                        
2025-09-07T07:49:45.4402947Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:49:45.4403474Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T07:49:46.0506242Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:49:46.7287413Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:50:50.4948659Z pass
2025-09-07T07:50:50.4951658Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:50:53.4314713Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:50:53.4315602Z   import pynvml  # type: ignore[import]
2025-09-07T07:50:55.4400459Z 
2025-09-07T07:50:55.8571055Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/alexnet-owt-7be5be79.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/alexnet-owt-7be5be79.pth
2025-09-07T07:50:55.8683811Z 
2025-09-07T07:50:55.8683830Z 
2025-09-07T07:50:55.9686534Z   0% 0.00/233M [00:00<?, ?B/s]
2025-09-07T07:50:55.9686705Z 
2025-09-07T07:50:56.0687820Z  21% 49.6M/233M [00:00<00:00, 520MB/s]
2025-09-07T07:50:56.0688011Z 
2025-09-07T07:50:56.1687796Z  45% 105M/233M [00:00<00:00, 555MB/s] 
2025-09-07T07:50:56.1687980Z 
2025-09-07T07:50:56.2689309Z  69% 160M/233M [00:00<00:00, 566MB/s]
2025-09-07T07:50:56.2689478Z 
2025-09-07T07:50:56.3009962Z  93% 216M/233M [00:00<00:00, 572MB/s]
2025-09-07T07:50:56.3010226Z 100% 233M/233M [00:00<00:00, 565MB/s]
2025-09-07T07:50:56.5830571Z 
2025-09-07T07:50:56.5832677Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:50:56.5867735Z cpu  eval  alexnet                            
2025-09-07T07:50:56.7411001Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:50:56.7596901Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:50:56.7720087Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:09.0804763Z pass
2025-09-07T07:51:09.0809041Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:11.0963486Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:51:11.0964358Z   import pynvml  # type: ignore[import]
2025-09-07T07:51:13.1022692Z 
2025-09-07T07:51:14.6148820Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:51:14.6150030Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:51:14.6159193Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T07:51:14.7736449Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:14.8258627Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:14.8788422Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:22.8380041Z pass
2025-09-07T07:51:22.8380511Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:24.9009688Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:51:24.9010580Z   import pynvml  # type: ignore[import]
2025-09-07T07:51:26.9039828Z 
2025-09-07T07:51:28.4013569Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:51:28.4013905Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:51:28.4018582Z cpu  eval  basic_gnn_gcn                      
2025-09-07T07:51:28.4818466Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:28.5442004Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:28.6013697Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:37.7097745Z pass
2025-09-07T07:51:37.7098159Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:39.7057095Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:51:39.7057983Z   import pynvml  # type: ignore[import]
2025-09-07T07:51:41.7166806Z 
2025-09-07T07:51:43.1983070Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:51:43.1983391Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:51:43.1990350Z cpu  eval  basic_gnn_gin                      
2025-09-07T07:51:43.2857930Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:43.3389940Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:43.3869357Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:51.3996943Z pass
2025-09-07T07:51:51.3997369Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:53.3637933Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:51:53.3638898Z   import pynvml  # type: ignore[import]
2025-09-07T07:51:55.3760806Z 
2025-09-07T07:51:56.8641674Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:51:56.8641971Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:51:56.8648100Z cpu  eval  basic_gnn_sage                     
2025-09-07T07:51:56.9364119Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:56.9868586Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:51:57.0339931Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:03.5059712Z pass
2025-09-07T07:52:03.5060123Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:05.5188863Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:52:05.5190203Z   import pynvml  # type: ignore[import]
2025-09-07T07:52:07.5237838Z 
2025-09-07T07:52:07.7708612Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:52:07.7708905Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:52:07.7718428Z cpu  eval  dcgan                              
2025-09-07T07:52:07.8232524Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:07.8351828Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:07.8425109Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:17.8844962Z pass
2025-09-07T07:52:17.8847739Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:19.8208423Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:52:19.8209300Z   import pynvml  # type: ignore[import]
2025-09-07T07:52:21.8287570Z 
2025-09-07T07:52:23.4477556Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:52:23.4477855Z loading model: 0it [00:01, ?it/s]
2025-09-07T07:52:23.4681160Z cpu  eval  demucs                             
2025-09-07T07:52:28.1664042Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:28.3293876Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:28.4774596Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:53.4268767Z pass
2025-09-07T07:52:53.4272222Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:55.6134583Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:52:55.6135701Z   import pynvml  # type: ignore[import]
2025-09-07T07:52:57.6245188Z 
2025-09-07T07:52:57.9024615Z loading model: 0it [00:00, ?it/s]Downloading: "https://download.pytorch.org/models/densenet121-a639ec97.pth" to /var/lib/jenkins/.cache/torch/hub/checkpoints/densenet121-a639ec97.pth
2025-09-07T07:52:57.9143542Z 
2025-09-07T07:52:57.9143545Z 
2025-09-07T07:52:57.9753152Z   0% 0.00/30.8M [00:00<?, ?B/s]
2025-09-07T07:52:57.9753407Z 100% 30.8M/30.8M [00:00<00:00, 533MB/s]
2025-09-07T07:52:58.4534066Z 
2025-09-07T07:52:58.4534340Z loading model: 0it [00:00, ?it/s]
2025-09-07T07:52:58.4698065Z cpu  eval  densenet121                        
2025-09-07T07:52:59.6794453Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:52:59.9398375Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:53:00.1940182Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:53:59.7942363Z pass
2025-09-07T07:53:59.7947682Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T07:54:02.3562701Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:54:02.3563574Z   import pynvml  # type: ignore[import]
2025-09-07T07:54:04.3801272Z 
2025-09-07T07:54:04.6032362Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T07:54:04.6032758Z   what():  std::bad_array_new_length
2025-09-07T07:55:47.6520795Z Run failed with return code:  -6
2025-09-07T07:55:47.6521067Z Output:  None
2025-09-07T07:55:47.6521221Z Error:  None
2025-09-07T07:55:48.0613484Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:55:48.0614358Z   import pynvml  # type: ignore[import]
2025-09-07T07:55:50.0732717Z 
2025-09-07T07:55:50.2916599Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T07:55:50.2917007Z   what():  std::bad_array_new_length
2025-09-07T07:57:33.5566966Z Run failed with return code:  -6
2025-09-07T07:57:33.5567219Z Output:  None
2025-09-07T07:57:33.5567386Z Error:  None
2025-09-07T07:57:33.9682117Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:57:33.9683003Z   import pynvml  # type: ignore[import]
2025-09-07T07:57:35.9802232Z 
2025-09-07T07:57:36.1982637Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T07:57:36.1983030Z   what():  std::bad_array_new_length
2025-09-07T07:59:19.3611290Z Run failed with return code:  -6
2025-09-07T07:59:19.3611581Z Output:  None
2025-09-07T07:59:19.3611734Z Error:  None
2025-09-07T07:59:19.7681170Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T07:59:19.7682094Z   import pynvml  # type: ignore[import]
2025-09-07T07:59:21.7770592Z 
2025-09-07T07:59:21.9948171Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T07:59:21.9948638Z   what():  std::bad_array_new_length
2025-09-07T08:01:10.4703714Z Run failed with return code:  -6
2025-09-07T08:01:10.4703967Z Output:  None
2025-09-07T08:01:10.4704123Z Error:  None
2025-09-07T08:01:10.8807715Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:01:10.8808601Z   import pynvml  # type: ignore[import]
2025-09-07T08:01:12.8903023Z 
2025-09-07T08:01:13.1083966Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:01:13.1084372Z   what():  std::bad_array_new_length
2025-09-07T08:02:56.9237916Z Run failed with return code:  -6
2025-09-07T08:02:56.9238169Z Output:  None
2025-09-07T08:02:56.9238316Z Error:  None
2025-09-07T08:02:57.3357859Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:02:57.3358746Z   import pynvml  # type: ignore[import]
2025-09-07T08:02:59.3406373Z 
2025-09-07T08:02:59.5581551Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:02:59.5581952Z   what():  std::bad_array_new_length
2025-09-07T08:04:42.2786723Z Run failed with return code:  -6
2025-09-07T08:04:42.2786981Z Output:  None
2025-09-07T08:04:42.2787157Z Error:  None
2025-09-07T08:04:42.6928138Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:04:42.6929050Z   import pynvml  # type: ignore[import]
2025-09-07T08:04:44.7112382Z 
2025-09-07T08:04:44.9279466Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:04:44.9279871Z   what():  std::bad_array_new_length
2025-09-07T08:06:27.5858917Z Run failed with return code:  -6
2025-09-07T08:06:27.5859181Z Output:  None
2025-09-07T08:06:27.5859329Z Error:  None
2025-09-07T08:06:27.9942772Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:06:27.9943667Z   import pynvml  # type: ignore[import]
2025-09-07T08:06:30.0037406Z 
2025-09-07T08:06:30.2224120Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:06:30.2224530Z   what():  std::bad_array_new_length
2025-09-07T08:08:13.3378282Z Run failed with return code:  -6
2025-09-07T08:08:13.3378536Z Output:  None
2025-09-07T08:08:13.3378699Z Error:  None
2025-09-07T08:08:13.7459413Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:08:13.7460337Z   import pynvml  # type: ignore[import]
2025-09-07T08:08:15.7521766Z 
2025-09-07T08:08:15.9703049Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:08:15.9703450Z   what():  std::bad_array_new_length
2025-09-07T08:09:59.1422698Z Run failed with return code:  -6
2025-09-07T08:09:59.1422974Z Output:  None
2025-09-07T08:09:59.1423130Z Error:  None
2025-09-07T08:09:59.5514995Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:09:59.5515874Z   import pynvml  # type: ignore[import]
2025-09-07T08:10:01.5564611Z 
2025-09-07T08:10:01.7739628Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:10:01.7740032Z   what():  std::bad_array_new_length
2025-09-07T08:11:44.7464548Z Run failed with return code:  -6
2025-09-07T08:11:44.7464818Z Output:  None
2025-09-07T08:11:44.7464974Z Error:  None
2025-09-07T08:11:45.1584624Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:11:45.1585503Z   import pynvml  # type: ignore[import]
2025-09-07T08:11:47.1616652Z 
2025-09-07T08:11:47.3777608Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:11:47.3778003Z   what():  std::bad_array_new_length
2025-09-07T08:13:30.6533244Z Run failed with return code:  -6
2025-09-07T08:13:30.6533522Z Output:  None
2025-09-07T08:13:30.6533700Z Error:  None
2025-09-07T08:13:30.6567462Z accuracy            pass_rate=91.67%
2025-09-07T08:13:30.6572894Z calls_captured      gmean=0.00x mean=145.000x
2025-09-07T08:13:30.6575946Z unique_graphs       gmean=0.00x mean=1.500x
2025-09-07T08:13:30.6578227Z graph_breaks        gmean=0.00x mean=0.750x
2025-09-07T08:13:30.6580389Z unique_graph_breaks gmean=0.00x mean=0.167x
2025-09-07T08:13:30.6582496Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T08:13:30.6584499Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T08:13:30.6586670Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T08:13:30.6587409Z compilation_latency mean=20.349 seconds
2025-09-07T08:13:31.1818738Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *cudagraphs-true* ]]
2025-09-07T08:13:31.1819479Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *dynamic-true* ]]
2025-09-07T08:13:31.1820731Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --dynamic-shapes --dynamic-batch-only --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv
2025-09-07T08:13:31.5767641Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:13:31.5768536Z   import pynvml  # type: ignore[import]
2025-09-07T08:13:34.0153781Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:13:36.0225065Z   import pynvml  # type: ignore[import]
2025-09-07T08:13:36.0225282Z 
2025-09-07T08:13:37.9046787Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:13:37.9047200Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:13:37.9264668Z cpu  eval  BERT_pytorch                       
2025-09-07T08:13:38.4843259Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:13:38.7455345Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:13:38.9994122Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:13:48.9470979Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9471440Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9471794Z     return mod(*inputs)
2025-09-07T08:13:48.9472171Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9472598Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9472996Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 44, in forward
2025-09-07T08:13:48.9473393Z     mask = (x > 0).unsqueeze(1).repeat(1, x.size(1), 1).unsqueeze(1)
2025-09-07T08:13:48.9473566Z 
2025-09-07T08:13:48.9473681Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9474060Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9474421Z     return mod(*inputs)
2025-09-07T08:13:48.9474775Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9475155Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9475495Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward
2025-09-07T08:13:48.9475856Z     x = self.embedding(x, segment_info)
2025-09-07T08:13:48.9476235Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward
2025-09-07T08:13:48.9477108Z     x = self.token(sequence) + self.position(sequence) + self.segment(segment_label)
2025-09-07T08:13:48.9477327Z 
2025-09-07T08:13:48.9477438Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9477803Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9478150Z     return mod(*inputs)
2025-09-07T08:13:48.9478496Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9478872Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9479208Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9479552Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9479913Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9480297Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9480687Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9481094Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9481652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9482098Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9482532Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9482927Z     query, key, value = [
2025-09-07T08:13:48.9483325Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9483790Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9483966Z 
2025-09-07T08:13:48.9484070Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9484457Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9484785Z     return mod(*inputs)
2025-09-07T08:13:48.9485119Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9485500Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9485834Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9486222Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9486573Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9486965Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9487357Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9487774Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9488181Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9488575Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9488999Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9489389Z     query, key, value = [
2025-09-07T08:13:48.9489775Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9490214Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9490376Z 
2025-09-07T08:13:48.9490477Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9490851Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9491211Z     return mod(*inputs)
2025-09-07T08:13:48.9491807Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9492179Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9492516Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9492864Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9493231Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9493611Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9493993Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9494407Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9494803Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9495206Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9495635Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9496082Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9496588Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9497059Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9497280Z 
2025-09-07T08:13:48.9497388Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9497759Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9498080Z     return mod(*inputs)
2025-09-07T08:13:48.9498416Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9498933Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9499271Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9499629Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9499990Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9500372Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9500763Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9501172Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9501561Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9501956Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9502377Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9502820Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9503257Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9503715Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9503939Z 
2025-09-07T08:13:48.9504039Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9504407Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9504732Z     return mod(*inputs)
2025-09-07T08:13:48.9505074Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9505433Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9505802Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9506269Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9506629Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9507008Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9507398Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9507818Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9508215Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9508611Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9509028Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9509473Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9509904Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9510374Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9510592Z 
2025-09-07T08:13:48.9510702Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9511194Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9511534Z     return mod(*inputs)
2025-09-07T08:13:48.9511882Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9512262Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9512596Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9512947Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9513311Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9513698Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9514084Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9514491Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9514893Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9515285Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9515712Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9516101Z     query, key, value = [
2025-09-07T08:13:48.9516464Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9516903Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9517078Z 
2025-09-07T08:13:48.9517178Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9517561Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9517882Z     return mod(*inputs)
2025-09-07T08:13:48.9518226Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9518596Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9518924Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9519274Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9519617Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9519999Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9520390Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9520890Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9521281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9521681Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9522108Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9522558Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9522995Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9523399Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9523542Z 
2025-09-07T08:13:48.9523643Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9524013Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9524347Z     return mod(*inputs)
2025-09-07T08:13:48.9524690Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9525060Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9525478Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9525831Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9526187Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9526568Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9526945Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9527352Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9527746Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9528150Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9528564Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9529009Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9529441Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9529832Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9529972Z 
2025-09-07T08:13:48.9530077Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9530430Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9530752Z     return mod(*inputs)
2025-09-07T08:13:48.9531088Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9531466Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9531801Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9532143Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9532501Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9532882Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9533263Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9533667Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9534066Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9534457Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9534978Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9535432Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9535624Z 
2025-09-07T08:13:48.9535726Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9536093Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9536421Z     return mod(*inputs)
2025-09-07T08:13:48.9536758Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9537125Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9537453Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9537801Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9538162Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9538554Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9538931Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9539334Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9539807Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9540213Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9540636Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9541018Z     return self.output_linear(x)
2025-09-07T08:13:48.9541143Z 
2025-09-07T08:13:48.9541242Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9541598Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9541926Z     return mod(*inputs)
2025-09-07T08:13:48.9542258Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9542622Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9542954Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9543297Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9543645Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9544014Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9544396Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9544796Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9545210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9545708Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9545882Z 
2025-09-07T08:13:48.9545980Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9546333Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9546660Z     return mod(*inputs)
2025-09-07T08:13:48.9546995Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9547351Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9547680Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9548024Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9548374Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9548745Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9549195Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9549595Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9550010Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9550431Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9550597Z 
2025-09-07T08:13:48.9550702Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9551050Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9551370Z     return mod(*inputs)
2025-09-07T08:13:48.9551703Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9552070Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9552394Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9552738Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9553090Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9553462Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9553909Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9554312Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9554724Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9555152Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9555324Z 
2025-09-07T08:13:48.9555432Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9555791Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9556114Z     return mod(*inputs)
2025-09-07T08:13:48.9556450Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9556818Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9557153Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9557494Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9557861Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9558236Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9558621Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9559026Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9559415Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9559811Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9560229Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9560614Z     query, key, value = [
2025-09-07T08:13:48.9560975Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9561407Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9561578Z 
2025-09-07T08:13:48.9561678Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9562040Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9562363Z     return mod(*inputs)
2025-09-07T08:13:48.9562693Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9563157Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9563489Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9563836Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9564186Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9564565Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9564943Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9565345Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9565740Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9566125Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9566546Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9566926Z     query, key, value = [
2025-09-07T08:13:48.9567294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9569690Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9569873Z 
2025-09-07T08:13:48.9569974Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9570328Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9570648Z     return mod(*inputs)
2025-09-07T08:13:48.9570984Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9571344Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9571672Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9572019Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9572368Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9572739Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9573110Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9573512Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9573901Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9574291Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9574720Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9575165Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9575600Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9576060Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9576272Z 
2025-09-07T08:13:48.9576376Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9576737Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9577062Z     return mod(*inputs)
2025-09-07T08:13:48.9577398Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9577767Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9578098Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9578435Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9578794Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9579251Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9579632Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9580037Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9580428Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9580819Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9581254Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9581701Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9582126Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9582577Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9582795Z 
2025-09-07T08:13:48.9582892Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9583252Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9583578Z     return mod(*inputs)
2025-09-07T08:13:48.9583980Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9584356Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9584692Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9585040Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9585394Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9585830Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9586217Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9586634Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9587022Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9587409Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9587826Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9588261Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9588688Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9589142Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9589355Z 
2025-09-07T08:13:48.9589456Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9589814Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9590135Z     return mod(*inputs)
2025-09-07T08:13:48.9590467Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9590835Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9591160Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9591507Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9591870Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9592252Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9592641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9593142Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9593554Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9593964Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9594398Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9594784Z     query, key, value = [
2025-09-07T08:13:48.9595164Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9595603Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9595775Z 
2025-09-07T08:13:48.9595888Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9596258Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9596585Z     return mod(*inputs)
2025-09-07T08:13:48.9596939Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9597313Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9597652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9598070Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9598440Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9598984Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9599386Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9599796Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9600185Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9600592Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9601008Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9601461Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9601901Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9602290Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9602438Z 
2025-09-07T08:13:48.9602538Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9602900Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9603230Z     return mod(*inputs)
2025-09-07T08:13:48.9603561Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9603932Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9604276Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9604621Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9604980Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9605354Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9605737Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9606143Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9606537Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9606935Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9607343Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9607989Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9608422Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9608817Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9608958Z 
2025-09-07T08:13:48.9609061Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9609424Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9609749Z     return mod(*inputs)
2025-09-07T08:13:48.9610085Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9610456Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9610788Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9611131Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9611491Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9611869Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9612245Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9612752Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9613155Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9613557Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9613976Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9614420Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9614619Z 
2025-09-07T08:13:48.9614718Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9615084Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9615416Z     return mod(*inputs)
2025-09-07T08:13:48.9615753Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9616120Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9616451Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9616805Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9617160Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9617528Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9617907Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9618313Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9618703Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9619099Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9619510Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9619901Z     return self.output_linear(x)
2025-09-07T08:13:48.9620028Z 
2025-09-07T08:13:48.9620128Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9620484Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9620806Z     return mod(*inputs)
2025-09-07T08:13:48.9621135Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9621500Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9621925Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9622268Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9622610Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9622984Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9623369Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9623771Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9624180Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9624600Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9624776Z 
2025-09-07T08:13:48.9624876Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9625225Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9625589Z     return mod(*inputs)
2025-09-07T08:13:48.9625924Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9626283Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9626702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9627053Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9627407Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9627779Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9628159Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9628556Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9628977Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9629401Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9629575Z 
2025-09-07T08:13:48.9629674Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9630039Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9630360Z     return mod(*inputs)
2025-09-07T08:13:48.9630695Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9631056Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9631384Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9631726Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9632083Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9632462Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9632829Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9633226Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9633638Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9634055Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9634222Z 
2025-09-07T08:13:48.9634324Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9634671Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9634995Z     return mod(*inputs)
2025-09-07T08:13:48.9635325Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9635773Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9636105Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9636455Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9636811Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9637190Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9637568Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9637963Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9638128Z 
2025-09-07T08:13:48.9638222Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9638578Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9638904Z     return mod(*inputs)
2025-09-07T08:13:48.9639231Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9639595Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9639925Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9640271Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9640695Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9641072Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9641453Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9641858Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9642249Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9642645Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9643061Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9643441Z     query, key, value = [
2025-09-07T08:13:48.9643813Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9644249Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9644420Z 
2025-09-07T08:13:48.9644531Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9644888Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9645210Z     return mod(*inputs)
2025-09-07T08:13:48.9645544Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9645909Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9646234Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9646580Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9646939Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9647326Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9647719Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9648130Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9648520Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9648917Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9649332Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9649707Z     query, key, value = [
2025-09-07T08:13:48.9650151Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9650581Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9650744Z 
2025-09-07T08:13:48.9650853Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9651215Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9651533Z     return mod(*inputs)
2025-09-07T08:13:48.9651868Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9652239Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9652570Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9652911Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9653264Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9653647Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9654023Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9654429Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9654878Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9655279Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9655693Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9656134Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9656565Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9657021Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9657242Z 
2025-09-07T08:13:48.9657339Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9657695Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9658016Z     return mod(*inputs)
2025-09-07T08:13:48.9658354Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9658714Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9659040Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9659381Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9659731Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9660097Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9660477Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9660898Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9661290Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9661690Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9662099Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9662541Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9662966Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9663427Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9663647Z 
2025-09-07T08:13:48.9663752Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9664191Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9664517Z     return mod(*inputs)
2025-09-07T08:13:48.9664857Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9665234Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9665630Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9665978Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9666336Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9666716Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9667096Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9667500Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9667894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9668298Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9668802Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9669253Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9669682Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9670147Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9670368Z 
2025-09-07T08:13:48.9670471Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9670833Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9671157Z     return mod(*inputs)
2025-09-07T08:13:48.9671499Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9671870Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9672210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9672562Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9672911Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9673290Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9673685Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9674093Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9674478Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9674877Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9675298Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9675683Z     query, key, value = [
2025-09-07T08:13:48.9676056Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9676485Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9676656Z 
2025-09-07T08:13:48.9676755Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9677114Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9677441Z     return mod(*inputs)
2025-09-07T08:13:48.9677780Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9678217Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9678555Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9678903Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9679261Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9679645Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9680030Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9680435Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9680828Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9681225Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9681643Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9682085Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9682514Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9682910Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9683117Z 
2025-09-07T08:13:48.9683224Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9683580Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9683902Z     return mod(*inputs)
2025-09-07T08:13:48.9684238Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9684605Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9684940Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9685285Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9685638Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9686015Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9686398Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9686798Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9687186Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9687579Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9687995Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9688438Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9688862Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9689259Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9689403Z 
2025-09-07T08:13:48.9689500Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9689860Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9690181Z     return mod(*inputs)
2025-09-07T08:13:48.9690516Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9690881Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9691213Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9691556Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9691905Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9692355Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9692731Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9707105Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9707551Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9707973Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9708406Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9708867Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9709062Z 
2025-09-07T08:13:48.9709171Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9709540Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9709865Z     return mod(*inputs)
2025-09-07T08:13:48.9710202Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9710577Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9711061Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9711412Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9711765Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9712140Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9712521Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9712925Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9713311Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9713705Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9714132Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9714545Z     return self.output_linear(x)
2025-09-07T08:13:48.9714680Z 
2025-09-07T08:13:48.9714789Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9715163Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9715499Z     return mod(*inputs)
2025-09-07T08:13:48.9715855Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9716234Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9716572Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9716922Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9717306Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9717695Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9718079Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9718487Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9718911Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9719341Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9719516Z 
2025-09-07T08:13:48.9719635Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9720017Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9720343Z     return mod(*inputs)
2025-09-07T08:13:48.9720823Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9721209Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9721552Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9721904Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9722274Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9722664Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9723055Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9723469Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9723886Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9724316Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9724501Z 
2025-09-07T08:13:48.9724605Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9724973Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9725302Z     return mod(*inputs)
2025-09-07T08:13:48.9725699Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9726078Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9726409Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9726764Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9727116Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9727498Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9727882Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9728297Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9728720Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9729141Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9729320Z 
2025-09-07T08:13:48.9729422Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9729789Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9730125Z     return mod(*inputs)
2025-09-07T08:13:48.9730461Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9730843Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9731183Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9731541Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9731894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9732274Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9732670Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9733084Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9733485Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9733889Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9734303Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9734686Z     query, key, value = [
2025-09-07T08:13:48.9735060Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9735576Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9735742Z 
2025-09-07T08:13:48.9735846Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9736215Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9736543Z     return mod(*inputs)
2025-09-07T08:13:48.9736883Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9737250Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9737575Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9737924Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9738296Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9738677Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9739054Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9739457Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9739913Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9740316Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9740737Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9741113Z     query, key, value = [
2025-09-07T08:13:48.9741484Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9741916Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9742078Z 
2025-09-07T08:13:48.9742189Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9742556Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9742874Z     return mod(*inputs)
2025-09-07T08:13:48.9743211Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9743583Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9743914Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9744254Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9744609Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9744996Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9745381Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9745822Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9746210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9746609Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9747036Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9747482Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9747915Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9748374Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9748595Z 
2025-09-07T08:13:48.9748696Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9749069Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9749477Z     return mod(*inputs)
2025-09-07T08:13:48.9749829Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9750202Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9750544Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9750902Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9751273Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9751656Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9752045Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9752456Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9752856Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9753265Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9753693Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9754212Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9754658Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9755127Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9755341Z 
2025-09-07T08:13:48.9755451Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9755813Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9756139Z     return mod(*inputs)
2025-09-07T08:13:48.9756485Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9756862Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9757196Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9757544Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9757910Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9758298Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9758682Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9759083Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9759477Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9759871Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9760294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9760738Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9761169Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9761632Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9761848Z 
2025-09-07T08:13:48.9761948Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9762303Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9762625Z     return mod(*inputs)
2025-09-07T08:13:48.9762954Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9763319Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9763913Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9764257Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9764605Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9764981Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9765359Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9765766Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9766164Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9766551Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9766962Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9767346Z     query, key, value = [
2025-09-07T08:13:48.9767709Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9768136Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9768300Z 
2025-09-07T08:13:48.9768469Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9768833Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9769152Z     return mod(*inputs)
2025-09-07T08:13:48.9769485Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9769844Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9770169Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9770510Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9770861Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9771250Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9771626Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9772056Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9772473Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9772873Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9773307Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9773770Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9774204Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9774596Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9774734Z 
2025-09-07T08:13:48.9774854Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9775206Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9775540Z     return mod(*inputs)
2025-09-07T08:13:48.9775874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9776245Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9776583Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9776924Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9777280Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9777649Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9778140Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9778538Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9778927Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9779319Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9779733Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9780169Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9780589Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9780974Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9781116Z 
2025-09-07T08:13:48.9781214Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9781573Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9781893Z     return mod(*inputs)
2025-09-07T08:13:48.9782217Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9782577Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9782986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9783330Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9783678Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9784046Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9784419Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9784818Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9785208Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9785646Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9786059Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9786505Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9786693Z 
2025-09-07T08:13:48.9786791Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9787144Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9787459Z     return mod(*inputs)
2025-09-07T08:13:48.9787783Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9788141Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9788468Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9788809Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9789161Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9789535Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9789911Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9790306Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9790695Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9791079Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9791489Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9791962Z     return self.output_linear(x)
2025-09-07T08:13:48.9792081Z 
2025-09-07T08:13:48.9792183Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9792537Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9792852Z     return mod(*inputs)
2025-09-07T08:13:48.9793185Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9793544Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9793865Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9794201Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9794551Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9794923Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9795294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9795691Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9796098Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9796590Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9796765Z 
2025-09-07T08:13:48.9796869Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9797220Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9797540Z     return mod(*inputs)
2025-09-07T08:13:48.9797868Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9798227Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9798551Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9799110Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9799462Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9799833Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9800211Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9800603Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9801010Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9801428Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9801595Z 
2025-09-07T08:13:48.9801697Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9802048Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9802367Z     return mod(*inputs)
2025-09-07T08:13:48.9802700Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9803064Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9803392Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9803734Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9804080Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9804450Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9804825Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9805222Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9805625Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9806191Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9806368Z 
2025-09-07T08:13:48.9806470Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9806826Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9807153Z     return mod(*inputs)
2025-09-07T08:13:48.9807486Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9807856Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9808181Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9808522Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9808875Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9809248Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9809632Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9810029Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9810192Z 
2025-09-07T08:13:48.9810292Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9810737Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9811065Z     return mod(*inputs)
2025-09-07T08:13:48.9811393Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9811752Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9812081Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9812416Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9812768Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9813148Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9813528Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9813926Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9814313Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9814709Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9815124Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9815504Z     query, key, value = [
2025-09-07T08:13:48.9815861Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9816293Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9816459Z 
2025-09-07T08:13:48.9816555Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9816909Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9817230Z     return mod(*inputs)
2025-09-07T08:13:48.9817559Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9817920Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9818246Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9818589Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9818936Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9819304Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9819679Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9820153Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9820537Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9820926Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9821340Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9821712Z     query, key, value = [
2025-09-07T08:13:48.9822072Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9822488Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9822649Z 
2025-09-07T08:13:48.9822750Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9823108Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9823434Z     return mod(*inputs)
2025-09-07T08:13:48.9823763Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9824128Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9824535Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9824881Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9825233Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9825678Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9826058Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9826456Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9826840Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9827231Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9827638Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9828078Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9828502Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9828956Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9829167Z 
2025-09-07T08:13:48.9829267Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9829616Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9829932Z     return mod(*inputs)
2025-09-07T08:13:48.9830259Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9830622Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9830946Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9831282Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9831631Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9831997Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9832369Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9832760Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9833143Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9833531Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9834022Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9834456Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9834877Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9835324Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9835536Z 
2025-09-07T08:13:48.9835637Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9835995Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9836315Z     return mod(*inputs)
2025-09-07T08:13:48.9836638Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9836999Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9837322Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9837657Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9838002Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9838433Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9838807Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9839201Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9839583Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9839970Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9840376Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9840815Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9841236Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9841682Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9841890Z 
2025-09-07T08:13:48.9841990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9842337Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9842654Z     return mod(*inputs)
2025-09-07T08:13:48.9842988Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9843356Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9843684Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9844033Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9844390Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9844770Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9845145Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9845558Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9845948Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9846341Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9846761Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9847138Z     query, key, value = [
2025-09-07T08:13:48.9847507Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9848013Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9848176Z 
2025-09-07T08:13:48.9848281Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9848639Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9848969Z     return mod(*inputs)
2025-09-07T08:13:48.9849304Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9849675Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9849999Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9850334Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9850689Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9851062Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9851444Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9851843Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9852229Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9852683Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9853100Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9853538Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9853962Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9854346Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9854490Z 
2025-09-07T08:13:48.9854591Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9854953Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9855277Z     return mod(*inputs)
2025-09-07T08:13:48.9855604Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9855973Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9856299Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9856641Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9856988Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9857361Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9857735Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9858136Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9858526Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9858912Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9859327Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9859782Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9860209Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9860596Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9860736Z 
2025-09-07T08:13:48.9860834Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9861186Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9861506Z     return mod(*inputs)
2025-09-07T08:13:48.9861915Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9862286Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9862610Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9862955Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9863307Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9863681Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9864055Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9864458Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9864842Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9865239Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9865712Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9866156Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9866355Z 
2025-09-07T08:13:48.9866538Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9866904Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9867233Z     return mod(*inputs)
2025-09-07T08:13:48.9867565Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9867934Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9868267Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9868612Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9868969Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9869348Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9869729Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9870136Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9870525Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9870917Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9871330Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9871718Z     return self.output_linear(x)
2025-09-07T08:13:48.9871839Z 
2025-09-07T08:13:48.9871939Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9872146Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9872212Z     return mod(*inputs)
2025-09-07T08:13:48.9872448Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9872521Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9872736Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9872804Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9873042Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9873127Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9873365Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9873468Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9873784Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9873901Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9873905Z 
2025-09-07T08:13:48.9874004Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9874213Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9874273Z     return mod(*inputs)
2025-09-07T08:13:48.9874510Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9874578Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9874781Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9874858Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9875081Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9875171Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9875407Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9875507Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9875839Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9875952Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9875955Z 
2025-09-07T08:13:48.9876058Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9876257Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9876317Z     return mod(*inputs)
2025-09-07T08:13:48.9876554Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9876621Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9876836Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9876910Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9877145Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9877228Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9877456Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9877561Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9877804Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9877914Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9877917Z 
2025-09-07T08:13:48.9878017Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9878214Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9878282Z     return mod(*inputs)
2025-09-07T08:13:48.9878517Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9878588Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9878795Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9878862Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9879089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9879171Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9879408Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9879573Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9879803Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9879906Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9880162Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9880230Z     query, key, value = [
2025-09-07T08:13:48.9880492Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9880602Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9880605Z 
2025-09-07T08:13:48.9880700Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9880896Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9880966Z     return mod(*inputs)
2025-09-07T08:13:48.9881197Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9881269Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9881475Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9881603Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9881836Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9881922Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9882158Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9882257Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9882484Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9882591Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9882843Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9882911Z     query, key, value = [
2025-09-07T08:13:48.9883176Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9883284Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9883287Z 
2025-09-07T08:13:48.9883387Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9883593Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9883659Z     return mod(*inputs)
2025-09-07T08:13:48.9883894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9883965Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9884177Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9884253Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9884479Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9884566Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9884804Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9884908Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9885135Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9885239Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9885491Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9885690Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9885932Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9886086Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9886092Z 
2025-09-07T08:13:48.9886193Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9886398Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9886459Z     return mod(*inputs)
2025-09-07T08:13:48.9886690Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9886764Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9886975Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9887052Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9887280Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9887363Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9887663Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9887767Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9887998Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9888099Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9888352Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9888476Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9888715Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9888871Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9888874Z 
2025-09-07T08:13:48.9888973Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9889181Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9889241Z     return mod(*inputs)
2025-09-07T08:13:48.9889474Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9889545Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9889754Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9889828Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9890054Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9890140Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9890381Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9890484Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9890713Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9890815Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9891065Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9891190Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9891429Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9891582Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9891653Z 
2025-09-07T08:13:48.9891923Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9892129Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9892189Z     return mod(*inputs)
2025-09-07T08:13:48.9892423Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9892499Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9892705Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9892783Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9893006Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9893095Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9893327Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9893430Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9893661Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9893829Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9894089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9894153Z     query, key, value = [
2025-09-07T08:13:48.9894414Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9894526Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9894529Z 
2025-09-07T08:13:48.9894628Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9894830Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9894890Z     return mod(*inputs)
2025-09-07T08:13:48.9895123Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9895195Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9895404Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9895480Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9895702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9895788Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9896019Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9896121Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9896348Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9896449Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9896706Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9896832Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9897073Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9897159Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9897163Z 
2025-09-07T08:13:48.9897258Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9897461Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9897521Z     return mod(*inputs)
2025-09-07T08:13:48.9897756Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9897905Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9898113Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9898190Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9898414Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9898502Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9898894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9898994Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9899226Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9899325Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9899586Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9899708Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9899949Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9900132Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9900135Z 
2025-09-07T08:13:48.9900231Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9900436Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9900497Z     return mod(*inputs)
2025-09-07T08:13:48.9900734Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9900798Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9901006Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9901082Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9901307Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9901390Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9901626Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9901723Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9901950Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9902049Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9902305Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9902434Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9902440Z 
2025-09-07T08:13:48.9902541Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9902738Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9902800Z     return mod(*inputs)
2025-09-07T08:13:48.9903043Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9903110Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9903320Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9903388Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9903612Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9903700Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9903932Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9904316Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9904542Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9904647Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9904904Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9904973Z     return self.output_linear(x)
2025-09-07T08:13:48.9904977Z 
2025-09-07T08:13:48.9905080Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9905278Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9905342Z     return mod(*inputs)
2025-09-07T08:13:48.9905656Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9905725Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9905947Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9906017Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9906308Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9906389Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9906621Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9906734Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9906979Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9907095Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9907100Z 
2025-09-07T08:13:48.9907201Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9907406Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9907472Z     return mod(*inputs)
2025-09-07T08:13:48.9907706Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9907782Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9907987Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9908061Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9908285Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9908372Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9908610Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9908710Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9908961Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9909069Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9909072Z 
2025-09-07T08:13:48.9909172Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9909377Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9909438Z     return mod(*inputs)
2025-09-07T08:13:48.9909676Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9909743Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9909954Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9910023Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9910321Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9910417Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9910649Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9910774Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9911024Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9911133Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9911137Z 
2025-09-07T08:13:48.9911239Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9911438Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9911507Z     return mod(*inputs)
2025-09-07T08:13:48.9911739Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9911810Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9912024Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9912092Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9912409Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9912490Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9912726Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9912827Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9912830Z 
2025-09-07T08:13:48.9912925Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9913127Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9913199Z     return mod(*inputs)
2025-09-07T08:13:48.9913441Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9913505Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9913714Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9913786Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9914014Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9914099Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9914328Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9914427Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9914666Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9914770Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9915028Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9915092Z     query, key, value = [
2025-09-07T08:13:48.9915368Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9915480Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9915483Z 
2025-09-07T08:13:48.9915578Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9915789Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9915854Z     return mod(*inputs)
2025-09-07T08:13:48.9916089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9916246Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9916454Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9916540Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9916764Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9916857Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9917093Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9917194Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9917427Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9917526Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9917789Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9917855Z     query, key, value = [
2025-09-07T08:13:48.9918123Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9918225Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9918294Z 
2025-09-07T08:13:48.9918392Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9918599Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9918660Z     return mod(*inputs)
2025-09-07T08:13:48.9918908Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9918975Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9919180Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9919259Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9919485Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9919578Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9919818Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9919931Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9920158Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9920263Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9920527Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9920652Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9920908Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9921064Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9921068Z 
2025-09-07T08:13:48.9921171Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9921397Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9921462Z     return mod(*inputs)
2025-09-07T08:13:48.9921702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9921771Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9921979Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9922058Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9922284Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9922473Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9922710Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9922819Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9923046Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9923148Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9923410Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9923535Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9923786Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9923932Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9923938Z 
2025-09-07T08:13:48.9924041Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9924241Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9924299Z     return mod(*inputs)
2025-09-07T08:13:48.9924610Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9924682Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9924892Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9924963Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9925199Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9925289Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9925522Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9925639Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9925863Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9925967Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9926226Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9926346Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9926598Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9926747Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9926750Z 
2025-09-07T08:13:48.9926852Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9927051Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9927112Z     return mod(*inputs)
2025-09-07T08:13:48.9927348Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9927420Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9927637Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9927708Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9927931Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9928019Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9928252Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9928362Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9928653Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9928756Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9929013Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9929094Z     query, key, value = [
2025-09-07T08:13:48.9929368Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9929474Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9929477Z 
2025-09-07T08:13:48.9929584Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9929787Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9929853Z     return mod(*inputs)
2025-09-07T08:13:48.9930090Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9930161Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9930379Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9930449Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9930736Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9930830Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9931060Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9931168Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9931388Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9931500Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9931764Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9931887Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9932134Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9932226Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9932230Z 
2025-09-07T08:13:48.9932334Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9932533Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9932595Z     return mod(*inputs)
2025-09-07T08:13:48.9932832Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9932897Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9933127Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9933225Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9933462Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9933556Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9933792Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9933903Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9934126Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9934230Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9934481Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9934668Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9934919Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9935000Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9935004Z 
2025-09-07T08:13:48.9935112Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9935306Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9935371Z     return mod(*inputs)
2025-09-07T08:13:48.9935607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9935674Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9935885Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9935966Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9936189Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9936275Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9936517Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9936688Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9936913Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9937016Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9937269Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9937402Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9937405Z 
2025-09-07T08:13:48.9937514Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9937709Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9937775Z     return mod(*inputs)
2025-09-07T08:13:48.9938009Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9938080Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9938293Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9938363Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9938597Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9938678Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9938912Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9939013Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9939236Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9939349Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9939598Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9939674Z     return self.output_linear(x)
2025-09-07T08:13:48.9939678Z 
2025-09-07T08:13:48.9939773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9939961Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9940030Z     return mod(*inputs)
2025-09-07T08:13:48.9940261Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9940341Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9940546Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9940679Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9940907Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9940990Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9941229Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9941330Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9941578Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9941689Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9941693Z 
2025-09-07T08:13:48.9941790Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9941993Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9942054Z     return mod(*inputs)
2025-09-07T08:13:48.9942291Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9942357Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9942641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9942719Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9942942Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9943027Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9943264Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9943368Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9943618Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9943728Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9943731Z 
2025-09-07T08:13:48.9943832Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9944022Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9944087Z     return mod(*inputs)
2025-09-07T08:13:48.9944321Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9944386Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9944596Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9944666Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9944898Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9944979Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9945215Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9945321Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9945618Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9945733Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9945736Z 
2025-09-07T08:13:48.9945833Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9946035Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9946095Z     return mod(*inputs)
2025-09-07T08:13:48.9946331Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9946405Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9946684Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9946760Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9946986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9947072Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9947311Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9947414Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9947644Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9947748Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9948001Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9948073Z     query, key, value = [
2025-09-07T08:13:48.9948335Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9948447Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9948450Z 
2025-09-07T08:13:48.9948608Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9948812Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9948872Z     return mod(*inputs)
2025-09-07T08:13:48.9949108Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9949179Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9949385Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9949462Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9949691Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9949775Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9950014Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9950118Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9950349Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9950450Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9950704Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9950772Z     query, key, value = [
2025-09-07T08:13:48.9951032Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9951145Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9951148Z 
2025-09-07T08:13:48.9951247Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9951454Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9951514Z     return mod(*inputs)
2025-09-07T08:13:48.9951749Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9951821Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9952026Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9952103Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9952329Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9952413Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9952716Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9952817Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9953048Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9953153Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9953413Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9953539Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9953779Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9953933Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9953936Z 
2025-09-07T08:13:48.9954033Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9954242Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9954302Z     return mod(*inputs)
2025-09-07T08:13:48.9954533Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9954670Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9954878Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9954956Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9955183Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9955263Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9955504Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9955605Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9955839Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9955940Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9956200Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9956323Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9956568Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9956722Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9956725Z 
2025-09-07T08:13:48.9956820Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9957025Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9957088Z     return mod(*inputs)
2025-09-07T08:13:48.9957322Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9957396Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9957600Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9957678Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9957906Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9957994Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9958226Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9958328Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9958556Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9958721Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9958979Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9959103Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9959345Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9959497Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9959500Z 
2025-09-07T08:13:48.9959598Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9959801Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9959860Z     return mod(*inputs)
2025-09-07T08:13:48.9960099Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9960169Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9960377Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9960453Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9960743Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9960829Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9961060Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9961163Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9961394Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9961495Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9961770Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9961834Z     query, key, value = [
2025-09-07T08:13:48.9962093Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9962203Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9962208Z 
2025-09-07T08:13:48.9962306Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9962513Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9962573Z     return mod(*inputs)
2025-09-07T08:13:48.9962810Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9962876Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9963081Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9963159Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9963384Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9963468Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9969976Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9970120Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9970374Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9970482Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9970748Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9970875Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9971237Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9971327Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9971331Z 
2025-09-07T08:13:48.9971437Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9971661Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9971726Z     return mod(*inputs)
2025-09-07T08:13:48.9971984Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9972056Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9972293Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9972373Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9972602Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9972702Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9972935Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9973045Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9973404Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9973515Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9973777Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9973902Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9974147Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:48.9974231Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:48.9974239Z 
2025-09-07T08:13:48.9974340Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9974548Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9974608Z     return mod(*inputs)
2025-09-07T08:13:48.9974851Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9974919Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9975131Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9975210Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9975438Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9975531Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9975767Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9975874Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9976118Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9976227Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9976488Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:48.9976622Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:48.9976625Z 
2025-09-07T08:13:48.9976728Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9976927Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9976993Z     return mod(*inputs)
2025-09-07T08:13:48.9977231Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9977362Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9977570Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9977639Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9977863Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9977950Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9978181Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9978287Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9978508Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9978610Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9978862Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:48.9978934Z     return self.output_linear(x)
2025-09-07T08:13:48.9978938Z 
2025-09-07T08:13:48.9979036Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9979228Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9979354Z     return mod(*inputs)
2025-09-07T08:13:48.9979591Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9979654Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9979860Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9979927Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9980152Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9980231Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9980467Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9980566Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9980817Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9980931Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9980934Z 
2025-09-07T08:13:48.9981029Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9981227Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9981286Z     return mod(*inputs)
2025-09-07T08:13:48.9981518Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9981590Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9981798Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9981867Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9982088Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9982170Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9982403Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9982499Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9982750Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9982856Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9982859Z 
2025-09-07T08:13:48.9982952Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9983229Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9983287Z     return mod(*inputs)
2025-09-07T08:13:48.9983526Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9983593Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9983806Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9983875Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9984097Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9984187Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9984419Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9984527Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9984773Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:48.9984884Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:48.9984887Z 
2025-09-07T08:13:48.9984990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9985415Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9985478Z     return mod(*inputs)
2025-09-07T08:13:48.9985781Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9985848Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9986063Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9986128Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9986361Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:48.9986447Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:48.9986683Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9986781Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9986785Z 
2025-09-07T08:13:48.9986891Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9987095Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9987156Z     return mod(*inputs)
2025-09-07T08:13:48.9987392Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9987455Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9987662Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9987732Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9987960Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9988044Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9988274Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9988376Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9988601Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9988704Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9988959Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9989023Z     query, key, value = [
2025-09-07T08:13:48.9989286Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9989468Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9989470Z 
2025-09-07T08:13:48.9989568Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9989775Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9989834Z     return mod(*inputs)
2025-09-07T08:13:48.9990076Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9990144Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9990348Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9990418Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9990642Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9990728Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9990964Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9991069Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9991359Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9991462Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9991718Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:48.9991779Z     query, key, value = [
2025-09-07T08:13:48.9992038Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:48.9992137Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:48.9992140Z 
2025-09-07T08:13:48.9992236Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9992440Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9992497Z     return mod(*inputs)
2025-09-07T08:13:48.9992731Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9992801Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9993008Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9993081Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9993302Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9993381Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9993611Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9993713Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9993938Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9994033Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9994286Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9994410Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9994655Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9994806Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9994809Z 
2025-09-07T08:13:48.9994901Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9995102Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9995243Z     return mod(*inputs)
2025-09-07T08:13:48.9995474Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9995538Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9995751Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9995823Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9996044Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9996127Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9996355Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9996458Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9996680Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9996784Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9997035Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:48.9997158Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:48.9997472Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:48.9997619Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:48.9997623Z 
2025-09-07T08:13:48.9997719Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:48.9997918Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:48.9997975Z     return mod(*inputs)
2025-09-07T08:13:48.9998210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:48.9998278Z     x = self.bert(x, segment_label)
2025-09-07T08:13:48.9998486Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:48.9998553Z     x = transformer.forward(x, mask)
2025-09-07T08:13:48.9998952Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:48.9999035Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:48.9999265Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:48.9999365Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:48.9999587Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:48.9999688Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:48.9999942Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0000067Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0000312Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0000463Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0000467Z 
2025-09-07T08:13:49.0000568Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0000763Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0000820Z     return mod(*inputs)
2025-09-07T08:13:49.0001056Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0001119Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0001325Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0001519Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0001745Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0001827Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0002061Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0002168Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0002391Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0002492Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0002741Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0002803Z     query, key, value = [
2025-09-07T08:13:49.0003071Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0003178Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0003183Z 
2025-09-07T08:13:49.0003287Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0003595Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0003656Z     return mod(*inputs)
2025-09-07T08:13:49.0003886Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0003950Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0004156Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0004222Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0004445Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0004529Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0004760Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0004864Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0005089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0005190Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0005439Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0005565Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0005803Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0005882Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0005888Z 
2025-09-07T08:13:49.0005986Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0006181Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0006242Z     return mod(*inputs)
2025-09-07T08:13:49.0006478Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0006543Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0006753Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0006821Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0007046Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0007125Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0007355Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0007539Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0007759Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0007861Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0008114Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0008240Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0008476Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0008550Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0008554Z 
2025-09-07T08:13:49.0008652Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0008845Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0008909Z     return mod(*inputs)
2025-09-07T08:13:49.0009136Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0009200Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0009471Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0009541Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0009765Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0009844Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0010072Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0010177Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0010399Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0010504Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0010752Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:49.0010887Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:49.0010891Z 
2025-09-07T08:13:49.0010985Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0011179Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0011241Z     return mod(*inputs)
2025-09-07T08:13:49.0011471Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0011536Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0011741Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0011810Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0012038Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0012116Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0012349Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0012448Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0012673Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0012772Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0013019Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:49.0013090Z     return self.output_linear(x)
2025-09-07T08:13:49.0013160Z 
2025-09-07T08:13:49.0013256Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0013455Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0013511Z     return mod(*inputs)
2025-09-07T08:13:49.0013744Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0013813Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0014017Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0014091Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0014316Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0014399Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0014632Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0014737Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0014985Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0015096Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0015100Z 
2025-09-07T08:13:49.0015269Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0015462Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0015521Z     return mod(*inputs)
2025-09-07T08:13:49.0015753Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0015819Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0016029Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0016096Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0016323Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0016406Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0016637Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0016742Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0016986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0017092Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0017099Z 
2025-09-07T08:13:49.0017192Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0017385Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0017447Z     return mod(*inputs)
2025-09-07T08:13:49.0017680Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0017748Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0017953Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0018018Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0018246Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0018325Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0018556Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0018654Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0018896Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0019007Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0019118Z 
2025-09-07T08:13:49.0019211Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0019409Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0019466Z     return mod(*inputs)
2025-09-07T08:13:49.0019705Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0019770Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0019972Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0020043Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0020266Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0020347Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0020580Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0020683Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0020912Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0021073Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0021332Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0021394Z     query, key, value = [
2025-09-07T08:13:49.0021657Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0021759Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0021762Z 
2025-09-07T08:13:49.0021855Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0022049Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0022111Z     return mod(*inputs)
2025-09-07T08:13:49.0022344Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0022409Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0022616Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0022688Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0022911Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0022994Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0023223Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0023321Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0023552Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0023654Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0023906Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0023968Z     query, key, value = [
2025-09-07T08:13:49.0024231Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0024334Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0024337Z 
2025-09-07T08:13:49.0024431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0024629Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0024688Z     return mod(*inputs)
2025-09-07T08:13:49.0024925Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0025053Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0025257Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0025328Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0025598Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0025685Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0025913Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0026012Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0026237Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0026336Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0026593Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0026712Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0026949Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0027170Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0027174Z 
2025-09-07T08:13:49.0027268Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0027462Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0027519Z     return mod(*inputs)
2025-09-07T08:13:49.0027749Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0027810Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0028014Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0028086Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0028304Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0028383Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0028614Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0028712Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0028936Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0029033Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0029281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0029399Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0029640Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0029800Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0029803Z 
2025-09-07T08:13:49.0029902Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0030110Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0030168Z     return mod(*inputs)
2025-09-07T08:13:49.0030403Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0030469Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0030675Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0030748Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0031044Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0031132Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0031364Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0031473Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0031698Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0031802Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0032054Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0032173Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0032414Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0032565Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0032568Z 
2025-09-07T08:13:49.0032665Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0032929Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0032987Z     return mod(*inputs)
2025-09-07T08:13:49.0033228Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0033293Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0033502Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0033568Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0033792Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0033880Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0034110Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0034212Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0034439Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0034541Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0034796Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0034857Z     query, key, value = [
2025-09-07T08:13:49.0035121Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0035223Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0035226Z 
2025-09-07T08:13:49.0035327Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0035528Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0035584Z     return mod(*inputs)
2025-09-07T08:13:49.0035819Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0035885Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0036093Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0036161Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0036382Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0036465Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0036694Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0036865Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0037088Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0037184Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0037438Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0037560Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0037801Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0037878Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0037882Z 
2025-09-07T08:13:49.0037977Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0038169Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0038228Z     return mod(*inputs)
2025-09-07T08:13:49.0038459Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0038521Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0038725Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0038872Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0039096Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0039177Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0039404Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0039504Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0039723Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0039825Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0040078Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0040197Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0040440Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0040518Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0040522Z 
2025-09-07T08:13:49.0040618Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0040811Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0040868Z     return mod(*inputs)
2025-09-07T08:13:49.0041100Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0041165Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0041371Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0041436Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0041658Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0041743Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0041974Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0042074Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0042294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0042391Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0042641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:49.0042832Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:49.0042835Z 
2025-09-07T08:13:49.0042933Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0043125Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0043188Z     return mod(*inputs)
2025-09-07T08:13:49.0043417Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0043481Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0043687Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0043752Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0043976Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0044053Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0044285Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0044390Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0044676Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0044781Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0045030Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:49.0045099Z     return self.output_linear(x)
2025-09-07T08:13:49.0045103Z 
2025-09-07T08:13:49.0045197Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0045384Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0045447Z     return mod(*inputs)
2025-09-07T08:13:49.0045678Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0045745Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0045951Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0046016Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0046243Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0046323Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0046556Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0046651Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0046895Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0047009Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0047014Z 
2025-09-07T08:13:49.0047110Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0047308Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0047366Z     return mod(*inputs)
2025-09-07T08:13:49.0047600Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0047665Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0047868Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0047939Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0048160Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0048239Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0048470Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0048634Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0048878Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0048989Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0048992Z 
2025-09-07T08:13:49.0049091Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0049286Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0049344Z     return mod(*inputs)
2025-09-07T08:13:49.0049573Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0049636Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0049842Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0049909Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0050134Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0050212Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0050500Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0050606Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0050848Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0050955Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0050958Z 
2025-09-07T08:13:49.0051050Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0051238Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0051301Z     return mod(*inputs)
2025-09-07T08:13:49.0051528Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0051596Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0051801Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0051871Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0052095Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0052173Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0052406Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0052502Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0052505Z 
2025-09-07T08:13:49.0052603Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0052797Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0052853Z     return mod(*inputs)
2025-09-07T08:13:49.0053083Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0053144Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0053352Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0053418Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0053641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0053723Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0053954Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0054054Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0054343Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0054449Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0054700Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0054759Z     query, key, value = [
2025-09-07T08:13:49.0055022Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0055119Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0055123Z 
2025-09-07T08:13:49.0055227Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0055413Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0055478Z     return mod(*inputs)
2025-09-07T08:13:49.0055716Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0055782Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0055990Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0056056Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0056342Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0056428Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0056660Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0056759Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0056979Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0057080Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0057329Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0057387Z     query, key, value = [
2025-09-07T08:13:49.0057650Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0057750Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0057753Z 
2025-09-07T08:13:49.0057848Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0058045Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0058105Z     return mod(*inputs)
2025-09-07T08:13:49.0058336Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0058398Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0058605Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0058673Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0058895Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0058975Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0059207Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0059304Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0059519Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0059618Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0059866Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0059987Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0060291Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0060439Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0060442Z 
2025-09-07T08:13:49.0060545Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0060738Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0060794Z     return mod(*inputs)
2025-09-07T08:13:49.0061028Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0061091Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0061296Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0061362Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0061592Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0061674Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0061900Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0062215Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0062441Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0062543Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0062786Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0062905Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0063146Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0063290Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0063293Z 
2025-09-07T08:13:49.0063389Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0063582Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0063644Z     return mod(*inputs)
2025-09-07T08:13:49.0063874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0063936Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0064141Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0064206Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0064427Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0064504Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0064737Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0064835Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0065058Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0065157Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0065403Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0065520Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0065810Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0065955Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0066024Z 
2025-09-07T08:13:49.0066123Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0066318Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0066377Z     return mod(*inputs)
2025-09-07T08:13:49.0066609Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0066674Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0066877Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0066942Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0067164Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0067244Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0067473Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0067575Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0067797Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0067899Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0068281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0068345Z     query, key, value = [
2025-09-07T08:13:49.0068604Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0068704Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0068708Z 
2025-09-07T08:13:49.0068806Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0069001Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0069063Z     return mod(*inputs)
2025-09-07T08:13:49.0069292Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0069355Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0069563Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0069629Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0069851Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0069932Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0070158Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0070258Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0070478Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0070581Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0070828Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0070954Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0071193Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0071273Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0071276Z 
2025-09-07T08:13:49.0071374Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0071569Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0071627Z     return mod(*inputs)
2025-09-07T08:13:49.0071857Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0071994Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0072203Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0072268Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0072493Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0072571Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0072802Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0072900Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0073122Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0073224Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0073470Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0073594Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0073832Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0073984Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0073988Z 
2025-09-07T08:13:49.0074088Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0074283Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0074342Z     return mod(*inputs)
2025-09-07T08:13:49.0074571Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0074633Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0074839Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0074908Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0075133Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0075211Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0075447Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0075549Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0075772Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0075873Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0076122Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:49.0076250Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:49.0076256Z 
2025-09-07T08:13:49.0076351Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0076546Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0076607Z     return mod(*inputs)
2025-09-07T08:13:49.0076839Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0076904Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0077108Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0077180Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0077402Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0077479Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0077711Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0077876Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0078101Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0078198Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0078454Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:49.0078527Z     return self.output_linear(x)
2025-09-07T08:13:49.0078532Z 
2025-09-07T08:13:49.0078628Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0078829Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0078885Z     return mod(*inputs)
2025-09-07T08:13:49.0079115Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0079180Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0079386Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0079453Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0079674Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0079817Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0080054Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0080155Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0080399Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0080509Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0080512Z 
2025-09-07T08:13:49.0080611Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0080811Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0080868Z     return mod(*inputs)
2025-09-07T08:13:49.0081102Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0081165Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0081373Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0081439Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0081657Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0081736Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0081961Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0082060Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0082307Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0082422Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0082426Z 
2025-09-07T08:13:49.0082517Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0082716Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0082781Z     return mod(*inputs)
2025-09-07T08:13:49.0083008Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0083078Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0083281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0083347Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0083575Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0083736Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0083970Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0084068Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0084316Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0084425Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0084428Z 
2025-09-07T08:13:49.0084522Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0084723Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0084780Z     return mod(*inputs)
2025-09-07T08:13:49.0085013Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0085081Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0085286Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0085355Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0085640Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0085727Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0085957Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0086055Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0086284Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0086384Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0086635Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0086699Z     query, key, value = [
2025-09-07T08:13:49.0086961Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0087063Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0087066Z 
2025-09-07T08:13:49.0087160Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0087361Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0087418Z     return mod(*inputs)
2025-09-07T08:13:49.0087653Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0087718Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0087921Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0087991Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0088214Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0088299Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0088531Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0088628Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0088853Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0088954Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0089207Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0089269Z     query, key, value = [
2025-09-07T08:13:49.0089528Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0089692Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0089695Z 
2025-09-07T08:13:49.0089789Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0089990Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0090048Z     return mod(*inputs)
2025-09-07T08:13:49.0090282Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0090346Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0090551Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0090623Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0090845Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0090930Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0091158Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0091257Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0091552Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0091648Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0091902Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0092024Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0092266Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0092414Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0092421Z 
2025-09-07T08:13:49.0092515Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0092717Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0092773Z     return mod(*inputs)
2025-09-07T08:13:49.0093013Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0093077Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0093281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0093352Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0093573Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0093659Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0093888Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0093991Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0094214Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0094314Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0094568Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0094687Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0094931Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0095077Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0095081Z 
2025-09-07T08:13:49.0095189Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0095465Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0095525Z     return mod(*inputs)
2025-09-07T08:13:49.0095769Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0095836Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0096049Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0096119Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0096345Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0096434Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0096664Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0096771Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0096995Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0097096Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0097346Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0097533Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0097781Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T08:13:49.0097928Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T08:13:49.0097931Z 
2025-09-07T08:13:49.0098036Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0098233Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0098292Z     return mod(*inputs)
2025-09-07T08:13:49.0098532Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0098595Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0098964Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0099037Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0099260Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0099347Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0099578Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0099681Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0099905Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0100009Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0100283Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T08:13:49.0100346Z     query, key, value = [
2025-09-07T08:13:49.0100619Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T08:13:49.0100727Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T08:13:49.0100731Z 
2025-09-07T08:13:49.0100837Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0101039Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0101100Z     return mod(*inputs)
2025-09-07T08:13:49.0101342Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0101409Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0101763Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0101833Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0102062Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0102152Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0102387Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0102497Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0102724Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0102828Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0103087Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0103216Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0103459Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0103539Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0103543Z 
2025-09-07T08:13:49.0103739Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0103939Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0103998Z     return mod(*inputs)
2025-09-07T08:13:49.0104239Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0104314Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0104526Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0104593Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0104826Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0104915Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0105146Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0105253Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0105477Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0105647Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0105901Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T08:13:49.0106023Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T08:13:49.0106269Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T08:13:49.0106352Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T08:13:49.0106356Z 
2025-09-07T08:13:49.0106457Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0106653Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0106712Z     return mod(*inputs)
2025-09-07T08:13:49.0106944Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0107008Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0107216Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0107283Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0107506Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0107591Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0107914Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0108024Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0108249Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0108354Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0108607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T08:13:49.0108737Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T08:13:49.0108741Z 
2025-09-07T08:13:49.0108845Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0109044Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0109108Z     return mod(*inputs)
2025-09-07T08:13:49.0109345Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0109410Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0109621Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0109689Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0109975Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T08:13:49.0110057Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T08:13:49.0110294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0110396Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0110621Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T08:13:49.0110725Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T08:13:49.0110977Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T08:13:49.0111050Z     return self.output_linear(x)
2025-09-07T08:13:49.0111054Z 
2025-09-07T08:13:49.0111149Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0111351Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0111413Z     return mod(*inputs)
2025-09-07T08:13:49.0111647Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0111716Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0111923Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0111998Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0112222Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0112305Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0112539Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0112637Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0112888Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0112998Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0113001Z 
2025-09-07T08:13:49.0113094Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0113296Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0113354Z     return mod(*inputs)
2025-09-07T08:13:49.0113594Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0113725Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0113931Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0114002Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0114228Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0114310Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0114540Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0114638Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0114887Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0114996Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0115000Z 
2025-09-07T08:13:49.0115100Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0115296Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0115355Z     return mod(*inputs)
2025-09-07T08:13:49.0115652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0115717Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0115931Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0115997Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0116222Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0116302Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0116531Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0116640Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0116884Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T08:13:49.0116994Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T08:13:49.0116997Z 
2025-09-07T08:13:49.0117095Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0117293Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0117351Z     return mod(*inputs)
2025-09-07T08:13:49.0117582Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T08:13:49.0117650Z     x = self.bert(x, segment_label)
2025-09-07T08:13:49.0117855Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T08:13:49.0117923Z     x = transformer.forward(x, mask)
2025-09-07T08:13:49.0118149Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T08:13:49.0118225Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T08:13:49.0118456Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T08:13:49.0118554Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T08:13:49.0118557Z 
2025-09-07T08:13:49.0118654Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0118845Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0118903Z     return mod(*inputs)
2025-09-07T08:13:49.0119138Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 25, in forward
2025-09-07T08:13:49.0119224Z     return self.next_sentence(x), self.mask_lm(x)
2025-09-07T08:13:49.0119452Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 42, in forward
2025-09-07T08:13:49.0119600Z     return self.softmax(self.linear(x[:, 0]))
2025-09-07T08:13:49.0119603Z 
2025-09-07T08:13:49.0119700Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:13:49.0119896Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:13:49.0119954Z     return mod(*inputs)
2025-09-07T08:13:49.0120190Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 25, in forward
2025-09-07T08:13:49.0120270Z     return self.next_sentence(x), self.mask_lm(x)
2025-09-07T08:13:49.0120504Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 61, in forward
2025-09-07T08:13:49.0120575Z     return self.softmax(self.linear(x))
2025-09-07T08:13:49.0120579Z 
2025-09-07T08:14:05.3577316Z pass
2025-09-07T08:14:05.3578963Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:14:07.7016901Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:14:07.7018240Z   import pynvml  # type: ignore[import]
2025-09-07T08:14:09.7116940Z 
2025-09-07T08:14:11.9372869Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:14:11.9373186Z loading model: 0it [00:02, ?it/s]
2025-09-07T08:14:11.9469905Z cpu  eval  Background_Matting                 
2025-09-07T08:14:12.0561877Z pass_due_to_skip
2025-09-07T08:14:12.0562245Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:14:13.3939058Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:14:13.3940075Z   import pynvml  # type: ignore[import]
2025-09-07T08:14:15.4047640Z 
2025-09-07T08:14:17.3924295Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:14:17.3924651Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:14:17.3965646Z cpu  eval  LearningToPaint                    
2025-09-07T08:14:17.6425950Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:14:17.6843118Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:14:17.7201381Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:14:20.7934340Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7934650Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7934865Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7935113Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7935317Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7935513Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7935697Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7935894Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7936107Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7936306Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7936494Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7936690Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7936891Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7937093Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7937285Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7937480Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7937674Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7937869Z cudagraph partition due to non gpu ops
2025-09-07T08:14:20.7938518Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7938910Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7939250Z     return mod(*inputs)
2025-09-07T08:14:20.7939609Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 128, in forward
2025-09-07T08:14:20.7939997Z     x = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7940144Z 
2025-09-07T08:14:20.7940280Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7940654Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7940990Z     return mod(*inputs)
2025-09-07T08:14:20.7941321Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 128, in forward
2025-09-07T08:14:20.7941690Z     x = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7941818Z 
2025-09-07T08:14:20.7941935Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7942286Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7942615Z     return mod(*inputs)
2025-09-07T08:14:20.7942943Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7943451Z     x = self.layer1(x)
2025-09-07T08:14:20.7943773Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7944139Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7944284Z 
2025-09-07T08:14:20.7944385Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7944750Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7945077Z     return mod(*inputs)
2025-09-07T08:14:20.7945393Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7945826Z     x = self.layer1(x)
2025-09-07T08:14:20.7946147Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7946510Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7946644Z 
2025-09-07T08:14:20.7946741Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7947103Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7947428Z     return mod(*inputs)
2025-09-07T08:14:20.7947749Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7948090Z     x = self.layer1(x)
2025-09-07T08:14:20.7948394Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.7948765Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.7948894Z 
2025-09-07T08:14:20.7948996Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7949350Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7949665Z     return mod(*inputs)
2025-09-07T08:14:20.7949979Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7950333Z     x = self.layer1(x)
2025-09-07T08:14:20.7950654Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T08:14:20.7951004Z     out += self.shortcut(x)
2025-09-07T08:14:20.7951113Z 
2025-09-07T08:14:20.7951209Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7951565Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7951885Z     return mod(*inputs)
2025-09-07T08:14:20.7952201Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7952643Z     x = self.layer1(x)
2025-09-07T08:14:20.7952957Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7953312Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7953444Z 
2025-09-07T08:14:20.7953545Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7953900Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7954215Z     return mod(*inputs)
2025-09-07T08:14:20.7954530Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7954882Z     x = self.layer1(x)
2025-09-07T08:14:20.7955195Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7955540Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7955677Z 
2025-09-07T08:14:20.7955772Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7956125Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7956446Z     return mod(*inputs)
2025-09-07T08:14:20.7956758Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7957090Z     x = self.layer1(x)
2025-09-07T08:14:20.7957492Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.7957856Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.7957981Z 
2025-09-07T08:14:20.7958086Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7958440Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7958759Z     return mod(*inputs)
2025-09-07T08:14:20.7959078Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T08:14:20.7959426Z     x = self.layer1(x)
2025-09-07T08:14:20.7959739Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T08:14:20.7960076Z     out = F.relu(out)
2025-09-07T08:14:20.7960176Z 
2025-09-07T08:14:20.7960273Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7960633Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7960954Z     return mod(*inputs)
2025-09-07T08:14:20.7961265Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7961608Z     x = self.layer2(x)
2025-09-07T08:14:20.7961914Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7962267Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7962398Z 
2025-09-07T08:14:20.7962502Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7962850Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7963173Z     return mod(*inputs)
2025-09-07T08:14:20.7963494Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7963840Z     x = self.layer2(x)
2025-09-07T08:14:20.7964147Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7964497Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7964631Z 
2025-09-07T08:14:20.7964726Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7965074Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7965400Z     return mod(*inputs)
2025-09-07T08:14:20.7965709Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7966050Z     x = self.layer2(x)
2025-09-07T08:14:20.7966441Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.7966792Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.7966917Z 
2025-09-07T08:14:20.7967014Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7967372Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7967696Z     return mod(*inputs)
2025-09-07T08:14:20.7968012Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7968349Z     x = self.layer2(x)
2025-09-07T08:14:20.7968674Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T08:14:20.7969025Z     out += self.shortcut(x)
2025-09-07T08:14:20.7969132Z 
2025-09-07T08:14:20.7969281Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7969632Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7969956Z     return mod(*inputs)
2025-09-07T08:14:20.7970271Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7970608Z     x = self.layer2(x)
2025-09-07T08:14:20.7970977Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7971334Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7971463Z 
2025-09-07T08:14:20.7971565Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7971916Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7972229Z     return mod(*inputs)
2025-09-07T08:14:20.7972546Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7972881Z     x = self.layer2(x)
2025-09-07T08:14:20.7973187Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7973529Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7973664Z 
2025-09-07T08:14:20.7973755Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7974110Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7974432Z     return mod(*inputs)
2025-09-07T08:14:20.7974745Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7975073Z     x = self.layer2(x)
2025-09-07T08:14:20.7975381Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.7975723Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.7975846Z 
2025-09-07T08:14:20.7975946Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7976292Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7976616Z     return mod(*inputs)
2025-09-07T08:14:20.7976931Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T08:14:20.7977276Z     x = self.layer2(x)
2025-09-07T08:14:20.7977579Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T08:14:20.7977908Z     out = F.relu(out)
2025-09-07T08:14:20.7978004Z 
2025-09-07T08:14:20.7978097Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7978449Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7978765Z     return mod(*inputs)
2025-09-07T08:14:20.7979072Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.7979414Z     x = self.layer3(x)
2025-09-07T08:14:20.7979722Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7980152Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7980280Z 
2025-09-07T08:14:20.7980383Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7980732Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7981052Z     return mod(*inputs)
2025-09-07T08:14:20.7981369Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.7981710Z     x = self.layer3(x)
2025-09-07T08:14:20.7982009Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7982359Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7982493Z 
2025-09-07T08:14:20.7982588Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7982934Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7983254Z     return mod(*inputs)
2025-09-07T08:14:20.7983560Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.7983905Z     x = self.layer3(x)
2025-09-07T08:14:20.7984214Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.7984660Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.7984782Z 
2025-09-07T08:14:20.7984880Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7985230Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7985600Z     return mod(*inputs)
2025-09-07T08:14:20.7985919Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.7986257Z     x = self.layer3(x)
2025-09-07T08:14:20.7986556Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T08:14:20.7986900Z     out += self.shortcut(x)
2025-09-07T08:14:20.7987012Z 
2025-09-07T08:14:20.7987109Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7987460Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7987771Z     return mod(*inputs)
2025-09-07T08:14:20.7988118Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.7988474Z     x = self.layer3(x)
2025-09-07T08:14:20.7988792Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7989168Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7989303Z 
2025-09-07T08:14:20.7989406Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.7997405Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.7997796Z     return mod(*inputs)
2025-09-07T08:14:20.7998145Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.7998512Z     x = self.layer3(x)
2025-09-07T08:14:20.7999047Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.7999415Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.7999555Z 
2025-09-07T08:14:20.7999660Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8000035Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8000366Z     return mod(*inputs)
2025-09-07T08:14:20.8000697Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.8001045Z     x = self.layer3(x)
2025-09-07T08:14:20.8001361Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.8001904Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.8002039Z 
2025-09-07T08:14:20.8002141Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8002504Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8002828Z     return mod(*inputs)
2025-09-07T08:14:20.8003160Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T08:14:20.8003506Z     x = self.layer3(x)
2025-09-07T08:14:20.8003822Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T08:14:20.8004158Z     out = F.relu(out)
2025-09-07T08:14:20.8004249Z 
2025-09-07T08:14:20.8004344Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8004701Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8005024Z     return mod(*inputs)
2025-09-07T08:14:20.8005343Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8005684Z     x = self.layer4(x)
2025-09-07T08:14:20.8005995Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.8006345Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.8006479Z 
2025-09-07T08:14:20.8006681Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8007043Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8007357Z     return mod(*inputs)
2025-09-07T08:14:20.8007673Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8008014Z     x = self.layer4(x)
2025-09-07T08:14:20.8008330Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.8008679Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.8008824Z 
2025-09-07T08:14:20.8008923Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8009279Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8009603Z     return mod(*inputs)
2025-09-07T08:14:20.8009926Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8010259Z     x = self.layer4(x)
2025-09-07T08:14:20.8010572Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.8010923Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.8011047Z 
2025-09-07T08:14:20.8011154Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8011500Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8011829Z     return mod(*inputs)
2025-09-07T08:14:20.8012153Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8012500Z     x = self.layer4(x)
2025-09-07T08:14:20.8012819Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T08:14:20.8013160Z     out += self.shortcut(x)
2025-09-07T08:14:20.8013277Z 
2025-09-07T08:14:20.8013379Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8013743Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8014063Z     return mod(*inputs)
2025-09-07T08:14:20.8014374Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8014719Z     x = self.layer4(x)
2025-09-07T08:14:20.8015032Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.8015393Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.8015525Z 
2025-09-07T08:14:20.8015750Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8016105Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8016430Z     return mod(*inputs)
2025-09-07T08:14:20.8016751Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8017104Z     x = self.layer4(x)
2025-09-07T08:14:20.8017409Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T08:14:20.8017755Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T08:14:20.8017892Z 
2025-09-07T08:14:20.8017988Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8018346Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8018668Z     return mod(*inputs)
2025-09-07T08:14:20.8018977Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8019324Z     x = self.layer4(x)
2025-09-07T08:14:20.8019632Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T08:14:20.8019983Z     out = self.bn2(self.conv2(out))
2025-09-07T08:14:20.8020105Z 
2025-09-07T08:14:20.8020268Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8020624Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8020940Z     return mod(*inputs)
2025-09-07T08:14:20.8021253Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T08:14:20.8021596Z     x = self.layer4(x)
2025-09-07T08:14:20.8021896Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T08:14:20.8022235Z     out = F.relu(out)
2025-09-07T08:14:20.8022325Z 
2025-09-07T08:14:20.8022427Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8022785Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8023097Z     return mod(*inputs)
2025-09-07T08:14:20.8023412Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 133, in forward
2025-09-07T08:14:20.8023762Z     x = F.avg_pool2d(x, 4)
2025-09-07T08:14:20.8023872Z 
2025-09-07T08:14:20.8023975Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8024334Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8024651Z     return mod(*inputs)
2025-09-07T08:14:20.8024970Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 135, in forward
2025-09-07T08:14:20.8025315Z     x = self.fc(x)
2025-09-07T08:14:20.8025403Z 
2025-09-07T08:14:20.8025506Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:14:20.8025911Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:14:20.8026236Z     return mod(*inputs)
2025-09-07T08:14:20.8026553Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 136, in forward
2025-09-07T08:14:20.8026906Z     x = torch.sigmoid(x)
2025-09-07T08:14:20.8027008Z 
2025-09-07T08:14:33.9255286Z pass
2025-09-07T08:14:33.9257798Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:14:36.1624256Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:14:36.1625260Z   import pynvml  # type: ignore[import]
2025-09-07T08:14:38.1764049Z 
2025-09-07T08:14:39.7014096Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T08:14:40.0934361Z 
2025-09-07T08:14:40.0934792Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:14:40.0935216Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T08:14:40.0935571Z cpu  eval  Super_SloMo                        
2025-09-07T08:15:00.3242546Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:15:00.3243049Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T08:15:00.9331097Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:15:01.5400299Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:15:13.1667309Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.1667605Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.1667855Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1668291Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1668649Z     return mod(*inputs)
2025-09-07T08:15:13.1668962Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1669794Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1670154Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1670495Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1670654Z 
2025-09-07T08:15:13.1670760Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1671133Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1671467Z     return mod(*inputs)
2025-09-07T08:15:13.1671756Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1672118Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1672456Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1672801Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1672948Z 
2025-09-07T08:15:13.1673056Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1673416Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1673745Z     return mod(*inputs)
2025-09-07T08:15:13.1674028Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1674370Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1674700Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.1675043Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1675204Z 
2025-09-07T08:15:13.1675348Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1675710Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1676036Z     return mod(*inputs)
2025-09-07T08:15:13.1676309Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1676644Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1676989Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.1677339Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1677485Z 
2025-09-07T08:15:13.1677585Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1677938Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1678269Z     return mod(*inputs)
2025-09-07T08:15:13.1678566Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1679110Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1679451Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1679769Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1680123Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1680474Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1680625Z 
2025-09-07T08:15:13.1680735Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1681090Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1681412Z     return mod(*inputs)
2025-09-07T08:15:13.1681696Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1682042Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1682379Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1682688Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1682970Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1683306Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1683531Z 
2025-09-07T08:15:13.1683641Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1683993Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1684331Z     return mod(*inputs)
2025-09-07T08:15:13.1684611Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1684951Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1685272Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1685580Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1685849Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1686178Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1686323Z 
2025-09-07T08:15:13.1686431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1686796Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1687126Z     return mod(*inputs)
2025-09-07T08:15:13.1687410Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1687751Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1688081Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1688386Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1688661Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1688992Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1689137Z 
2025-09-07T08:15:13.1689242Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1689595Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1689919Z     return mod(*inputs)
2025-09-07T08:15:13.1690201Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1690546Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1690869Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1691181Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1691454Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1691792Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1691937Z 
2025-09-07T08:15:13.1692133Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1692479Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1692810Z     return mod(*inputs)
2025-09-07T08:15:13.1693098Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1693442Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1693765Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1694072Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1694344Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1694679Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1694826Z 
2025-09-07T08:15:13.1694928Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1695275Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1695621Z     return mod(*inputs)
2025-09-07T08:15:13.1695905Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1696244Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1696647Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1696960Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1697243Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1697574Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1697719Z 
2025-09-07T08:15:13.1697823Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1698182Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1698509Z     return mod(*inputs)
2025-09-07T08:15:13.1698956Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1699303Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1699628Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1699934Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1700214Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1700542Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1700687Z 
2025-09-07T08:15:13.1700791Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1701146Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1701469Z     return mod(*inputs)
2025-09-07T08:15:13.1701744Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1702080Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1702405Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1702720Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1703001Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1703330Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1703475Z 
2025-09-07T08:15:13.1703590Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1703944Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1704262Z     return mod(*inputs)
2025-09-07T08:15:13.1704543Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1704879Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1705197Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1705685Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1705963Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1706297Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1706502Z 
2025-09-07T08:15:13.1706606Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1706954Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1707280Z     return mod(*inputs)
2025-09-07T08:15:13.1707558Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1707892Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1708220Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1708525Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1708800Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1709160Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1709308Z 
2025-09-07T08:15:13.1709410Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1709758Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1710078Z     return mod(*inputs)
2025-09-07T08:15:13.1710469Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1710814Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1711131Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1711442Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1711713Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1712038Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1712183Z 
2025-09-07T08:15:13.1712291Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1712635Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1712964Z     return mod(*inputs)
2025-09-07T08:15:13.1713244Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1713585Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1713911Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1714206Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1714476Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1714809Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1714953Z 
2025-09-07T08:15:13.1715053Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1715398Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1715758Z     return mod(*inputs)
2025-09-07T08:15:13.1716042Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1716373Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1716701Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1717003Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1717273Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1717600Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1717741Z 
2025-09-07T08:15:13.1717843Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1718193Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1718513Z     return mod(*inputs)
2025-09-07T08:15:13.1718784Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1719231Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1719561Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1719865Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1720140Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1720470Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1720617Z 
2025-09-07T08:15:13.1720720Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1721070Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1721390Z     return mod(*inputs)
2025-09-07T08:15:13.1721667Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1722035Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1722371Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1722668Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1722940Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1723272Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1723482Z 
2025-09-07T08:15:13.1723597Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1723940Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1724259Z     return mod(*inputs)
2025-09-07T08:15:13.1724535Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1724863Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1725187Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1725492Z     x = self.down5(s5)
2025-09-07T08:15:13.1725762Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1726095Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1726238Z 
2025-09-07T08:15:13.1726342Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1726692Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1727024Z     return mod(*inputs)
2025-09-07T08:15:13.1727297Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1727632Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1727955Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1728255Z     x = self.down5(s5)
2025-09-07T08:15:13.1728531Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1728865Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1729008Z 
2025-09-07T08:15:13.1729106Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1729456Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1729786Z     return mod(*inputs)
2025-09-07T08:15:13.1730064Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1730397Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1730718Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1731015Z     x = self.down5(s5)
2025-09-07T08:15:13.1731285Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1731612Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1731754Z 
2025-09-07T08:15:13.1731946Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1732299Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1732632Z     return mod(*inputs)
2025-09-07T08:15:13.1732925Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1733274Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1733606Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1733913Z     x = self.down5(s5)
2025-09-07T08:15:13.1734190Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1734525Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1734674Z 
2025-09-07T08:15:13.1734780Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1735128Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1735470Z     return mod(*inputs)
2025-09-07T08:15:13.1735754Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1736094Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1736488Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1736797Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1737073Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1737405Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1737551Z 
2025-09-07T08:15:13.1737654Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1738003Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1738328Z     return mod(*inputs)
2025-09-07T08:15:13.1738609Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1738949Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1739270Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1739570Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1739848Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1740178Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1740322Z 
2025-09-07T08:15:13.1740431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1740779Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1741101Z     return mod(*inputs)
2025-09-07T08:15:13.1741378Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1741715Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1742036Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1742336Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1742606Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1742990Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1743187Z 
2025-09-07T08:15:13.1743291Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1743638Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1743958Z     return mod(*inputs)
2025-09-07T08:15:13.1744236Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1744575Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1744897Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1745293Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1745622Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1746006Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1746201Z 
2025-09-07T08:15:13.1746311Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1746669Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1747000Z     return mod(*inputs)
2025-09-07T08:15:13.1747284Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1747625Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1747957Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1748263Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1748533Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1748872Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1749016Z 
2025-09-07T08:15:13.1749120Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1749460Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1749860Z     return mod(*inputs)
2025-09-07T08:15:13.1750138Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1750480Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1750811Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1751108Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1751385Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1751714Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1751862Z 
2025-09-07T08:15:13.1751966Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1752315Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1752637Z     return mod(*inputs)
2025-09-07T08:15:13.1752921Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1753260Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1753583Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1753891Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1754159Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1754539Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1754731Z 
2025-09-07T08:15:13.1754834Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1755184Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1755507Z     return mod(*inputs)
2025-09-07T08:15:13.1755784Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1756119Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1756449Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1756747Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1757021Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1757397Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1757590Z 
2025-09-07T08:15:13.1757691Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1758037Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1758445Z     return mod(*inputs)
2025-09-07T08:15:13.1758726Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1759064Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1759396Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1759693Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1759964Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1760289Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1760432Z 
2025-09-07T08:15:13.1760534Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1760886Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1761209Z     return mod(*inputs)
2025-09-07T08:15:13.1761485Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1761826Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1762154Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1762452Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1762726Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1763152Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1763301Z 
2025-09-07T08:15:13.1763406Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1763747Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1764066Z     return mod(*inputs)
2025-09-07T08:15:13.1764354Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1764689Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1765016Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1765319Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1765588Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1765963Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1766156Z 
2025-09-07T08:15:13.1766262Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1766602Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1766931Z     return mod(*inputs)
2025-09-07T08:15:13.1767215Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1767552Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1767883Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1768180Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1768457Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1768828Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1769021Z 
2025-09-07T08:15:13.1769124Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1769473Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1769797Z     return mod(*inputs)
2025-09-07T08:15:13.1770088Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1770425Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1770757Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1771057Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1771333Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1772789Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1772939Z 
2025-09-07T08:15:13.1773051Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1773407Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1773736Z     return mod(*inputs)
2025-09-07T08:15:13.1774017Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1774358Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1774690Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1774988Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1775262Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1775595Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1775742Z 
2025-09-07T08:15:13.1775850Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1776205Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1776527Z     return mod(*inputs)
2025-09-07T08:15:13.1776809Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1777219Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1777552Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1777853Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1778125Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1778504Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1778696Z 
2025-09-07T08:15:13.1778801Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1779147Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1779474Z     return mod(*inputs)
2025-09-07T08:15:13.1779751Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1780093Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1780426Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1780728Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1781002Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1781385Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1781577Z 
2025-09-07T08:15:13.1781681Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1782032Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1782356Z     return mod(*inputs)
2025-09-07T08:15:13.1782638Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1782980Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1783300Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1783603Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1783874Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1784206Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1784351Z 
2025-09-07T08:15:13.1784450Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1784798Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1785120Z     return mod(*inputs)
2025-09-07T08:15:13.1785400Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1785863Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1786259Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1786559Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1786832Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1787165Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1787308Z 
2025-09-07T08:15:13.1787409Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1787751Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1788077Z     return mod(*inputs)
2025-09-07T08:15:13.1788356Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1788691Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1789016Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1789316Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1789587Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1789960Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1790155Z 
2025-09-07T08:15:13.1790319Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1790671Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1790993Z     return mod(*inputs)
2025-09-07T08:15:13.1791274Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1791608Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1791936Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1792231Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1792506Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1792882Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1793080Z 
2025-09-07T08:15:13.1793184Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1793536Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1793865Z     return mod(*inputs)
2025-09-07T08:15:13.1794143Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1794480Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1794817Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T08:15:13.1795147Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T08:15:13.1795301Z 
2025-09-07T08:15:13.1795398Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1795752Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1796082Z     return mod(*inputs)
2025-09-07T08:15:13.1796357Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1796697Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1797027Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T08:15:13.1797363Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T08:15:13.1797506Z 
2025-09-07T08:15:13.1797595Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.1797798Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.1798034Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1798390Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1798713Z     return mod(*inputs)
2025-09-07T08:15:13.1799157Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1799614Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1799931Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1800269Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1800418Z 
2025-09-07T08:15:13.1800526Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1800884Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1801218Z     return mod(*inputs)
2025-09-07T08:15:13.1801508Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1801844Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1802168Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1802509Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1802670Z 
2025-09-07T08:15:13.1802773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1803132Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1803455Z     return mod(*inputs)
2025-09-07T08:15:13.1803826Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1804163Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1804472Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.1804818Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1804968Z 
2025-09-07T08:15:13.1805068Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1805429Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1805754Z     return mod(*inputs)
2025-09-07T08:15:13.1806037Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1806360Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1806664Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.1807003Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1807159Z 
2025-09-07T08:15:13.1807258Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1807614Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1807932Z     return mod(*inputs)
2025-09-07T08:15:13.1808219Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1808544Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1808854Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1809158Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1809435Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1809769Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1809926Z 
2025-09-07T08:15:13.1810026Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1810384Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1810703Z     return mod(*inputs)
2025-09-07T08:15:13.1810985Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1811303Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1811610Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1811916Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1812184Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1812521Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1812746Z 
2025-09-07T08:15:13.1812843Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1813196Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1813513Z     return mod(*inputs)
2025-09-07T08:15:13.1813794Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1814122Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1814435Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1814741Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1815004Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1815335Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1815481Z 
2025-09-07T08:15:13.1815586Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1815943Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1816255Z     return mod(*inputs)
2025-09-07T08:15:13.1816538Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1816857Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1817240Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1817554Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1817827Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1818163Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1818311Z 
2025-09-07T08:15:13.1818416Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1818776Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1819096Z     return mod(*inputs)
2025-09-07T08:15:13.1819380Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1819706Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1820017Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1820317Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1820595Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1820923Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1821065Z 
2025-09-07T08:15:13.1821168Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1821514Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1821826Z     return mod(*inputs)
2025-09-07T08:15:13.1822103Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1822428Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1822741Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1823042Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1823322Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1823663Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1823809Z 
2025-09-07T08:15:13.1823912Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1824268Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1824584Z     return mod(*inputs)
2025-09-07T08:15:13.1824864Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1825191Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1825502Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1825910Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1826190Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1826520Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1826668Z 
2025-09-07T08:15:13.1826774Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1827132Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1827448Z     return mod(*inputs)
2025-09-07T08:15:13.1827730Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1828051Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1828359Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1828654Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1828924Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1829257Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1829403Z 
2025-09-07T08:15:13.1829506Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1829859Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1830172Z     return mod(*inputs)
2025-09-07T08:15:13.1830519Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1830848Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1831154Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1831453Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1831723Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1832048Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1832194Z 
2025-09-07T08:15:13.1832297Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1832658Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1832973Z     return mod(*inputs)
2025-09-07T08:15:13.1833252Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1833577Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1833888Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1834188Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1834459Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1834784Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1834926Z 
2025-09-07T08:15:13.1835028Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1835378Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1835699Z     return mod(*inputs)
2025-09-07T08:15:13.1835983Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1836305Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1836613Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1836912Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1837365Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1837696Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1837841Z 
2025-09-07T08:15:13.1837945Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1838298Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1838615Z     return mod(*inputs)
2025-09-07T08:15:13.1838898Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1839304Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1839620Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1839920Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1840197Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1840531Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1840680Z 
2025-09-07T08:15:13.1840788Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1841155Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1841481Z     return mod(*inputs)
2025-09-07T08:15:13.1841763Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1842093Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1842401Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1842704Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1842982Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1843315Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1843461Z 
2025-09-07T08:15:13.1843569Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1843991Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1844312Z     return mod(*inputs)
2025-09-07T08:15:13.1844596Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1844925Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1845238Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1845542Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1845818Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1846155Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1846303Z 
2025-09-07T08:15:13.1846408Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1846758Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1847091Z     return mod(*inputs)
2025-09-07T08:15:13.1847376Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1847704Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1848012Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1848314Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1848590Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1848917Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1849062Z 
2025-09-07T08:15:13.1849173Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1849522Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1849849Z     return mod(*inputs)
2025-09-07T08:15:13.1850134Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1850460Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1850769Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1851065Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1851336Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1851671Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1851818Z 
2025-09-07T08:15:13.1851925Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1852272Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1863273Z     return mod(*inputs)
2025-09-07T08:15:13.1863647Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1864003Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1864333Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1864659Z     x = self.down5(s5)
2025-09-07T08:15:13.1864943Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1865290Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1865452Z 
2025-09-07T08:15:13.1865613Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1865993Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1866321Z     return mod(*inputs)
2025-09-07T08:15:13.1866622Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1866974Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1867304Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1867623Z     x = self.down5(s5)
2025-09-07T08:15:13.1867901Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1868351Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1868515Z 
2025-09-07T08:15:13.1868618Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1868984Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1869309Z     return mod(*inputs)
2025-09-07T08:15:13.1869596Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1869928Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1870243Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1870556Z     x = self.down5(s5)
2025-09-07T08:15:13.1870824Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1871155Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1871310Z 
2025-09-07T08:15:13.1871412Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1871773Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1872084Z     return mod(*inputs)
2025-09-07T08:15:13.1872367Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1872693Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1873007Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1873317Z     x = self.down5(s5)
2025-09-07T08:15:13.1873587Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1873926Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1874073Z 
2025-09-07T08:15:13.1874177Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1874535Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1874857Z     return mod(*inputs)
2025-09-07T08:15:13.1875133Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1875460Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1875780Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1876095Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1876371Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1876711Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1876944Z 
2025-09-07T08:15:13.1877056Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1877422Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1877745Z     return mod(*inputs)
2025-09-07T08:15:13.1878083Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1878434Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1878749Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1879051Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1879323Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1879659Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1879807Z 
2025-09-07T08:15:13.1879918Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1880282Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1880603Z     return mod(*inputs)
2025-09-07T08:15:13.1880886Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1881215Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1881598Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1881911Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1882188Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1882567Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1882763Z 
2025-09-07T08:15:13.1882873Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1883230Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1883548Z     return mod(*inputs)
2025-09-07T08:15:13.1883827Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1884158Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1884470Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.1884769Z     x = self.up1(x, s5)
2025-09-07T08:15:13.1885041Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1885416Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1885609Z 
2025-09-07T08:15:13.1885715Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1886071Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1886385Z     return mod(*inputs)
2025-09-07T08:15:13.1886663Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1886987Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1887297Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1887596Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1887870Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1888202Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1888353Z 
2025-09-07T08:15:13.1888460Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1888812Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1889124Z     return mod(*inputs)
2025-09-07T08:15:13.1889403Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1889727Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1890027Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1890330Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1890676Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1891003Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1891149Z 
2025-09-07T08:15:13.1891247Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1891606Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1891925Z     return mod(*inputs)
2025-09-07T08:15:13.1892209Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1892521Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1892831Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1893130Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1893399Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1893778Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1893974Z 
2025-09-07T08:15:13.1894069Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1894426Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1894752Z     return mod(*inputs)
2025-09-07T08:15:13.1895117Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1895441Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1895745Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.1896050Z     x = self.up2(x, s4)
2025-09-07T08:15:13.1896321Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1896697Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1896892Z 
2025-09-07T08:15:13.1896992Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1897347Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1897674Z     return mod(*inputs)
2025-09-07T08:15:13.1897952Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1898270Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1898575Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1899036Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1899317Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1899653Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1899802Z 
2025-09-07T08:15:13.1899901Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1900250Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1900570Z     return mod(*inputs)
2025-09-07T08:15:13.1900840Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1901154Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1901456Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1901754Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1902022Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1902349Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1902492Z 
2025-09-07T08:15:13.1902589Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1902927Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1903237Z     return mod(*inputs)
2025-09-07T08:15:13.1903502Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1903956Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1904252Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1904542Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1904811Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1905180Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1905378Z 
2025-09-07T08:15:13.1905474Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1905883Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1906198Z     return mod(*inputs)
2025-09-07T08:15:13.1906472Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1906795Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1907094Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.1907421Z     x = self.up3(x, s3)
2025-09-07T08:15:13.1907682Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1908044Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1908236Z 
2025-09-07T08:15:13.1908439Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1908795Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1909113Z     return mod(*inputs)
2025-09-07T08:15:13.1909386Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1909701Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1909998Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1910340Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1910637Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1910963Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1911110Z 
2025-09-07T08:15:13.1911206Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1911577Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1911894Z     return mod(*inputs)
2025-09-07T08:15:13.1912166Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1912497Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1912801Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1913096Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1913357Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1913675Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1913826Z 
2025-09-07T08:15:13.1913924Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1914269Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1914587Z     return mod(*inputs)
2025-09-07T08:15:13.1914870Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1915179Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1915477Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1915770Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1916037Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1916399Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1916591Z 
2025-09-07T08:15:13.1916683Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1917103Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1917417Z     return mod(*inputs)
2025-09-07T08:15:13.1917688Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1917997Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1918296Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.1918587Z     x = self.up4(x, s2)
2025-09-07T08:15:13.1918849Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1919208Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1919401Z 
2025-09-07T08:15:13.1919495Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1919845Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1920167Z     return mod(*inputs)
2025-09-07T08:15:13.1920440Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1920757Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1921058Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1921421Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1921690Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1922012Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1922165Z 
2025-09-07T08:15:13.1922261Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1922607Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1922922Z     return mod(*inputs)
2025-09-07T08:15:13.1923194Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1923510Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1923810Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1924111Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1924376Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.1924698Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1924848Z 
2025-09-07T08:15:13.1924941Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1925284Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1925596Z     return mod(*inputs)
2025-09-07T08:15:13.1925869Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1926178Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1926477Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1926777Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1927037Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1927398Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1927588Z 
2025-09-07T08:15:13.1927684Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1928017Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1928331Z     return mod(*inputs)
2025-09-07T08:15:13.1928600Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1928909Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1929206Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.1929497Z     x = self.up5(x, s1)
2025-09-07T08:15:13.1929764Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.1930201Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.1930394Z 
2025-09-07T08:15:13.1930490Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1930835Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1931153Z     return mod(*inputs)
2025-09-07T08:15:13.1931425Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1931735Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1932033Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T08:15:13.1932352Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T08:15:13.1932497Z 
2025-09-07T08:15:13.1932596Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1932938Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1933257Z     return mod(*inputs)
2025-09-07T08:15:13.1933528Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.1933844Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.1934244Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T08:15:13.1934577Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T08:15:13.1934728Z 
2025-09-07T08:15:13.1934828Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1935177Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1935496Z     return mod(*inputs)
2025-09-07T08:15:13.1935774Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1936116Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1936273Z 
2025-09-07T08:15:13.1936370Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1936725Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1937040Z     return mod(*inputs)
2025-09-07T08:15:13.1937311Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1937642Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1937966Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1938291Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1938435Z 
2025-09-07T08:15:13.1938529Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1938873Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1939185Z     return mod(*inputs)
2025-09-07T08:15:13.1939452Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1939781Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1940097Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1940418Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1940559Z 
2025-09-07T08:15:13.1940653Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1940998Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1941302Z     return mod(*inputs)
2025-09-07T08:15:13.1941570Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1941896Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1942217Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.1942538Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1942753Z 
2025-09-07T08:15:13.1942843Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1943179Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1943489Z     return mod(*inputs)
2025-09-07T08:15:13.1943760Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1944084Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1944402Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.1944731Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1944878Z 
2025-09-07T08:15:13.1944972Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1945312Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1945684Z     return mod(*inputs)
2025-09-07T08:15:13.1945957Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1946285Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1946601Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1946963Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1947228Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.1947530Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.1947635Z 
2025-09-07T08:15:13.1947733Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1948106Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1948418Z     return mod(*inputs)
2025-09-07T08:15:13.1948689Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1949018Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1949344Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1949639Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1949903Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1950227Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1950372Z 
2025-09-07T08:15:13.1950467Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1950806Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1951117Z     return mod(*inputs)
2025-09-07T08:15:13.1951387Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1951718Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1952040Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1952334Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1952602Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1952921Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1953065Z 
2025-09-07T08:15:13.1953161Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1953512Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1953822Z     return mod(*inputs)
2025-09-07T08:15:13.1954095Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1954422Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1954742Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.1955034Z     s2 = self.down1(s1)
2025-09-07T08:15:13.1955295Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1955975Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1956120Z 
2025-09-07T08:15:13.1956219Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1956563Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1956875Z     return mod(*inputs)
2025-09-07T08:15:13.1957146Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1957469Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1957789Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1958080Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1958339Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.1958638Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.1958739Z 
2025-09-07T08:15:13.1958842Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1959182Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1959504Z     return mod(*inputs)
2025-09-07T08:15:13.1959778Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1960169Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1960496Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1960798Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1961063Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1961384Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1961528Z 
2025-09-07T08:15:13.1961625Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1961969Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1962286Z     return mod(*inputs)
2025-09-07T08:15:13.1962563Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1962889Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1963212Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1963507Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1963768Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1964089Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1964232Z 
2025-09-07T08:15:13.1964328Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1964674Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1964980Z     return mod(*inputs)
2025-09-07T08:15:13.1965249Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1965581Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1965895Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.1966188Z     s3 = self.down2(s2)
2025-09-07T08:15:13.1966457Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1966778Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1966918Z 
2025-09-07T08:15:13.1967016Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1967358Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1967667Z     return mod(*inputs)
2025-09-07T08:15:13.1967935Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1968266Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1968667Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1968983Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1969248Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.1969539Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.1969639Z 
2025-09-07T08:15:13.1969741Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1970076Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1970386Z     return mod(*inputs)
2025-09-07T08:15:13.1970655Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1970979Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1971299Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1971590Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1971854Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1972181Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1972325Z 
2025-09-07T08:15:13.1972422Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1972831Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1973143Z     return mod(*inputs)
2025-09-07T08:15:13.1973415Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1973740Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1974062Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1974356Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1974623Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1974945Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1975089Z 
2025-09-07T08:15:13.1975189Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1975530Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1975841Z     return mod(*inputs)
2025-09-07T08:15:13.1976115Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1976440Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1976759Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.1977052Z     s4 = self.down3(s3)
2025-09-07T08:15:13.1977313Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1977633Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1977778Z 
2025-09-07T08:15:13.1977876Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1978232Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1978541Z     return mod(*inputs)
2025-09-07T08:15:13.1978815Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1979146Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1979466Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1979757Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1980021Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.1980320Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.1980417Z 
2025-09-07T08:15:13.1980516Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1980867Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1981254Z     return mod(*inputs)
2025-09-07T08:15:13.1981534Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1981869Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1982196Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1982493Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1982757Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1983080Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1983224Z 
2025-09-07T08:15:13.1983325Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1983675Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1983984Z     return mod(*inputs)
2025-09-07T08:15:13.1984260Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1984588Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1984909Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1985201Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1985463Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1985881Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1986026Z 
2025-09-07T08:15:13.1986122Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1986469Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1986781Z     return mod(*inputs)
2025-09-07T08:15:13.1987055Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1987384Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1987705Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.1988004Z     s5 = self.down4(s4)
2025-09-07T08:15:13.1988271Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1988594Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1988737Z 
2025-09-07T08:15:13.1988840Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1989183Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1989496Z     return mod(*inputs)
2025-09-07T08:15:13.1989763Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1990092Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1990414Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1990710Z     x = self.down5(s5)
2025-09-07T08:15:13.1990987Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.1991289Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.1991388Z 
2025-09-07T08:15:13.1991489Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1991834Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1992153Z     return mod(*inputs)
2025-09-07T08:15:13.1992431Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1992759Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1993084Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1993376Z     x = self.down5(s5)
2025-09-07T08:15:13.1993643Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1993969Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1994187Z 
2025-09-07T08:15:13.1994288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1994632Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1994949Z     return mod(*inputs)
2025-09-07T08:15:13.1995228Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1995556Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1995878Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1996179Z     x = self.down5(s5)
2025-09-07T08:15:13.1996450Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.1996778Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.1996922Z 
2025-09-07T08:15:13.1997018Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.1997371Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.1997686Z     return mod(*inputs)
2025-09-07T08:15:13.1997965Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.1998298Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.1998690Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.1999140Z     x = self.down5(s5)
2025-09-07T08:15:13.1999410Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.1999739Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.1999884Z 
2025-09-07T08:15:13.1999989Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2000342Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2000662Z     return mod(*inputs)
2025-09-07T08:15:13.2000942Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2001029Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2001212Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2001269Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2001454Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2001538Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2001542Z 
2025-09-07T08:15:13.2001640Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2001838Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2001897Z     return mod(*inputs)
2025-09-07T08:15:13.2002085Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2002173Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2002350Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2002414Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2002587Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2002677Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2002680Z 
2025-09-07T08:15:13.2002774Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2002975Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2003032Z     return mod(*inputs)
2025-09-07T08:15:13.2003211Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2003301Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2003476Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.2003677Z     s5 = self.down4(s4)
2025-09-07T08:15:13.2003853Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2003935Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2003938Z 
2025-09-07T08:15:13.2004042Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2004246Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2004309Z     return mod(*inputs)
2025-09-07T08:15:13.2004484Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2004569Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2004750Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2004806Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2004984Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2005117Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2005121Z 
2025-09-07T08:15:13.2005202Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2005297Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2005581Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2005647Z     return mod(*inputs)
2025-09-07T08:15:13.2005826Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2005915Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2006088Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2006146Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2006322Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2006454Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2006457Z 
2025-09-07T08:15:13.2006557Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2006751Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2006810Z     return mod(*inputs)
2025-09-07T08:15:13.2006994Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2007075Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2007251Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2007309Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2007483Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2007569Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2007575Z 
2025-09-07T08:15:13.2007668Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2007862Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2007918Z     return mod(*inputs)
2025-09-07T08:15:13.2008102Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2008189Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2008367Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2008429Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2008601Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2008689Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2008692Z 
2025-09-07T08:15:13.2008785Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2008974Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2009114Z     return mod(*inputs)
2025-09-07T08:15:13.2009290Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2009381Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2009555Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.2009613Z     s4 = self.down3(s3)
2025-09-07T08:15:13.2009792Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2009877Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2009881Z 
2025-09-07T08:15:13.2009978Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2010166Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2010223Z     return mod(*inputs)
2025-09-07T08:15:13.2010409Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2010496Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2010674Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2010731Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2010972Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2011105Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2011108Z 
2025-09-07T08:15:13.2011182Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2011278Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2011470Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2011531Z     return mod(*inputs)
2025-09-07T08:15:13.2011710Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2011801Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2011977Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2012039Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2012215Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2012341Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2012344Z 
2025-09-07T08:15:13.2012437Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2012630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2012689Z     return mod(*inputs)
2025-09-07T08:15:13.2012872Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2012958Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2013132Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2013194Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2013366Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2013455Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2013460Z 
2025-09-07T08:15:13.2013550Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2013746Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2013803Z     return mod(*inputs)
2025-09-07T08:15:13.2013976Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2014066Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2014240Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2014372Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2014544Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2014626Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2014630Z 
2025-09-07T08:15:13.2014728Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2014919Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2014982Z     return mod(*inputs)
2025-09-07T08:15:13.2015158Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2015240Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2015419Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.2015476Z     s3 = self.down2(s2)
2025-09-07T08:15:13.2015655Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2015743Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2015746Z 
2025-09-07T08:15:13.2015835Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2016032Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2016090Z     return mod(*inputs)
2025-09-07T08:15:13.2016335Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2016419Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2016597Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2016655Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2016828Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2016957Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2016960Z 
2025-09-07T08:15:13.2017035Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2017133Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2017320Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2017377Z     return mod(*inputs)
2025-09-07T08:15:13.2017557Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2017641Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2017816Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2017874Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2018047Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2018173Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2018176Z 
2025-09-07T08:15:13.2018267Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2018467Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2018526Z     return mod(*inputs)
2025-09-07T08:15:13.2018703Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2018792Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2018963Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2019025Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2019196Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2019281Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2019284Z 
2025-09-07T08:15:13.2019377Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2019566Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2019690Z     return mod(*inputs)
2025-09-07T08:15:13.2019869Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2019955Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2020129Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2020188Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2020363Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2020444Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2020447Z 
2025-09-07T08:15:13.2020543Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2020734Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2020790Z     return mod(*inputs)
2025-09-07T08:15:13.2020970Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2021059Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2021234Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.2021291Z     s2 = self.down1(s1)
2025-09-07T08:15:13.2021542Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2021631Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2021635Z 
2025-09-07T08:15:13.2021726Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2021916Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2021976Z     return mod(*inputs)
2025-09-07T08:15:13.2022156Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2022240Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2022417Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2022481Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2022652Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2022784Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2022790Z 
2025-09-07T08:15:13.2022861Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2022951Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2023147Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2023205Z     return mod(*inputs)
2025-09-07T08:15:13.2023387Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2023470Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2023661Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2023726Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2023892Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2024021Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2024024Z 
2025-09-07T08:15:13.2024120Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2024319Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2024374Z     return mod(*inputs)
2025-09-07T08:15:13.2024566Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2024657Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2024826Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2024888Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2025060Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2025211Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2025214Z 
2025-09-07T08:15:13.2025310Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2025499Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2025647Z     return mod(*inputs)
2025-09-07T08:15:13.2025829Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2025911Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2026085Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2026144Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2026324Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2026406Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2026412Z 
2025-09-07T08:15:13.2026507Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2026703Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2026761Z     return mod(*inputs)
2025-09-07T08:15:13.2027008Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2027093Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2027270Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.2027373Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2027376Z 
2025-09-07T08:15:13.2027470Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2027667Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2027726Z     return mod(*inputs)
2025-09-07T08:15:13.2027916Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2028000Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2028176Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2028242Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2028425Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2028558Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2028561Z 
2025-09-07T08:15:13.2028634Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2028725Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2028918Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2028976Z     return mod(*inputs)
2025-09-07T08:15:13.2029161Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2029249Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2029420Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2029495Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2029671Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2029803Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2029806Z 
2025-09-07T08:15:13.2029897Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2030093Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2030151Z     return mod(*inputs)
2025-09-07T08:15:13.2030329Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2030415Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2030662Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2030723Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2030900Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2031032Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2031035Z 
2025-09-07T08:15:13.2031136Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2031331Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2031391Z     return mod(*inputs)
2025-09-07T08:15:13.2031574Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T08:15:13.2031663Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T08:15:13.2031843Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T08:15:13.2031930Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T08:15:13.2031932Z 
2025-09-07T08:15:13.2032028Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2032225Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2032290Z     return mod(*inputs)
2025-09-07T08:15:13.2032527Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 45, in forward
2025-09-07T08:15:13.2032613Z     g_I1_F_t_1 = self.trainFlowBackWarp(I1, F_t_1)
2025-09-07T08:15:13.2032791Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T08:15:13.2032861Z     grid = torch.stack((x, y), dim=3)
2025-09-07T08:15:13.2032864Z 
2025-09-07T08:15:13.2032965Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2033155Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2033218Z     return mod(*inputs)
2025-09-07T08:15:13.2033398Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 44, in forward
2025-09-07T08:15:13.2033478Z     g_I0_F_t_0 = self.trainFlowBackWarp(I0, F_t_0)
2025-09-07T08:15:13.2033656Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T08:15:13.2033725Z     grid = torch.stack((x, y), dim=3)
2025-09-07T08:15:13.2033728Z 
2025-09-07T08:15:13.2033818Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2034016Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2034072Z     return mod(*inputs)
2025-09-07T08:15:13.2034254Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 49, in forward
2025-09-07T08:15:13.2034309Z     torch.cat(
2025-09-07T08:15:13.2034313Z 
2025-09-07T08:15:13.2034413Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2034610Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2034669Z     return mod(*inputs)
2025-09-07T08:15:13.2034847Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 49, in forward
2025-09-07T08:15:13.2034901Z     torch.cat(
2025-09-07T08:15:13.2034904Z 
2025-09-07T08:15:13.2034980Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2035052Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2035146Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2035361Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2035417Z     return mod(*inputs)
2025-09-07T08:15:13.2035599Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 49, in forward
2025-09-07T08:15:13.2035651Z     torch.cat(
2025-09-07T08:15:13.2035653Z 
2025-09-07T08:15:13.2035744Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2036024Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2036088Z     return mod(*inputs)
2025-09-07T08:15:13.2036271Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2036346Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2036525Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.2036615Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2036618Z 
2025-09-07T08:15:13.2036707Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2036901Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2036961Z     return mod(*inputs)
2025-09-07T08:15:13.2037139Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2037230Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2037402Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.2037491Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2037494Z 
2025-09-07T08:15:13.2037591Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2037854Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2037915Z     return mod(*inputs)
2025-09-07T08:15:13.2038096Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2038197Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2038374Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T08:15:13.2038467Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2038471Z 
2025-09-07T08:15:13.2038569Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2038763Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2038840Z     return mod(*inputs)
2025-09-07T08:15:13.2039019Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2039094Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2039270Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.2039362Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2039365Z 
2025-09-07T08:15:13.2039462Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2039651Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2039710Z     return mod(*inputs)
2025-09-07T08:15:13.2039893Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2039971Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2040152Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.2040207Z     s2 = self.down1(s1)
2025-09-07T08:15:13.2040389Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.2040452Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.2040455Z 
2025-09-07T08:15:13.2040555Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2040768Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2040832Z     return mod(*inputs)
2025-09-07T08:15:13.2041021Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2041092Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2041267Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.2041386Z     s2 = self.down1(s1)
2025-09-07T08:15:13.2041560Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2041650Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2041654Z 
2025-09-07T08:15:13.2041746Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2041945Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2042016Z     return mod(*inputs)
2025-09-07T08:15:13.2042201Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2042275Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2042448Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.2042509Z     s2 = self.down1(s1)
2025-09-07T08:15:13.2042682Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2042768Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2042771Z 
2025-09-07T08:15:13.2042865Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2043070Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2043135Z     return mod(*inputs)
2025-09-07T08:15:13.2043426Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2043498Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2043678Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.2043736Z     s2 = self.down1(s1)
2025-09-07T08:15:13.2043928Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2044020Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2044022Z 
2025-09-07T08:15:13.2044122Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2044318Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2044377Z     return mod(*inputs)
2025-09-07T08:15:13.2044557Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2044626Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2044810Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.2044866Z     s3 = self.down2(s2)
2025-09-07T08:15:13.2045056Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.2045124Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.2045127Z 
2025-09-07T08:15:13.2045222Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2045434Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2045494Z     return mod(*inputs)
2025-09-07T08:15:13.2045683Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2045759Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2045934Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.2045997Z     s3 = self.down2(s2)
2025-09-07T08:15:13.2046168Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2046259Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2046262Z 
2025-09-07T08:15:13.2046362Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2046553Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2046612Z     return mod(*inputs)
2025-09-07T08:15:13.2046790Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2046861Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2047117Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.2047175Z     s3 = self.down2(s2)
2025-09-07T08:15:13.2047351Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2047436Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2047439Z 
2025-09-07T08:15:13.2047539Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2047724Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2047781Z     return mod(*inputs)
2025-09-07T08:15:13.2047973Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2048044Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2048220Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.2048281Z     s3 = self.down2(s2)
2025-09-07T08:15:13.2048458Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2048545Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2048548Z 
2025-09-07T08:15:13.2048641Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2048903Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2048970Z     return mod(*inputs)
2025-09-07T08:15:13.2049156Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2049231Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2049406Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.2049468Z     s4 = self.down3(s3)
2025-09-07T08:15:13.2049639Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.2049719Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.2049728Z 
2025-09-07T08:15:13.2049821Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2050010Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2050073Z     return mod(*inputs)
2025-09-07T08:15:13.2050253Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2050328Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2050501Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.2050559Z     s4 = self.down3(s3)
2025-09-07T08:15:13.2050732Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2050815Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2050818Z 
2025-09-07T08:15:13.2050924Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2051119Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2051175Z     return mod(*inputs)
2025-09-07T08:15:13.2051354Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2051424Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2051619Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.2051677Z     s4 = self.down3(s3)
2025-09-07T08:15:13.2051852Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2051942Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2051945Z 
2025-09-07T08:15:13.2052037Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2052234Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2052291Z     return mod(*inputs)
2025-09-07T08:15:13.2052537Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2052620Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2052800Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.2052861Z     s4 = self.down3(s3)
2025-09-07T08:15:13.2053035Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2053121Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2053129Z 
2025-09-07T08:15:13.2053219Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2053410Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2053480Z     return mod(*inputs)
2025-09-07T08:15:13.2053662Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2053734Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2053911Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.2053968Z     s5 = self.down4(s4)
2025-09-07T08:15:13.2054141Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.2054201Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.2054265Z 
2025-09-07T08:15:13.2054364Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2054552Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2054616Z     return mod(*inputs)
2025-09-07T08:15:13.2054808Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2054876Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2055055Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.2055113Z     s5 = self.down4(s4)
2025-09-07T08:15:13.2055287Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2055375Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2055378Z 
2025-09-07T08:15:13.2055468Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2055662Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2055733Z     return mod(*inputs)
2025-09-07T08:15:13.2055913Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2055984Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2056157Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.2056218Z     s5 = self.down4(s4)
2025-09-07T08:15:13.2056392Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2056481Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2056487Z 
2025-09-07T08:15:13.2056581Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2056772Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2056836Z     return mod(*inputs)
2025-09-07T08:15:13.2057018Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2057093Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2057269Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.2057327Z     s5 = self.down4(s4)
2025-09-07T08:15:13.2057502Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2057587Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2057590Z 
2025-09-07T08:15:13.2057685Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2057942Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2057998Z     return mod(*inputs)
2025-09-07T08:15:13.2058188Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2058255Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2058433Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.2058490Z     x = self.down5(s5)
2025-09-07T08:15:13.2058661Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T08:15:13.2058726Z     x = F.avg_pool2d(x, 2)
2025-09-07T08:15:13.2058729Z 
2025-09-07T08:15:13.2058820Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2059015Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2059071Z     return mod(*inputs)
2025-09-07T08:15:13.2059258Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2059335Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2059508Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.2059569Z     x = self.down5(s5)
2025-09-07T08:15:13.2059839Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2059928Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2059930Z 
2025-09-07T08:15:13.2060025Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2060217Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2060283Z     return mod(*inputs)
2025-09-07T08:15:13.2060458Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2060529Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2060704Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.2060765Z     x = self.down5(s5)
2025-09-07T08:15:13.2060941Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T08:15:13.2061023Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2061029Z 
2025-09-07T08:15:13.2061123Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2061313Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2061370Z     return mod(*inputs)
2025-09-07T08:15:13.2061550Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2061617Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2061791Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T08:15:13.2061847Z     x = self.down5(s5)
2025-09-07T08:15:13.2062022Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2062112Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2062114Z 
2025-09-07T08:15:13.2062205Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2062403Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2062461Z     return mod(*inputs)
2025-09-07T08:15:13.2062642Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2062712Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2062880Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2062943Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2063116Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2063282Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2063284Z 
2025-09-07T08:15:13.2063376Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2063564Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2063623Z     return mod(*inputs)
2025-09-07T08:15:13.2063805Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2063878Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2064053Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2064110Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2064292Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2064377Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2064380Z 
2025-09-07T08:15:13.2064479Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2064672Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2064728Z     return mod(*inputs)
2025-09-07T08:15:13.2064913Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2064982Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2065219Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T08:15:13.2065278Z     s5 = self.down4(s4)
2025-09-07T08:15:13.2065450Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2065609Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2065612Z 
2025-09-07T08:15:13.2065715Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2065919Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2065975Z     return mod(*inputs)
2025-09-07T08:15:13.2066171Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2066244Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2066419Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2066481Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2066657Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2066795Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2066798Z 
2025-09-07T08:15:13.2066872Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2066968Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2067165Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2067222Z     return mod(*inputs)
2025-09-07T08:15:13.2067410Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2067485Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2067659Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T08:15:13.2067724Z     x = self.up1(x, s5)
2025-09-07T08:15:13.2067902Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2068037Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2068040Z 
2025-09-07T08:15:13.2068134Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2068332Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2068392Z     return mod(*inputs)
2025-09-07T08:15:13.2068571Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2068649Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2068892Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2068957Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2069132Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2069216Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2069222Z 
2025-09-07T08:15:13.2069317Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2069505Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2069569Z     return mod(*inputs)
2025-09-07T08:15:13.2069745Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2069820Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2069997Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2070053Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2070232Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2070315Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2070318Z 
2025-09-07T08:15:13.2070411Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2070669Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2070729Z     return mod(*inputs)
2025-09-07T08:15:13.2070920Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2070996Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2071170Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T08:15:13.2071238Z     s4 = self.down3(s3)
2025-09-07T08:15:13.2071414Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2071506Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2071513Z 
2025-09-07T08:15:13.2071608Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2071811Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2071872Z     return mod(*inputs)
2025-09-07T08:15:13.2072055Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2072135Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2072306Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2072369Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2072543Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2072676Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2072678Z 
2025-09-07T08:15:13.2072761Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2072857Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2073059Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2073117Z     return mod(*inputs)
2025-09-07T08:15:13.2073300Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2073382Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2073555Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T08:15:13.2073620Z     x = self.up2(x, s4)
2025-09-07T08:15:13.2073794Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2073923Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2073926Z 
2025-09-07T08:15:13.2074024Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2080884Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2081058Z     return mod(*inputs)
2025-09-07T08:15:13.2081273Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2081356Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2081555Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2081627Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2081814Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2081915Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2081920Z 
2025-09-07T08:15:13.2082024Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2082229Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2082298Z     return mod(*inputs)
2025-09-07T08:15:13.2082486Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2082569Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2082749Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2082809Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2083058Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2083151Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2083155Z 
2025-09-07T08:15:13.2083255Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2083454Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2083513Z     return mod(*inputs)
2025-09-07T08:15:13.2083701Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2083774Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2083958Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T08:15:13.2084019Z     s3 = self.down2(s2)
2025-09-07T08:15:13.2084200Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2084288Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2084291Z 
2025-09-07T08:15:13.2084392Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2084590Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2084650Z     return mod(*inputs)
2025-09-07T08:15:13.2084833Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2084904Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2085079Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2085142Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2085318Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2085455Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2085458Z 
2025-09-07T08:15:13.2085536Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2085635Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2085837Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2085898Z     return mod(*inputs)
2025-09-07T08:15:13.2086082Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2086153Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2086327Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T08:15:13.2086393Z     x = self.up3(x, s3)
2025-09-07T08:15:13.2086568Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2086772Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2086775Z 
2025-09-07T08:15:13.2086868Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2087068Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2087130Z     return mod(*inputs)
2025-09-07T08:15:13.2087309Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2087386Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2087555Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2087623Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2087797Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2087884Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2087889Z 
2025-09-07T08:15:13.2087987Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2088182Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2088247Z     return mod(*inputs)
2025-09-07T08:15:13.2088492Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2088566Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2088740Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2088797Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2088974Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2089059Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2089063Z 
2025-09-07T08:15:13.2089157Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2089353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2089415Z     return mod(*inputs)
2025-09-07T08:15:13.2089596Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2089667Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2089844Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T08:15:13.2089908Z     s2 = self.down1(s1)
2025-09-07T08:15:13.2090083Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T08:15:13.2090174Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2090177Z 
2025-09-07T08:15:13.2090267Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2090465Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2090531Z     return mod(*inputs)
2025-09-07T08:15:13.2090712Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2090787Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2090963Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2091024Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2091199Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2091327Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2091331Z 
2025-09-07T08:15:13.2091409Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2091500Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2091694Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2091752Z     return mod(*inputs)
2025-09-07T08:15:13.2091933Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2092088Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2092263Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T08:15:13.2092325Z     x = self.up4(x, s2)
2025-09-07T08:15:13.2092493Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2092626Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2092636Z 
2025-09-07T08:15:13.2092730Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2092922Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2092985Z     return mod(*inputs)
2025-09-07T08:15:13.2093166Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2093241Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2093418Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2093480Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2093655Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2093740Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2093742Z 
2025-09-07T08:15:13.2093899Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2094093Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2094151Z     return mod(*inputs)
2025-09-07T08:15:13.2094337Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2094409Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2094587Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2094647Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2094820Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T08:15:13.2094915Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T08:15:13.2094918Z 
2025-09-07T08:15:13.2095009Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2095204Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2095267Z     return mod(*inputs)
2025-09-07T08:15:13.2095445Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2095521Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2095694Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T08:15:13.2095793Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T08:15:13.2095796Z 
2025-09-07T08:15:13.2095891Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2096090Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2096152Z     return mod(*inputs)
2025-09-07T08:15:13.2096331Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2096409Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2096583Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2096651Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2096825Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2096952Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2096955Z 
2025-09-07T08:15:13.2097032Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2097123Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2097320Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2097380Z     return mod(*inputs)
2025-09-07T08:15:13.2097633Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2097710Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2097888Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2097953Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2098127Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2098256Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2098262Z 
2025-09-07T08:15:13.2098355Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2098547Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2098612Z     return mod(*inputs)
2025-09-07T08:15:13.2099012Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2099089Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2099260Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T08:15:13.2099321Z     x = self.up5(x, s1)
2025-09-07T08:15:13.2099496Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T08:15:13.2099733Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T08:15:13.2099737Z 
2025-09-07T08:15:13.2099834Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2100026Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2100084Z     return mod(*inputs)
2025-09-07T08:15:13.2100269Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T08:15:13.2100336Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T08:15:13.2100511Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T08:15:13.2100602Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T08:15:13.2100605Z 
2025-09-07T08:15:13.2100696Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2100891Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2100955Z     return mod(*inputs)
2025-09-07T08:15:13.2101134Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 57, in forward
2025-09-07T08:15:13.2101212Z     V_t_0 = F.sigmoid(intrpOut[:, 4:5, :, :])
2025-09-07T08:15:13.2101215Z 
2025-09-07T08:15:13.2101313Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2101507Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2101570Z     return mod(*inputs)
2025-09-07T08:15:13.2101752Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 61, in forward
2025-09-07T08:15:13.2101845Z     g_I0_F_t_0_f = self.trainFlowBackWarp(I0, F_t_0_f)
2025-09-07T08:15:13.2102024Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T08:15:13.2102089Z     grid = torch.stack((x, y), dim=3)
2025-09-07T08:15:13.2102091Z 
2025-09-07T08:15:13.2102182Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2102376Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2102443Z     return mod(*inputs)
2025-09-07T08:15:13.2102620Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 62, in forward
2025-09-07T08:15:13.2102708Z     g_I1_F_t_1_f = self.trainFlowBackWarp(I1, F_t_1_f)
2025-09-07T08:15:13.2102886Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T08:15:13.2102953Z     grid = torch.stack((x, y), dim=3)
2025-09-07T08:15:13.2102956Z 
2025-09-07T08:15:13.2103150Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2103343Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2103409Z     return mod(*inputs)
2025-09-07T08:15:13.2103593Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2103741Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2103744Z 
2025-09-07T08:15:13.2103843Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2104034Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2104095Z     return mod(*inputs)
2025-09-07T08:15:13.2104274Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2104413Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2104422Z 
2025-09-07T08:15:13.2104518Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2104710Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2104771Z     return mod(*inputs)
2025-09-07T08:15:13.2104947Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2105152Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2105155Z 
2025-09-07T08:15:13.2105248Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2105438Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2105500Z     return mod(*inputs)
2025-09-07T08:15:13.2105738Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2105877Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2105884Z 
2025-09-07T08:15:13.2105973Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2106165Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2106229Z     return mod(*inputs)
2025-09-07T08:15:13.2106408Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2106543Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2106546Z 
2025-09-07T08:15:13.2106639Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2106829Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2106885Z     return mod(*inputs)
2025-09-07T08:15:13.2107060Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2107194Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2107200Z 
2025-09-07T08:15:13.2107294Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2107484Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2107540Z     return mod(*inputs)
2025-09-07T08:15:13.2107717Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2107856Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2107860Z 
2025-09-07T08:15:13.2107950Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2108147Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2108205Z     return mod(*inputs)
2025-09-07T08:15:13.2108386Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2108513Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2108582Z 
2025-09-07T08:15:13.2108688Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2108878Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2108934Z     return mod(*inputs)
2025-09-07T08:15:13.2109114Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2109246Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2109250Z 
2025-09-07T08:15:13.2109338Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2109529Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2109588Z     return mod(*inputs)
2025-09-07T08:15:13.2109770Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2109902Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2109907Z 
2025-09-07T08:15:13.2110001Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2110188Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2110248Z     return mod(*inputs)
2025-09-07T08:15:13.2110502Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2110633Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2110636Z 
2025-09-07T08:15:13.2110735Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2110925Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2110980Z     return mod(*inputs)
2025-09-07T08:15:13.2111161Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2111296Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2111299Z 
2025-09-07T08:15:13.2111398Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2111586Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2111644Z     return mod(*inputs)
2025-09-07T08:15:13.2111830Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2111962Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2111965Z 
2025-09-07T08:15:13.2112062Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2112249Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2112309Z     return mod(*inputs)
2025-09-07T08:15:13.2112488Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2112624Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2112627Z 
2025-09-07T08:15:13.2112722Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2112904Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2112966Z     return mod(*inputs)
2025-09-07T08:15:13.2113146Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2113276Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2113284Z 
2025-09-07T08:15:13.2113377Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2113564Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2113626Z     return mod(*inputs)
2025-09-07T08:15:13.2113805Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2114008Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2114010Z 
2025-09-07T08:15:13.2114101Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2114297Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2114363Z     return mod(*inputs)
2025-09-07T08:15:13.2114542Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2114676Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2114679Z 
2025-09-07T08:15:13.2114773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2114957Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2115019Z     return mod(*inputs)
2025-09-07T08:15:13.2115194Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2115334Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2115336Z 
2025-09-07T08:15:13.2115426Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2115617Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2115739Z     return mod(*inputs)
2025-09-07T08:15:13.2115922Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2116059Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2116062Z 
2025-09-07T08:15:13.2116159Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2116353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2116412Z     return mod(*inputs)
2025-09-07T08:15:13.2116588Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2116725Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2116728Z 
2025-09-07T08:15:13.2116820Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2117007Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2117065Z     return mod(*inputs)
2025-09-07T08:15:13.2117242Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2117372Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2117375Z 
2025-09-07T08:15:13.2117465Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2117657Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2117715Z     return mod(*inputs)
2025-09-07T08:15:13.2117898Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2118035Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2118038Z 
2025-09-07T08:15:13.2118132Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2118333Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2118392Z     return mod(*inputs)
2025-09-07T08:15:13.2118576Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2118709Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2118712Z 
2025-09-07T08:15:13.2118811Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2119001Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2119059Z     return mod(*inputs)
2025-09-07T08:15:13.2119310Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2119440Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2119443Z 
2025-09-07T08:15:13.2119539Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2119733Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2119790Z     return mod(*inputs)
2025-09-07T08:15:13.2119968Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2120101Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2120104Z 
2025-09-07T08:15:13.2120199Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2120388Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2120446Z     return mod(*inputs)
2025-09-07T08:15:13.2120633Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2120765Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2120767Z 
2025-09-07T08:15:13.2120850Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2121004Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2121201Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2121258Z     return mod(*inputs)
2025-09-07T08:15:13.2121439Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 79, in forward
2025-09-07T08:15:13.2121535Z     + L1_lossFn(self.trainFlowBackWarp(I0, F_1_0), I1)
2025-09-07T08:15:13.2121714Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T08:15:13.2121788Z     grid = torch.stack((x, y), dim=3)
2025-09-07T08:15:13.2121795Z 
2025-09-07T08:15:13.2121869Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2121963Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2122155Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2122215Z     return mod(*inputs)
2025-09-07T08:15:13.2122395Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 80, in forward
2025-09-07T08:15:13.2122484Z     + L1_lossFn(self.trainFlowBackWarp(I1, F_0_1), I0)
2025-09-07T08:15:13.2122658Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T08:15:13.2122728Z     grid = torch.stack((x, y), dim=3)
2025-09-07T08:15:13.2122731Z 
2025-09-07T08:15:13.2122803Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2122895Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2123084Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2123145Z     return mod(*inputs)
2025-09-07T08:15:13.2123325Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2123457Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2123460Z 
2025-09-07T08:15:13.2123556Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2123745Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2123805Z     return mod(*inputs)
2025-09-07T08:15:13.2123985Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2124116Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2124118Z 
2025-09-07T08:15:13.2124212Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2124400Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2124521Z     return mod(*inputs)
2025-09-07T08:15:13.2124698Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2124831Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2124836Z 
2025-09-07T08:15:13.2124929Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2125116Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2125176Z     return mod(*inputs)
2025-09-07T08:15:13.2125355Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2125494Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2125497Z 
2025-09-07T08:15:13.2125588Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2125772Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2125834Z     return mod(*inputs)
2025-09-07T08:15:13.2126013Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2126149Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2126152Z 
2025-09-07T08:15:13.2126524Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2126717Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2126780Z     return mod(*inputs)
2025-09-07T08:15:13.2126956Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2127090Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2127093Z 
2025-09-07T08:15:13.2127185Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2127378Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2127439Z     return mod(*inputs)
2025-09-07T08:15:13.2127616Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2127749Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2127754Z 
2025-09-07T08:15:13.2127846Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2128038Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2128096Z     return mod(*inputs)
2025-09-07T08:15:13.2128275Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2128408Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2128411Z 
2025-09-07T08:15:13.2128502Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2128694Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2128751Z     return mod(*inputs)
2025-09-07T08:15:13.2128930Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2129064Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2129067Z 
2025-09-07T08:15:13.2129158Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2129360Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2129418Z     return mod(*inputs)
2025-09-07T08:15:13.2129601Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2129729Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2129732Z 
2025-09-07T08:15:13.2129821Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2130083Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2130142Z     return mod(*inputs)
2025-09-07T08:15:13.2130321Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2130458Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2130462Z 
2025-09-07T08:15:13.2130557Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2130748Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2130805Z     return mod(*inputs)
2025-09-07T08:15:13.2130980Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T08:15:13.2131109Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T08:15:13.2131112Z 
2025-09-07T08:15:13.2131186Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2131258Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2131327Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2131399Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2131468Z cudagraph partition due to non gpu ops
2025-09-07T08:15:13.2131561Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:15:13.2131825Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:15:13.2131884Z     return mod(*inputs)
2025-09-07T08:15:13.2132067Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 94, in forward
2025-09-07T08:15:13.2132186Z     loss = 204 * recnLoss + 102 * warpLoss + 0.005 * prcpLoss + loss_smooth
2025-09-07T08:15:13.2132190Z 
2025-09-07T08:16:04.0641260Z pass
2025-09-07T08:16:04.0642844Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:07.0868445Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:16:07.0869361Z   import pynvml  # type: ignore[import]
2025-09-07T08:16:09.0930161Z 
2025-09-07T08:16:09.8008450Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:16:09.8008765Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:16:09.8045867Z cpu  eval  alexnet                            
2025-09-07T08:16:09.9583786Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:09.9775825Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:09.9888703Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:12.2807826Z cudagraph partition due to non gpu ops
2025-09-07T08:16:12.2808154Z cudagraph partition due to non gpu ops
2025-09-07T08:16:12.2808381Z cudagraph partition due to non gpu ops
2025-09-07T08:16:12.2808594Z cudagraph partition due to non gpu ops
2025-09-07T08:16:12.2808791Z cudagraph partition due to non gpu ops
2025-09-07T08:16:12.2808993Z cudagraph partition due to non gpu ops
2025-09-07T08:16:12.2809249Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2809635Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2809977Z     return mod(*inputs)
2025-09-07T08:16:12.2810335Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2810724Z     x = self.features(x)
2025-09-07T08:16:12.2810836Z 
2025-09-07T08:16:12.2810942Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2811319Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2812082Z     return mod(*inputs)
2025-09-07T08:16:12.2812414Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2812776Z     x = self.features(x)
2025-09-07T08:16:12.2812880Z 
2025-09-07T08:16:12.2812990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2813364Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2813694Z     return mod(*inputs)
2025-09-07T08:16:12.2814025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2814384Z     x = self.features(x)
2025-09-07T08:16:12.2814489Z 
2025-09-07T08:16:12.2814619Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2814992Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2815321Z     return mod(*inputs)
2025-09-07T08:16:12.2815647Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2815997Z     x = self.features(x)
2025-09-07T08:16:12.2816108Z 
2025-09-07T08:16:12.2816207Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2816748Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2817075Z     return mod(*inputs)
2025-09-07T08:16:12.2817399Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2817744Z     x = self.features(x)
2025-09-07T08:16:12.2817848Z 
2025-09-07T08:16:12.2817954Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2818307Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2818626Z     return mod(*inputs)
2025-09-07T08:16:12.2818947Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2819299Z     x = self.features(x)
2025-09-07T08:16:12.2819394Z 
2025-09-07T08:16:12.2819505Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2819873Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2820194Z     return mod(*inputs)
2025-09-07T08:16:12.2820522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2820875Z     x = self.features(x)
2025-09-07T08:16:12.2820975Z 
2025-09-07T08:16:12.2821080Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2821428Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2821745Z     return mod(*inputs)
2025-09-07T08:16:12.2822063Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2822421Z     x = self.features(x)
2025-09-07T08:16:12.2822526Z 
2025-09-07T08:16:12.2822633Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2822988Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2823311Z     return mod(*inputs)
2025-09-07T08:16:12.2823640Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2823987Z     x = self.features(x)
2025-09-07T08:16:12.2824088Z 
2025-09-07T08:16:12.2824188Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2824541Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2824867Z     return mod(*inputs)
2025-09-07T08:16:12.2825189Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T08:16:12.2825673Z     x = self.features(x)
2025-09-07T08:16:12.2825774Z 
2025-09-07T08:16:12.2825870Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2826239Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2826565Z     return mod(*inputs)
2025-09-07T08:16:12.2826897Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 49, in forward
2025-09-07T08:16:12.2827242Z     x = self.avgpool(x)
2025-09-07T08:16:12.2827342Z 
2025-09-07T08:16:12.2827439Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2827789Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2828113Z     return mod(*inputs)
2025-09-07T08:16:12.2828459Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T08:16:12.2828810Z     x = self.classifier(x)
2025-09-07T08:16:12.2828928Z 
2025-09-07T08:16:12.2829025Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2829386Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2829711Z     return mod(*inputs)
2025-09-07T08:16:12.2830102Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T08:16:12.2830471Z     x = self.classifier(x)
2025-09-07T08:16:12.2830583Z 
2025-09-07T08:16:12.2830682Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2831043Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2831368Z     return mod(*inputs)
2025-09-07T08:16:12.2831686Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T08:16:12.2832033Z     x = self.classifier(x)
2025-09-07T08:16:12.2832145Z 
2025-09-07T08:16:12.2832244Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2832604Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2832923Z     return mod(*inputs)
2025-09-07T08:16:12.2833244Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T08:16:12.2833594Z     x = self.classifier(x)
2025-09-07T08:16:12.2833698Z 
2025-09-07T08:16:12.2833800Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:12.2834151Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:12.2834468Z     return mod(*inputs)
2025-09-07T08:16:12.2834789Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T08:16:12.2835139Z     x = self.classifier(x)
2025-09-07T08:16:12.2835243Z 
2025-09-07T08:16:21.0152235Z pass
2025-09-07T08:16:21.0154035Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:23.0494510Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:16:23.0495427Z   import pynvml  # type: ignore[import]
2025-09-07T08:16:25.0543543Z 
2025-09-07T08:16:26.5643354Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:16:26.5643664Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:16:26.5652879Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T08:16:26.7315840Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:26.7835417Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:26.8366858Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:27.9857623Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9858071Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9858425Z     return mod(*inputs)
2025-09-07T08:16:27.9858850Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9859248Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9859485Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 233, in forward
2025-09-07T08:16:27.9859758Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9860039Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 192, in propagate
2025-09-07T08:16:27.9860396Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T08:16:27.9860929Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:27.9861432Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:27.9861866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:27.9862692Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:27.9863120Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward
2025-09-07T08:16:27.9863550Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='max')
2025-09-07T08:16:27.9863961Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:27.9864345Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:27.9864723Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter
2025-09-07T08:16:27.9865106Z     return src.new_zeros(size).scatter_reduce_(
2025-09-07T08:16:27.9865251Z 
2025-09-07T08:16:27.9865357Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9865769Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9866115Z     return mod(*inputs)
2025-09-07T08:16:27.9866488Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9866866Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9867111Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 233, in forward
2025-09-07T08:16:27.9867385Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9867687Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 192, in propagate
2025-09-07T08:16:27.9868035Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T08:16:27.9868557Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:27.9869027Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:27.9869453Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:27.9869878Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:27.9870287Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward
2025-09-07T08:16:27.9870693Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='max')
2025-09-07T08:16:27.9871092Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:27.9871461Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:27.9871828Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter
2025-09-07T08:16:27.9872345Z     return src.new_zeros(size).scatter_reduce_(
2025-09-07T08:16:27.9872499Z 
2025-09-07T08:16:27.9872600Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9872970Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9873300Z     return mod(*inputs)
2025-09-07T08:16:27.9873646Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9874014Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9874250Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 233, in forward
2025-09-07T08:16:27.9874510Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9874783Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 192, in propagate
2025-09-07T08:16:27.9875120Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T08:16:27.9875616Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:27.9876071Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:27.9876486Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:27.9876956Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:27.9877419Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward
2025-09-07T08:16:27.9877818Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='max')
2025-09-07T08:16:27.9878211Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:27.9878574Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:27.9878942Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter
2025-09-07T08:16:27.9879311Z     return src.new_zeros(size).scatter_reduce_(
2025-09-07T08:16:27.9879449Z 
2025-09-07T08:16:27.9879553Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9879907Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9880240Z     return mod(*inputs)
2025-09-07T08:16:27.9880580Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9880952Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9881187Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 233, in forward
2025-09-07T08:16:27.9881440Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9881703Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 191, in propagate
2025-09-07T08:16:27.9881972Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9882358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9882750Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9882910Z 
2025-09-07T08:16:27.9883009Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9883368Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9883695Z     return mod(*inputs)
2025-09-07T08:16:27.9884033Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9884397Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9884629Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 233, in forward
2025-09-07T08:16:27.9884889Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9885154Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 191, in propagate
2025-09-07T08:16:27.9885422Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9885883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9886270Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9886650Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T08:16:27.9887000Z     x = lin(x)
2025-09-07T08:16:27.9887309Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:27.9887687Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:27.9887837Z 
2025-09-07T08:16:27.9887942Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9888311Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9888635Z     return mod(*inputs)
2025-09-07T08:16:27.9888982Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9889361Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9889597Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 233, in forward
2025-09-07T08:16:27.9889857Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9890187Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 191, in propagate
2025-09-07T08:16:27.9890452Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9890838Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9891234Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9891601Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T08:16:27.9891951Z     x = self.act(x)
2025-09-07T08:16:27.9892044Z 
2025-09-07T08:16:27.9892140Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9892502Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9892832Z     return mod(*inputs)
2025-09-07T08:16:27.9893162Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9893532Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9893763Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 233, in forward
2025-09-07T08:16:27.9894017Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9894277Z   File "/tmp/jenkins_pyg/tmpz299eehb.py", line 191, in propagate
2025-09-07T08:16:27.9894532Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9894914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9895298Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9895677Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T08:16:27.9896022Z     x = self.lins[-1](x)
2025-09-07T08:16:27.9896353Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:27.9896724Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:27.9896869Z 
2025-09-07T08:16:27.9896955Z cudagraph partition due to non gpu ops
2025-09-07T08:16:27.9897180Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9897541Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9897869Z     return mod(*inputs)
2025-09-07T08:16:27.9898216Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9898592Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9898990Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 233, in forward
2025-09-07T08:16:27.9899407Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9899682Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 191, in propagate
2025-09-07T08:16:27.9899949Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9900335Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9900734Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9900895Z 
2025-09-07T08:16:27.9900996Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9901365Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9901693Z     return mod(*inputs)
2025-09-07T08:16:27.9902029Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9902399Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9902642Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 233, in forward
2025-09-07T08:16:27.9902909Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9903170Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 191, in propagate
2025-09-07T08:16:27.9903434Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9903913Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9904316Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9904697Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T08:16:27.9905039Z     x = lin(x)
2025-09-07T08:16:27.9905353Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:27.9905758Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:27.9905901Z 
2025-09-07T08:16:27.9906007Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9906358Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9906682Z     return mod(*inputs)
2025-09-07T08:16:27.9907025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9907396Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9907628Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 233, in forward
2025-09-07T08:16:27.9907881Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9908151Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 191, in propagate
2025-09-07T08:16:27.9908410Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9908792Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9909172Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9909552Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T08:16:27.9909896Z     x = self.act(x)
2025-09-07T08:16:27.9909986Z 
2025-09-07T08:16:27.9910089Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9910459Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9910775Z     return mod(*inputs)
2025-09-07T08:16:27.9911118Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9911485Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9911719Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 233, in forward
2025-09-07T08:16:27.9911971Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9912236Z   File "/tmp/jenkins_pyg/tmpaolhgyxm.py", line 191, in propagate
2025-09-07T08:16:27.9912577Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9912956Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9913341Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9913713Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T08:16:27.9914066Z     x = self.lins[-1](x)
2025-09-07T08:16:27.9914403Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:27.9914773Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:27.9914913Z 
2025-09-07T08:16:27.9914995Z cudagraph partition due to non gpu ops
2025-09-07T08:16:27.9915221Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9915575Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9915900Z     return mod(*inputs)
2025-09-07T08:16:27.9916266Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9916630Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9916864Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 233, in forward
2025-09-07T08:16:27.9917192Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9917463Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 191, in propagate
2025-09-07T08:16:27.9917722Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9918100Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9918487Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9918642Z 
2025-09-07T08:16:27.9918751Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9919114Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9919436Z     return mod(*inputs)
2025-09-07T08:16:27.9919773Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9920145Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9920376Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 233, in forward
2025-09-07T08:16:27.9920626Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9920895Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 191, in propagate
2025-09-07T08:16:27.9921152Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9921532Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9921914Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9922284Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T08:16:27.9922627Z     x = lin(x)
2025-09-07T08:16:27.9922940Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:27.9923315Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:27.9923456Z 
2025-09-07T08:16:27.9923563Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9923927Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9924256Z     return mod(*inputs)
2025-09-07T08:16:27.9924607Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9924986Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9925212Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 233, in forward
2025-09-07T08:16:27.9925469Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9925812Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 191, in propagate
2025-09-07T08:16:27.9926076Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9926454Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9926842Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9927227Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T08:16:27.9927578Z     x = self.act(x)
2025-09-07T08:16:27.9927667Z 
2025-09-07T08:16:27.9927770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:27.9928119Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:27.9928441Z     return mod(*inputs)
2025-09-07T08:16:27.9928784Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:27.9929168Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:27.9929391Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 233, in forward
2025-09-07T08:16:27.9929648Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T08:16:27.9929911Z   File "/tmp/jenkins_pyg/tmptosuby9e.py", line 191, in propagate
2025-09-07T08:16:27.9930234Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T08:16:27.9930624Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T08:16:27.9931000Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T08:16:27.9931375Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T08:16:27.9931727Z     x = self.lins[-1](x)
2025-09-07T08:16:27.9932056Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:27.9932422Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:27.9932573Z 
2025-09-07T08:16:27.9932651Z cudagraph partition due to non gpu ops
2025-09-07T08:16:33.2724078Z pass
2025-09-07T08:16:33.2724497Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:35.3679442Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:16:35.3680398Z   import pynvml  # type: ignore[import]
2025-09-07T08:16:37.3794634Z 
2025-09-07T08:16:38.8834320Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:16:38.8834619Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:16:38.8839607Z cpu  eval  basic_gnn_gcn                      
2025-09-07T08:16:38.9645390Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:39.0262939Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:39.0842877Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:40.0069679Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:40.0070265Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/loop.py", line 340, in add_remaining_self_loops
2025-09-07T08:16:40.0070693Z     mask = edge_index[0] != edge_index[1]
2025-09-07T08:16:40.0070828Z 
2025-09-07T08:16:40.0070938Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:40.0071400Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/loop.py", line 343, in add_remaining_self_loops
2025-09-07T08:16:40.0071834Z     loop_index = loop_index.unsqueeze(0).repeat(2, 1)
2025-09-07T08:16:40.0071990Z 
2025-09-07T08:16:44.3821705Z cudagraph partition due to non gpu ops
2025-09-07T08:16:44.3822526Z cudagraph partition due to non gpu ops
2025-09-07T08:16:44.3822770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.3823310Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/loop.py", line 370, in torch_dynamo_resume_in_add_remaining_self_loops_at_370
2025-09-07T08:16:44.3823855Z     edge_index = torch.cat([edge_index[:, mask], loop_index], dim=1)
2025-09-07T08:16:44.3824048Z 
2025-09-07T08:16:44.5175977Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.5176546Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91
2025-09-07T08:16:44.5177075Z     deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum')
2025-09-07T08:16:44.5177517Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T08:16:44.5177977Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:16:44.5178152Z 
2025-09-07T08:16:44.5178258Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.5178735Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 95, in torch_dynamo_resume_in_gcn_norm_at_91
2025-09-07T08:16:44.5179612Z     edge_weight = torch.ones((edge_index.size(1), ), dtype=dtype,
2025-09-07T08:16:44.5179793Z 
2025-09-07T08:16:44.5179874Z cudagraph partition due to non gpu ops
2025-09-07T08:16:44.5180111Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.5180570Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 103, in torch_dynamo_resume_in_gcn_norm_at_91
2025-09-07T08:16:44.5181055Z     edge_weight = deg_inv_sqrt[row] * edge_weight * deg_inv_sqrt[col]
2025-09-07T08:16:44.5181233Z 
2025-09-07T08:16:44.6918727Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.6919140Z    File "/tmp/jenkins_pyg/tmp67acste2.py", line 240, in torch_dynamo_resume_in_forward_at_221
2025-09-07T08:16:44.6919451Z     x = self.lin(x)
2025-09-07T08:16:44.6919817Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:44.6920211Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:44.6920373Z 
2025-09-07T08:16:44.6920487Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.6920832Z    File "/tmp/jenkins_pyg/tmp67acste2.py", line 243, in torch_dynamo_resume_in_forward_at_221
2025-09-07T08:16:44.6921224Z     out = self.propagate(edge_index, x=x, edge_weight=edge_weight,
2025-09-07T08:16:44.6921531Z   File "/tmp/jenkins_pyg/tmp67acste2.py", line 188, in propagate
2025-09-07T08:16:44.6921888Z     out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr)
2025-09-07T08:16:44.6922402Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:44.6922868Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:44.6923304Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:44.6923729Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:44.6924134Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T08:16:44.6924550Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T08:16:44.6924948Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:44.6925331Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:44.6925709Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T08:16:44.6926504Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:16:44.6926673Z 
2025-09-07T08:16:44.6926780Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.6927119Z    File "/tmp/jenkins_pyg/tmp67acste2.py", line 243, in torch_dynamo_resume_in_forward_at_221
2025-09-07T08:16:44.6927480Z     out = self.propagate(edge_index, x=x, edge_weight=edge_weight,
2025-09-07T08:16:44.6927775Z   File "/tmp/jenkins_pyg/tmp67acste2.py", line 187, in propagate
2025-09-07T08:16:44.6928070Z     out = self.message(x_j=kwargs.x_j, edge_weight=kwargs.edge_weight)
2025-09-07T08:16:44.6928492Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 241, in message
2025-09-07T08:16:44.6928928Z     return x_j if edge_weight is None else edge_weight.view(-1, 1) * x_j
2025-09-07T08:16:44.6929120Z 
2025-09-07T08:16:44.6929199Z cudagraph partition due to non gpu ops
2025-09-07T08:16:44.6929433Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:44.6929770Z    File "/tmp/jenkins_pyg/tmp67acste2.py", line 247, in torch_dynamo_resume_in_forward_at_221
2025-09-07T08:16:44.6930077Z     out = out + self.bias
2025-09-07T08:16:44.6930191Z 
2025-09-07T08:16:45.0718896Z pass
2025-09-07T08:16:45.0719334Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:47.0507409Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:16:47.0508333Z   import pynvml  # type: ignore[import]
2025-09-07T08:16:49.0579121Z 
2025-09-07T08:16:50.5423432Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:16:50.5423855Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:16:50.5429270Z cpu  eval  basic_gnn_gin                      
2025-09-07T08:16:50.6284455Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:50.6817940Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:50.7326721Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:51.8312657Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8313178Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8313548Z     return mod(*inputs)
2025-09-07T08:16:51.8313935Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8314388Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8314642Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 225, in forward
2025-09-07T08:16:51.8314914Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:16:51.8315203Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 182, in propagate
2025-09-07T08:16:51.8315561Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T08:16:51.8316088Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:51.8316559Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:51.8316985Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:51.8317394Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:51.8317803Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T08:16:51.8318216Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T08:16:51.8318629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:51.8319369Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:51.8319739Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T08:16:51.8320137Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:16:51.8320317Z 
2025-09-07T08:16:51.8320425Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8320798Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8321131Z     return mod(*inputs)
2025-09-07T08:16:51.8321472Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8321876Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8322118Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 225, in forward
2025-09-07T08:16:51.8322387Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:16:51.8322656Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 180, in propagate
2025-09-07T08:16:51.8322942Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T08:16:51.8323217Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 127, in _collect
2025-09-07T08:16:51.8323462Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T08:16:51.8323822Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 87, in _lift
2025-09-07T08:16:51.8324077Z     return src.index_select(self.node_dim, index)
2025-09-07T08:16:51.8324232Z 
2025-09-07T08:16:51.8324330Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8324716Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8325047Z     return mod(*inputs)
2025-09-07T08:16:51.8325404Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8325783Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8326029Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 225, in forward
2025-09-07T08:16:51.8326286Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:16:51.8326553Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 182, in propagate
2025-09-07T08:16:51.8326896Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T08:16:51.8327408Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:51.8327859Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:51.8328287Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:51.8328702Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:51.8329111Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T08:16:51.8329521Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T08:16:51.8329915Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:51.8330300Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:51.8330681Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T08:16:51.8331080Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:16:51.8331245Z 
2025-09-07T08:16:51.8339090Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8339528Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8339870Z     return mod(*inputs)
2025-09-07T08:16:51.8340272Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8340772Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8341014Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 225, in forward
2025-09-07T08:16:51.8341287Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:16:51.8341563Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 182, in propagate
2025-09-07T08:16:51.8341918Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T08:16:51.8342428Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:16:51.8342916Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:16:51.8343349Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:16:51.8343761Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:16:51.8344178Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T08:16:51.8344607Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T08:16:51.8345007Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:16:51.8345390Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:16:51.8345940Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T08:16:51.8346350Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:16:51.8346520Z 
2025-09-07T08:16:51.8346602Z cudagraph partition due to non gpu ops
2025-09-07T08:16:51.8346848Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8347221Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8347554Z     return mod(*inputs)
2025-09-07T08:16:51.8347903Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8348277Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8348519Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 229, in forward
2025-09-07T08:16:51.8348759Z     out = out + (1 + self.eps) * x_r
2025-09-07T08:16:51.8348879Z 
2025-09-07T08:16:51.8348990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8349348Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8349677Z     return mod(*inputs)
2025-09-07T08:16:51.8350021Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8350399Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8350628Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 231, in forward
2025-09-07T08:16:51.8350852Z     return self.nn(out)
2025-09-07T08:16:51.8351179Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T08:16:51.8351534Z     x = lin(x)
2025-09-07T08:16:51.8351851Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:51.8352217Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:51.8352368Z 
2025-09-07T08:16:51.8352465Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8352826Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8353150Z     return mod(*inputs)
2025-09-07T08:16:51.8353490Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8353863Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8354095Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 231, in forward
2025-09-07T08:16:51.8354330Z     return self.nn(out)
2025-09-07T08:16:51.8354735Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T08:16:51.8355084Z     x = self.act(x)
2025-09-07T08:16:51.8355180Z 
2025-09-07T08:16:51.8355276Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8355641Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8355969Z     return mod(*inputs)
2025-09-07T08:16:51.8356306Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8356668Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8356906Z   File "/tmp/jenkins_pyg/tmp05hyire7.py", line 231, in forward
2025-09-07T08:16:51.8357140Z     return self.nn(out)
2025-09-07T08:16:51.8357466Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T08:16:51.8357814Z     x = self.lins[-1](x)
2025-09-07T08:16:51.8358151Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:51.8358539Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:51.8358682Z 
2025-09-07T08:16:51.8358789Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8359216Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8359542Z     return mod(*inputs)
2025-09-07T08:16:51.8359887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8360264Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8360494Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 225, in forward
2025-09-07T08:16:51.8360749Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:16:51.8361016Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 180, in propagate
2025-09-07T08:16:51.8361298Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T08:16:51.8361578Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 127, in _collect
2025-09-07T08:16:51.8361813Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T08:16:51.8362044Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 87, in _lift
2025-09-07T08:16:51.8362299Z     return src.index_select(self.node_dim, index)
2025-09-07T08:16:51.8362447Z 
2025-09-07T08:16:51.8362532Z cudagraph partition due to non gpu ops
2025-09-07T08:16:51.8362763Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8363115Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8363440Z     return mod(*inputs)
2025-09-07T08:16:51.8363782Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8364157Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8364378Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 229, in forward
2025-09-07T08:16:51.8364616Z     out = out + (1 + self.eps) * x_r
2025-09-07T08:16:51.8364745Z 
2025-09-07T08:16:51.8364842Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8365198Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8365518Z     return mod(*inputs)
2025-09-07T08:16:51.8365850Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8366224Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8366449Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 231, in forward
2025-09-07T08:16:51.8366676Z     return self.nn(out)
2025-09-07T08:16:51.8366993Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T08:16:51.8367345Z     x = lin(x)
2025-09-07T08:16:51.8367662Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:51.8368117Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:51.8368256Z 
2025-09-07T08:16:51.8368353Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8368715Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8369033Z     return mod(*inputs)
2025-09-07T08:16:51.8369369Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8369736Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8369956Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 231, in forward
2025-09-07T08:16:51.8370184Z     return self.nn(out)
2025-09-07T08:16:51.8370495Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T08:16:51.8370842Z     x = self.act(x)
2025-09-07T08:16:51.8370938Z 
2025-09-07T08:16:51.8371031Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8371387Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8371701Z     return mod(*inputs)
2025-09-07T08:16:51.8372090Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8372466Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8372691Z   File "/tmp/jenkins_pyg/tmp1lyu_5sq.py", line 231, in forward
2025-09-07T08:16:51.8372919Z     return self.nn(out)
2025-09-07T08:16:51.8373228Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T08:16:51.8373579Z     x = self.lins[-1](x)
2025-09-07T08:16:51.8373905Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:51.8374273Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:51.8374412Z 
2025-09-07T08:16:51.8374508Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8374863Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8375183Z     return mod(*inputs)
2025-09-07T08:16:51.8375516Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8375880Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8376109Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 225, in forward
2025-09-07T08:16:51.8376367Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:16:51.8376627Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 180, in propagate
2025-09-07T08:16:51.8376901Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T08:16:51.8377165Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 127, in _collect
2025-09-07T08:16:51.8377404Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T08:16:51.8377630Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 87, in _lift
2025-09-07T08:16:51.8377875Z     return src.index_select(self.node_dim, index)
2025-09-07T08:16:51.8378020Z 
2025-09-07T08:16:51.8378101Z cudagraph partition due to non gpu ops
2025-09-07T08:16:51.8378320Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8378679Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8379007Z     return mod(*inputs)
2025-09-07T08:16:51.8379349Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8379714Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8379941Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 229, in forward
2025-09-07T08:16:51.8380172Z     out = out + (1 + self.eps) * x_r
2025-09-07T08:16:51.8380290Z 
2025-09-07T08:16:51.8380391Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8380811Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8381132Z     return mod(*inputs)
2025-09-07T08:16:51.8381464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8381832Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8382060Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 231, in forward
2025-09-07T08:16:51.8382280Z     return self.nn(out)
2025-09-07T08:16:51.8382604Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T08:16:51.8382944Z     x = lin(x)
2025-09-07T08:16:51.8383255Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:51.8383615Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:51.8383761Z 
2025-09-07T08:16:51.8383861Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8384212Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8384526Z     return mod(*inputs)
2025-09-07T08:16:51.8384861Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8385291Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8385597Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 231, in forward
2025-09-07T08:16:51.8385826Z     return self.nn(out)
2025-09-07T08:16:51.8386143Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T08:16:51.8386482Z     x = self.act(x)
2025-09-07T08:16:51.8386577Z 
2025-09-07T08:16:51.8386672Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:16:51.8387027Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:16:51.8387351Z     return mod(*inputs)
2025-09-07T08:16:51.8387690Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:16:51.8388059Z     x = self.convs[i](x, edge_index)
2025-09-07T08:16:51.8388286Z   File "/tmp/jenkins_pyg/tmp_9twutnc.py", line 231, in forward
2025-09-07T08:16:51.8388511Z     return self.nn(out)
2025-09-07T08:16:51.8388839Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T08:16:51.8389196Z     x = self.lins[-1](x)
2025-09-07T08:16:51.8389535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:16:51.8389910Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:16:51.8390049Z 
2025-09-07T08:16:57.2740026Z pass
2025-09-07T08:16:57.2740445Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:16:59.2556444Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:16:59.2557323Z   import pynvml  # type: ignore[import]
2025-09-07T08:17:01.2717012Z 
2025-09-07T08:17:02.7561764Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:17:02.7562049Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:17:02.7568526Z cpu  eval  basic_gnn_sage                     
2025-09-07T08:17:02.8282603Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:02.8776441Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:02.9248295Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:04.0352180Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0352657Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0353115Z     return mod(*inputs)
2025-09-07T08:17:04.0353539Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0353930Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0354189Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 228, in forward
2025-09-07T08:17:04.0354462Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0354746Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 182, in propagate
2025-09-07T08:17:04.0355095Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0355600Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0356142Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0356560Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0356973Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0357727Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0358149Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0358554Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0358935Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0359313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter
2025-09-07T08:17:04.0359700Z     out = src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:17:04.0359875Z 
2025-09-07T08:17:04.0359984Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0360358Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0360697Z     return mod(*inputs)
2025-09-07T08:17:04.0361068Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0361454Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0361701Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 228, in forward
2025-09-07T08:17:04.0361967Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0362237Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 180, in propagate
2025-09-07T08:17:04.0362510Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T08:17:04.0362786Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 127, in _collect
2025-09-07T08:17:04.0363027Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T08:17:04.0363267Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 87, in _lift
2025-09-07T08:17:04.0363520Z     return src.index_select(self.node_dim, index)
2025-09-07T08:17:04.0363667Z 
2025-09-07T08:17:04.0363770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0364137Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0364470Z     return mod(*inputs)
2025-09-07T08:17:04.0364817Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0365191Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0365427Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 228, in forward
2025-09-07T08:17:04.0365685Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0365948Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 182, in propagate
2025-09-07T08:17:04.0366287Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0366926Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0367379Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0367800Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0368224Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0368630Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0369034Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0369438Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0369809Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0370189Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T08:17:04.0370587Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T08:17:04.0370765Z 
2025-09-07T08:17:04.0370869Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0371303Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0371644Z     return mod(*inputs)
2025-09-07T08:17:04.0371991Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0372359Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0372597Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 228, in forward
2025-09-07T08:17:04.0372857Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0373119Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 182, in propagate
2025-09-07T08:17:04.0373452Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0373949Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0374414Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0374835Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0375240Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0375635Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0376040Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0376438Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0376809Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0377184Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T08:17:04.0377573Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T08:17:04.0377747Z 
2025-09-07T08:17:04.0377850Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0378212Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0378541Z     return mod(*inputs)
2025-09-07T08:17:04.0378883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0379254Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0379485Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 228, in forward
2025-09-07T08:17:04.0379750Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0380015Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 182, in propagate
2025-09-07T08:17:04.0383089Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0383588Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0384043Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0384463Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0384873Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0385263Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0385716Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0386117Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0386498Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0386870Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter
2025-09-07T08:17:04.0387252Z     out = src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:17:04.0387418Z 
2025-09-07T08:17:04.0387614Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0387988Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0388321Z     return mod(*inputs)
2025-09-07T08:17:04.0388670Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0389057Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0389297Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 228, in forward
2025-09-07T08:17:04.0389559Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0389825Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 182, in propagate
2025-09-07T08:17:04.0390159Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0390651Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0391107Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0391523Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0391921Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0392319Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0392718Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0393116Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0393492Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0393858Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T08:17:04.0394251Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T08:17:04.0394424Z 
2025-09-07T08:17:04.0394526Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0394890Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0395219Z     return mod(*inputs)
2025-09-07T08:17:04.0395559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0395936Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0396176Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 228, in forward
2025-09-07T08:17:04.0396439Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0396783Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 182, in propagate
2025-09-07T08:17:04.0397125Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0397614Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0398073Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0398485Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0399034Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0399437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0399843Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0400255Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0400637Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0401005Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T08:17:04.0401402Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T08:17:04.0401738Z 
2025-09-07T08:17:04.0401842Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0402209Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0402538Z     return mod(*inputs)
2025-09-07T08:17:04.0402876Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0403256Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0403498Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 228, in forward
2025-09-07T08:17:04.0403764Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0404025Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 182, in propagate
2025-09-07T08:17:04.0404366Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0404860Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0405314Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0405729Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0406124Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0406515Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0406920Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0407315Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0407687Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0408058Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter
2025-09-07T08:17:04.0408446Z     out = src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T08:17:04.0408604Z 
2025-09-07T08:17:04.0408713Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0409078Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0409401Z     return mod(*inputs)
2025-09-07T08:17:04.0409746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0410117Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0410367Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 228, in forward
2025-09-07T08:17:04.0410772Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0411032Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 182, in propagate
2025-09-07T08:17:04.0411373Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0411863Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0412316Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0412723Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0413140Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0413533Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0413941Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0414342Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0414712Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0415086Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T08:17:04.0415558Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T08:17:04.0415729Z 
2025-09-07T08:17:04.0415841Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0416211Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0416542Z     return mod(*inputs)
2025-09-07T08:17:04.0416883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0417255Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0417489Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 228, in forward
2025-09-07T08:17:04.0417745Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0418006Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 182, in propagate
2025-09-07T08:17:04.0418367Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0418860Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0419309Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0419714Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0420117Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0420516Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0420918Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0421318Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0421680Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0422056Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T08:17:04.0422459Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T08:17:04.0422628Z 
2025-09-07T08:17:04.0422717Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0422922Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0423152Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0423515Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0423842Z     return mod(*inputs)
2025-09-07T08:17:04.0424183Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0424624Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0424857Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 228, in forward
2025-09-07T08:17:04.0425122Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0425390Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 182, in propagate
2025-09-07T08:17:04.0425788Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0426272Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0426724Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0427136Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0427536Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0427928Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0428335Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0428732Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0429171Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0429548Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 84, in scatter
2025-09-07T08:17:04.0429908Z     return out / broadcast(count, out, dim)
2025-09-07T08:17:04.0430052Z 
2025-09-07T08:17:04.0430157Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0430520Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0430849Z     return mod(*inputs)
2025-09-07T08:17:04.0431186Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0431564Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0431801Z   File "/tmp/jenkins_pyg/tmpat4d6e9y.py", line 229, in forward
2025-09-07T08:17:04.0432042Z     out = self.lin_l(out)
2025-09-07T08:17:04.0432381Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:17:04.0432754Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:17:04.0432916Z 
2025-09-07T08:17:04.0433025Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0433267Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0433644Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0433986Z     return mod(*inputs)
2025-09-07T08:17:04.0434344Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0434739Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0434979Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 228, in forward
2025-09-07T08:17:04.0435250Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0435520Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 180, in propagate
2025-09-07T08:17:04.0435801Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T08:17:04.0436076Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 127, in _collect
2025-09-07T08:17:04.0436323Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T08:17:04.0436560Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 87, in _lift
2025-09-07T08:17:04.0436808Z     return src.index_select(self.node_dim, index)
2025-09-07T08:17:04.0436962Z 
2025-09-07T08:17:04.0437038Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0437242Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0437478Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0437915Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0438249Z     return mod(*inputs)
2025-09-07T08:17:04.0438596Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0438974Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0439210Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 228, in forward
2025-09-07T08:17:04.0439465Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0439727Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 182, in propagate
2025-09-07T08:17:04.0440064Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0440554Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0440997Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0441419Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0441826Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0442226Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0442696Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0443097Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0443469Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0443840Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 84, in scatter
2025-09-07T08:17:04.0444205Z     return out / broadcast(count, out, dim)
2025-09-07T08:17:04.0444339Z 
2025-09-07T08:17:04.0444449Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0444810Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0445139Z     return mod(*inputs)
2025-09-07T08:17:04.0445482Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0445857Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0446085Z   File "/tmp/jenkins_pyg/tmpys8ym3ky.py", line 229, in forward
2025-09-07T08:17:04.0446325Z     out = self.lin_l(out)
2025-09-07T08:17:04.0446665Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:17:04.0447043Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:17:04.0447182Z 
2025-09-07T08:17:04.0447289Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0447641Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0447970Z     return mod(*inputs)
2025-09-07T08:17:04.0448310Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 234, in forward
2025-09-07T08:17:04.0448676Z     x = self.act(x)
2025-09-07T08:17:04.0448766Z 
2025-09-07T08:17:04.0448850Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0449074Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0449443Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0449771Z     return mod(*inputs)
2025-09-07T08:17:04.0450110Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0450486Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0450725Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 228, in forward
2025-09-07T08:17:04.0450981Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0451249Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 180, in propagate
2025-09-07T08:17:04.0451607Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T08:17:04.0451885Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 127, in _collect
2025-09-07T08:17:04.0452123Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T08:17:04.0452354Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 87, in _lift
2025-09-07T08:17:04.0452601Z     return src.index_select(self.node_dim, index)
2025-09-07T08:17:04.0452752Z 
2025-09-07T08:17:04.0452828Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0453032Z cudagraph partition due to non gpu ops
2025-09-07T08:17:04.0453263Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0453622Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0453945Z     return mod(*inputs)
2025-09-07T08:17:04.0454287Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0454664Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0454897Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 228, in forward
2025-09-07T08:17:04.0455148Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T08:17:04.0455407Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 182, in propagate
2025-09-07T08:17:04.0455836Z     out = self.aggregate(out, ptr=kwargs.ptr, index=kwargs.index, dim_size=kwargs.dim_size)
2025-09-07T08:17:04.0456336Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T08:17:04.0456793Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T08:17:04.0457202Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T08:17:04.0457607Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T08:17:04.0458006Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T08:17:04.0458423Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T08:17:04.0458824Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T08:17:04.0459193Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T08:17:04.0459562Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 84, in scatter
2025-09-07T08:17:04.0459927Z     return out / broadcast(count, out, dim)
2025-09-07T08:17:04.0460066Z 
2025-09-07T08:17:04.0460172Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0460528Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0460856Z     return mod(*inputs)
2025-09-07T08:17:04.0461201Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T08:17:04.0461582Z     x = self.convs[i](x, edge_index)
2025-09-07T08:17:04.0461817Z   File "/tmp/jenkins_pyg/tmpg1iyru12.py", line 229, in forward
2025-09-07T08:17:04.0462046Z     out = self.lin_l(out)
2025-09-07T08:17:04.0462387Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T08:17:04.0462766Z     return F.linear(x, self.weight, self.bias)
2025-09-07T08:17:04.0462906Z 
2025-09-07T08:17:04.0463009Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:04.0463359Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:04.0463686Z     return mod(*inputs)
2025-09-07T08:17:04.0464025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 234, in forward
2025-09-07T08:17:04.0464394Z     x = self.act(x)
2025-09-07T08:17:04.0464480Z 
2025-09-07T08:17:04.0464642Z cudagraph partition due to non gpu ops
2025-09-07T08:17:09.0095919Z pass
2025-09-07T08:17:09.0096325Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:11.0076557Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:17:11.0077538Z   import pynvml  # type: ignore[import]
2025-09-07T08:17:13.0171292Z 
2025-09-07T08:17:13.2602005Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:17:13.2602317Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:17:13.2614768Z cpu  eval  dcgan                              
2025-09-07T08:17:13.3136573Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:13.3259515Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:13.3331373Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:15.4866864Z cudagraph partition due to non gpu ops
2025-09-07T08:17:15.4867161Z cudagraph partition due to non gpu ops
2025-09-07T08:17:15.4867388Z cudagraph partition due to non gpu ops
2025-09-07T08:17:15.4868011Z cudagraph partition due to non gpu ops
2025-09-07T08:17:15.4868223Z cudagraph partition due to non gpu ops
2025-09-07T08:17:15.4868422Z cudagraph partition due to non gpu ops
2025-09-07T08:17:15.4868666Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4869054Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4869392Z     return mod(*inputs)
2025-09-07T08:17:15.4869676Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4869996Z     return self.main(input)
2025-09-07T08:17:15.4870131Z 
2025-09-07T08:17:15.4870247Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4870616Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4870954Z     return mod(*inputs)
2025-09-07T08:17:15.4871226Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4871525Z     return self.main(input)
2025-09-07T08:17:15.4871633Z 
2025-09-07T08:17:15.4871731Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4872091Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4872412Z     return mod(*inputs)
2025-09-07T08:17:15.4872691Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4872984Z     return self.main(input)
2025-09-07T08:17:15.4873095Z 
2025-09-07T08:17:15.4873189Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4873566Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4873895Z     return mod(*inputs)
2025-09-07T08:17:15.4874152Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4874433Z     return self.main(input)
2025-09-07T08:17:15.4874543Z 
2025-09-07T08:17:15.4874641Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4874990Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4875308Z     return mod(*inputs)
2025-09-07T08:17:15.4875556Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4875840Z     return self.main(input)
2025-09-07T08:17:15.4875946Z 
2025-09-07T08:17:15.4876042Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4876390Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4876873Z     return mod(*inputs)
2025-09-07T08:17:15.4877121Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4877405Z     return self.main(input)
2025-09-07T08:17:15.4877514Z 
2025-09-07T08:17:15.4877618Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:15.4877970Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:17:15.4878279Z     return mod(*inputs)
2025-09-07T08:17:15.4878532Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T08:17:15.4878817Z     return self.main(input)
2025-09-07T08:17:15.4878919Z 
2025-09-07T08:17:22.8292456Z pass
2025-09-07T08:17:22.8295409Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:24.7589409Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:17:24.7590399Z   import pynvml  # type: ignore[import]
2025-09-07T08:17:26.7777280Z 
2025-09-07T08:17:28.3926950Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:17:28.3927705Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:17:28.4129019Z cpu  eval  demucs                             
2025-09-07T08:17:33.1854555Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:33.3492591Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:33.4970430Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:35.5909706Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:35.5910111Z    File "/torchbench/torchbenchmark/models/demucs/__init__.py", line 32, in forward
2025-09-07T08:17:35.5910483Z     mix = sources.sum(dim=1)
2025-09-07T08:17:35.5910607Z 
2025-09-07T08:17:40.7990208Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7990635Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7990953Z     x = encode(x)
2025-09-07T08:17:40.7991089Z 
2025-09-07T08:17:40.7991196Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7991540Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7991846Z     x = encode(x)
2025-09-07T08:17:40.7991935Z 
2025-09-07T08:17:40.7992039Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7992365Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7992666Z     x = encode(x)
2025-09-07T08:17:40.7992757Z 
2025-09-07T08:17:40.7992865Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7993223Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7993515Z     x = encode(x)
2025-09-07T08:17:40.7993604Z 
2025-09-07T08:17:40.7993704Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7994043Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7994340Z     x = encode(x)
2025-09-07T08:17:40.7994424Z 
2025-09-07T08:17:40.7994522Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7994840Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7995133Z     x = encode(x)
2025-09-07T08:17:40.7995215Z 
2025-09-07T08:17:40.7995317Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7995648Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7995931Z     x = encode(x)
2025-09-07T08:17:40.7996400Z 
2025-09-07T08:17:40.7996499Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7996836Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7997132Z     x = encode(x)
2025-09-07T08:17:40.7997217Z 
2025-09-07T08:17:40.7997324Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7997651Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7997960Z     x = encode(x)
2025-09-07T08:17:40.7998045Z 
2025-09-07T08:17:40.7998152Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7998489Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7998944Z     x = encode(x)
2025-09-07T08:17:40.7999034Z 
2025-09-07T08:17:40.7999127Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.7999462Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.7999764Z     x = encode(x)
2025-09-07T08:17:40.7999846Z 
2025-09-07T08:17:40.7999947Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8000272Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8000562Z     x = encode(x)
2025-09-07T08:17:40.8000783Z 
2025-09-07T08:17:40.8000900Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8001229Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8001520Z     x = encode(x)
2025-09-07T08:17:40.8001603Z 
2025-09-07T08:17:40.8001695Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8002017Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8002314Z     x = encode(x)
2025-09-07T08:17:40.8002395Z 
2025-09-07T08:17:40.8002491Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8002818Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8003112Z     x = encode(x)
2025-09-07T08:17:40.8003201Z 
2025-09-07T08:17:40.8003295Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8003629Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8003947Z     x = encode(x)
2025-09-07T08:17:40.8004038Z 
2025-09-07T08:17:40.8004132Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8004462Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8004755Z     x = encode(x)
2025-09-07T08:17:40.8004837Z 
2025-09-07T08:17:40.8004937Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8005265Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8005558Z     x = encode(x)
2025-09-07T08:17:40.8005648Z 
2025-09-07T08:17:40.8005741Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8006063Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8006357Z     x = encode(x)
2025-09-07T08:17:40.8006438Z 
2025-09-07T08:17:40.8006532Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8006861Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8007168Z     x = encode(x)
2025-09-07T08:17:40.8007254Z 
2025-09-07T08:17:40.8007358Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8007676Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8007970Z     x = encode(x)
2025-09-07T08:17:40.8008058Z 
2025-09-07T08:17:40.8008148Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8008484Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8008879Z     x = encode(x)
2025-09-07T08:17:40.8008958Z 
2025-09-07T08:17:40.8009046Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8009363Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8009654Z     x = encode(x)
2025-09-07T08:17:40.8009735Z 
2025-09-07T08:17:40.8009838Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:40.8010159Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T08:17:40.8010440Z     x = encode(x)
2025-09-07T08:17:40.8010526Z 
2025-09-07T08:17:41.4015195Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4015693Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4016084Z     x = x + skip
2025-09-07T08:17:41.4016180Z 
2025-09-07T08:17:41.4016295Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4016761Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4017135Z     x = decode(x)
2025-09-07T08:17:41.4017233Z 
2025-09-07T08:17:41.4017336Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4018112Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4018491Z     x = decode(x)
2025-09-07T08:17:41.4018580Z 
2025-09-07T08:17:41.4018690Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4019090Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4019461Z     x = decode(x)
2025-09-07T08:17:41.4019553Z 
2025-09-07T08:17:41.4019656Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4020068Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4020439Z     x = x + skip
2025-09-07T08:17:41.4020536Z 
2025-09-07T08:17:41.4020633Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4021033Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4021423Z     x = decode(x)
2025-09-07T08:17:41.4021511Z 
2025-09-07T08:17:41.4021618Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4022029Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4022402Z     x = decode(x)
2025-09-07T08:17:41.4022491Z 
2025-09-07T08:17:41.4022587Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4022993Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4023363Z     x = decode(x)
2025-09-07T08:17:41.4023444Z 
2025-09-07T08:17:41.4023540Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4023935Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4024300Z     x = x + skip
2025-09-07T08:17:41.4024384Z 
2025-09-07T08:17:41.4024487Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4024884Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4025245Z     x = decode(x)
2025-09-07T08:17:41.4025333Z 
2025-09-07T08:17:41.4025426Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4025887Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4026258Z     x = decode(x)
2025-09-07T08:17:41.4026344Z 
2025-09-07T08:17:41.4026438Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4027028Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4027399Z     x = decode(x)
2025-09-07T08:17:41.4027482Z 
2025-09-07T08:17:41.4027583Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4027977Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4028326Z     x = x + skip
2025-09-07T08:17:41.4028416Z 
2025-09-07T08:17:41.4028526Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4028927Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4029290Z     x = decode(x)
2025-09-07T08:17:41.4029371Z 
2025-09-07T08:17:41.4029476Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4029875Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4030240Z     x = decode(x)
2025-09-07T08:17:41.4030331Z 
2025-09-07T08:17:41.4030424Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4030888Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4031256Z     x = decode(x)
2025-09-07T08:17:41.4031339Z 
2025-09-07T08:17:41.4031431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4031826Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4032191Z     x = x + skip
2025-09-07T08:17:41.4032274Z 
2025-09-07T08:17:41.4032373Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4032764Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4033125Z     x = decode(x)
2025-09-07T08:17:41.4033213Z 
2025-09-07T08:17:41.4033305Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4033700Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4034061Z     x = decode(x)
2025-09-07T08:17:41.4034141Z 
2025-09-07T08:17:41.4034237Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4034659Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4035021Z     x = decode(x)
2025-09-07T08:17:41.4035104Z 
2025-09-07T08:17:41.4035203Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4035586Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4043527Z     x = x + skip
2025-09-07T08:17:41.4043636Z 
2025-09-07T08:17:41.4043757Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4044190Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4044571Z     x = decode(x)
2025-09-07T08:17:41.4044669Z 
2025-09-07T08:17:41.4044771Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4045184Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4045549Z     x = decode(x)
2025-09-07T08:17:41.4045639Z 
2025-09-07T08:17:41.4045730Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:17:41.4046132Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T08:17:41.4046502Z     x = decode(x)
2025-09-07T08:17:41.4046588Z 
2025-09-07T08:17:42.0124091Z pass
2025-09-07T08:17:42.0127313Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:44.2231397Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:17:44.2232393Z   import pynvml  # type: ignore[import]
2025-09-07T08:17:46.2341640Z 
2025-09-07T08:17:46.9987421Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:17:46.9987714Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:17:47.0158355Z cpu  eval  densenet121                        
2025-09-07T08:17:48.1526853Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:48.4142542Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:17:48.6695989Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:18:00.1545130Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1545412Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1545671Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1545867Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1546069Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1546677Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1546897Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1547093Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1547295Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1547505Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1547726Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1547934Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1548131Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1548333Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1548531Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1548768Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1548970Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1549171Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1549370Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1549571Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1549773Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1549972Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1550172Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1550374Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1550565Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1550762Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1550967Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1551168Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1551359Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1551560Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1551760Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1551958Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1552211Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1552405Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1552603Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1552803Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1553003Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1553196Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1553393Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1553598Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1553796Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1553998Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1554197Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1554395Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1554587Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1554945Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1555145Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1555347Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1555543Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1555753Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1555954Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1556152Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1556364Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1556554Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1556758Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1556955Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1557151Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1557340Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1557549Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1557747Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1557986Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1558390Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1558743Z     return mod(*inputs)
2025-09-07T08:18:00.1559108Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1559558Z     features = self.features(x)
2025-09-07T08:18:00.1559681Z 
2025-09-07T08:18:00.1559797Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1560190Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1560514Z     return mod(*inputs)
2025-09-07T08:18:00.1560859Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1561243Z     features = self.features(x)
2025-09-07T08:18:00.1561360Z 
2025-09-07T08:18:00.1561529Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1561905Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1562225Z     return mod(*inputs)
2025-09-07T08:18:00.1562554Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1562923Z     features = self.features(x)
2025-09-07T08:18:00.1563034Z 
2025-09-07T08:18:00.1563142Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1563495Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1563820Z     return mod(*inputs)
2025-09-07T08:18:00.1564155Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1564523Z     features = self.features(x)
2025-09-07T08:18:00.1564869Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1565221Z     new_features = layer(features)
2025-09-07T08:18:00.1565583Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1565982Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1566387Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1566862Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1567097Z 
2025-09-07T08:18:00.1567198Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1567565Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1567888Z     return mod(*inputs)
2025-09-07T08:18:00.1568213Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1568644Z     features = self.features(x)
2025-09-07T08:18:00.1568991Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1569349Z     new_features = layer(features)
2025-09-07T08:18:00.1569702Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1570126Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1570317Z 
2025-09-07T08:18:00.1570426Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1570803Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1571129Z     return mod(*inputs)
2025-09-07T08:18:00.1571452Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1571809Z     features = self.features(x)
2025-09-07T08:18:00.1572150Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1572503Z     new_features = layer(features)
2025-09-07T08:18:00.1572850Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1573338Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1573539Z 
2025-09-07T08:18:00.1573636Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1573990Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1574320Z     return mod(*inputs)
2025-09-07T08:18:00.1574653Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1575022Z     features = self.features(x)
2025-09-07T08:18:00.1575350Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1575705Z     new_features = layer(features)
2025-09-07T08:18:00.1576078Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1576464Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1576883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1577270Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1577415Z 
2025-09-07T08:18:00.1577516Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1577879Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1578209Z     return mod(*inputs)
2025-09-07T08:18:00.1578523Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1578880Z     features = self.features(x)
2025-09-07T08:18:00.1579218Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1579576Z     new_features = layer(features)
2025-09-07T08:18:00.1579924Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1580326Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1580724Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1581196Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1581426Z 
2025-09-07T08:18:00.1581527Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1581888Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1582207Z     return mod(*inputs)
2025-09-07T08:18:00.1582613Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1582973Z     features = self.features(x)
2025-09-07T08:18:00.1583307Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1583665Z     new_features = layer(features)
2025-09-07T08:18:00.1584020Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1584398Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1584798Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1585266Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1585509Z 
2025-09-07T08:18:00.1585658Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1586029Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1586358Z     return mod(*inputs)
2025-09-07T08:18:00.1586677Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1587027Z     features = self.features(x)
2025-09-07T08:18:00.1587442Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1587802Z     new_features = layer(features)
2025-09-07T08:18:00.1588148Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1588566Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1588755Z 
2025-09-07T08:18:00.1588856Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1589217Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1589545Z     return mod(*inputs)
2025-09-07T08:18:00.1589878Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1590229Z     features = self.features(x)
2025-09-07T08:18:00.1590556Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1590911Z     new_features = layer(features)
2025-09-07T08:18:00.1591248Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1591667Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1591853Z 
2025-09-07T08:18:00.1591956Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1592297Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1592632Z     return mod(*inputs)
2025-09-07T08:18:00.1592961Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1593312Z     features = self.features(x)
2025-09-07T08:18:00.1593640Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1593996Z     new_features = layer(features)
2025-09-07T08:18:00.1594337Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1594724Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1595112Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1595488Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1595629Z 
2025-09-07T08:18:00.1595726Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1596081Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1596513Z     return mod(*inputs)
2025-09-07T08:18:00.1596837Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1597193Z     features = self.features(x)
2025-09-07T08:18:00.1597542Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1597900Z     new_features = layer(features)
2025-09-07T08:18:00.1598248Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1598625Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1599169Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1599647Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1599885Z 
2025-09-07T08:18:00.1599994Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1600351Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1600674Z     return mod(*inputs)
2025-09-07T08:18:00.1601161Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1601528Z     features = self.features(x)
2025-09-07T08:18:00.1601867Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1602217Z     new_features = layer(features)
2025-09-07T08:18:00.1602563Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1602944Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1603331Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1603803Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1604029Z 
2025-09-07T08:18:00.1604128Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1604495Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1604819Z     return mod(*inputs)
2025-09-07T08:18:00.1605144Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1605506Z     features = self.features(x)
2025-09-07T08:18:00.1605838Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1606194Z     new_features = layer(features)
2025-09-07T08:18:00.1606535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1606954Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1607145Z 
2025-09-07T08:18:00.1607245Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1607609Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1607928Z     return mod(*inputs)
2025-09-07T08:18:00.1608253Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1608603Z     features = self.features(x)
2025-09-07T08:18:00.1608937Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1609291Z     new_features = layer(features)
2025-09-07T08:18:00.1609636Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1610047Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1610343Z 
2025-09-07T08:18:00.1610445Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1610791Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1611116Z     return mod(*inputs)
2025-09-07T08:18:00.1611437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1611787Z     features = self.features(x)
2025-09-07T08:18:00.1612118Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1612472Z     new_features = layer(features)
2025-09-07T08:18:00.1612818Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1613196Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1613585Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1613964Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1614113Z 
2025-09-07T08:18:00.1614208Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1614564Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1614981Z     return mod(*inputs)
2025-09-07T08:18:00.1615291Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1615649Z     features = self.features(x)
2025-09-07T08:18:00.1615980Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1616337Z     new_features = layer(features)
2025-09-07T08:18:00.1616678Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1617055Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1617448Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1617915Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1618144Z 
2025-09-07T08:18:00.1618245Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1618602Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1618925Z     return mod(*inputs)
2025-09-07T08:18:00.1619238Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1619599Z     features = self.features(x)
2025-09-07T08:18:00.1619930Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1620273Z     new_features = layer(features)
2025-09-07T08:18:00.1620619Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1620997Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1621388Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1621847Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1622079Z 
2025-09-07T08:18:00.1622175Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1622529Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1622868Z     return mod(*inputs)
2025-09-07T08:18:00.1623185Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1623537Z     features = self.features(x)
2025-09-07T08:18:00.1623901Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1624357Z     new_features = layer(features)
2025-09-07T08:18:00.1624712Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1625134Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1625327Z 
2025-09-07T08:18:00.1625426Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1625832Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1626156Z     return mod(*inputs)
2025-09-07T08:18:00.1626483Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1626836Z     features = self.features(x)
2025-09-07T08:18:00.1627171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1627530Z     new_features = layer(features)
2025-09-07T08:18:00.1627879Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1628307Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1628499Z 
2025-09-07T08:18:00.1629763Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1630134Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1630459Z     return mod(*inputs)
2025-09-07T08:18:00.1630781Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1631147Z     features = self.features(x)
2025-09-07T08:18:00.1631478Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1631837Z     new_features = layer(features)
2025-09-07T08:18:00.1632181Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1632572Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1632969Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1633344Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1633488Z 
2025-09-07T08:18:00.1633583Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1633946Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1634268Z     return mod(*inputs)
2025-09-07T08:18:00.1634586Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1634942Z     features = self.features(x)
2025-09-07T08:18:00.1635271Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1635629Z     new_features = layer(features)
2025-09-07T08:18:00.1635967Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1636338Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1636733Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1637204Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1637433Z 
2025-09-07T08:18:00.1637536Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1637894Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1638212Z     return mod(*inputs)
2025-09-07T08:18:00.1638528Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1638965Z     features = self.features(x)
2025-09-07T08:18:00.1639300Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1639650Z     new_features = layer(features)
2025-09-07T08:18:00.1640002Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1640384Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1640806Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1641271Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1641499Z 
2025-09-07T08:18:00.1641597Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1641957Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1642296Z     return mod(*inputs)
2025-09-07T08:18:00.1642619Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1642964Z     features = self.features(x)
2025-09-07T08:18:00.1643298Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1643739Z     new_features = layer(features)
2025-09-07T08:18:00.1644088Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1644501Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1644690Z 
2025-09-07T08:18:00.1644786Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1645145Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1645466Z     return mod(*inputs)
2025-09-07T08:18:00.1645786Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1646148Z     features = self.features(x)
2025-09-07T08:18:00.1646473Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1646825Z     new_features = layer(features)
2025-09-07T08:18:00.1647164Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1647572Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1647759Z 
2025-09-07T08:18:00.1647854Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1648211Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1648530Z     return mod(*inputs)
2025-09-07T08:18:00.1648848Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1649205Z     features = self.features(x)
2025-09-07T08:18:00.1649525Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1649875Z     new_features = layer(features)
2025-09-07T08:18:00.1650222Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1650597Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1650977Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1651353Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1651492Z 
2025-09-07T08:18:00.1651587Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1651943Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1652265Z     return mod(*inputs)
2025-09-07T08:18:00.1652650Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1653001Z     features = self.features(x)
2025-09-07T08:18:00.1653330Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1653678Z     new_features = layer(features)
2025-09-07T08:18:00.1654017Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1654390Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1654780Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1655248Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1655472Z 
2025-09-07T08:18:00.1655579Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1655927Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1656258Z     return mod(*inputs)
2025-09-07T08:18:00.1656576Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1656934Z     features = self.features(x)
2025-09-07T08:18:00.1657333Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1657687Z     new_features = layer(features)
2025-09-07T08:18:00.1658028Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1658406Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1658795Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1659259Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1659491Z 
2025-09-07T08:18:00.1659588Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1659945Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1660266Z     return mod(*inputs)
2025-09-07T08:18:00.1660583Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1660927Z     features = self.features(x)
2025-09-07T08:18:00.1661257Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1661608Z     new_features = layer(features)
2025-09-07T08:18:00.1661943Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1662355Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1662544Z 
2025-09-07T08:18:00.1662639Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1662994Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1663312Z     return mod(*inputs)
2025-09-07T08:18:00.1663629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1663979Z     features = self.features(x)
2025-09-07T08:18:00.1664313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1664665Z     new_features = layer(features)
2025-09-07T08:18:00.1665003Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1665410Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1665691Z 
2025-09-07T08:18:00.1665771Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1666006Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1666440Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1666765Z     return mod(*inputs)
2025-09-07T08:18:00.1667079Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1667437Z     features = self.features(x)
2025-09-07T08:18:00.1667770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T08:18:00.1668127Z     return torch.cat(features, 1)
2025-09-07T08:18:00.1668246Z 
2025-09-07T08:18:00.1668349Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1668694Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1669012Z     return mod(*inputs)
2025-09-07T08:18:00.1669334Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1669690Z     features = self.features(x)
2025-09-07T08:18:00.1669800Z 
2025-09-07T08:18:00.1669903Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1670253Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1670570Z     return mod(*inputs)
2025-09-07T08:18:00.1670953Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1671313Z     features = self.features(x)
2025-09-07T08:18:00.1671425Z 
2025-09-07T08:18:00.1671521Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1671883Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1672206Z     return mod(*inputs)
2025-09-07T08:18:00.1672530Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1672891Z     features = self.features(x)
2025-09-07T08:18:00.1673227Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1673585Z     new_features = layer(features)
2025-09-07T08:18:00.1673940Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1674321Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1674706Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1675173Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1675413Z 
2025-09-07T08:18:00.1675513Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1675872Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1676197Z     return mod(*inputs)
2025-09-07T08:18:00.1676517Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1676874Z     features = self.features(x)
2025-09-07T08:18:00.1677210Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1677565Z     new_features = layer(features)
2025-09-07T08:18:00.1677908Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1678321Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1678519Z 
2025-09-07T08:18:00.1678617Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1678976Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1679296Z     return mod(*inputs)
2025-09-07T08:18:00.1679608Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1680036Z     features = self.features(x)
2025-09-07T08:18:00.1680370Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1680721Z     new_features = layer(features)
2025-09-07T08:18:00.1681066Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1681477Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1681673Z 
2025-09-07T08:18:00.1682093Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1682450Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1682773Z     return mod(*inputs)
2025-09-07T08:18:00.1683095Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1683453Z     features = self.features(x)
2025-09-07T08:18:00.1683779Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1684138Z     new_features = layer(features)
2025-09-07T08:18:00.1684572Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1684956Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1685352Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1685725Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1685861Z 
2025-09-07T08:18:00.1685963Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1686321Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1686637Z     return mod(*inputs)
2025-09-07T08:18:00.1686959Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1687316Z     features = self.features(x)
2025-09-07T08:18:00.1687651Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1687999Z     new_features = layer(features)
2025-09-07T08:18:00.1688351Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1688732Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1689128Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1689599Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1689829Z 
2025-09-07T08:18:00.1689927Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1690287Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1690616Z     return mod(*inputs)
2025-09-07T08:18:00.1690936Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1691291Z     features = self.features(x)
2025-09-07T08:18:00.1691628Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1691981Z     new_features = layer(features)
2025-09-07T08:18:00.1692327Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1692709Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1693092Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1693557Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1693875Z 
2025-09-07T08:18:00.1693973Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1694331Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1694655Z     return mod(*inputs)
2025-09-07T08:18:00.1694972Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1695327Z     features = self.features(x)
2025-09-07T08:18:00.1695662Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1696016Z     new_features = layer(features)
2025-09-07T08:18:00.1696351Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1696765Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1696958Z 
2025-09-07T08:18:00.1697059Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1697417Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1697741Z     return mod(*inputs)
2025-09-07T08:18:00.1698053Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1698486Z     features = self.features(x)
2025-09-07T08:18:00.1698989Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1699379Z     new_features = layer(features)
2025-09-07T08:18:00.1699740Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1700161Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1700361Z 
2025-09-07T08:18:00.1700461Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1700830Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1701159Z     return mod(*inputs)
2025-09-07T08:18:00.1701482Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1701842Z     features = self.features(x)
2025-09-07T08:18:00.1702187Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1702551Z     new_features = layer(features)
2025-09-07T08:18:00.1702902Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1703297Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1703690Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1704071Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1704212Z 
2025-09-07T08:18:00.1704313Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1704672Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1705016Z     return mod(*inputs)
2025-09-07T08:18:00.1705349Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1705759Z     features = self.features(x)
2025-09-07T08:18:00.1706103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1706452Z     new_features = layer(features)
2025-09-07T08:18:00.1706794Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1707173Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1707564Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1708185Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1708418Z 
2025-09-07T08:18:00.1708515Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1708873Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1709205Z     return mod(*inputs)
2025-09-07T08:18:00.1709525Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1709876Z     features = self.features(x)
2025-09-07T08:18:00.1710212Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1710565Z     new_features = layer(features)
2025-09-07T08:18:00.1710910Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1711295Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1711683Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1712144Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1712380Z 
2025-09-07T08:18:00.1712571Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1712935Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1713262Z     return mod(*inputs)
2025-09-07T08:18:00.1713575Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1713928Z     features = self.features(x)
2025-09-07T08:18:00.1714264Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1714617Z     new_features = layer(features)
2025-09-07T08:18:00.1714958Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1715379Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1715576Z 
2025-09-07T08:18:00.1715676Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1716041Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1716365Z     return mod(*inputs)
2025-09-07T08:18:00.1716678Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1717034Z     features = self.features(x)
2025-09-07T08:18:00.1717371Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1717732Z     new_features = layer(features)
2025-09-07T08:18:00.1718069Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1718490Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1718685Z 
2025-09-07T08:18:00.1718779Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1719131Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1719457Z     return mod(*inputs)
2025-09-07T08:18:00.1719771Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1720127Z     features = self.features(x)
2025-09-07T08:18:00.1720463Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1720824Z     new_features = layer(features)
2025-09-07T08:18:00.1721168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1721625Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1722012Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1722389Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1722537Z 
2025-09-07T08:18:00.1722641Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1722995Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1723339Z     return mod(*inputs)
2025-09-07T08:18:00.1723667Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1724020Z     features = self.features(x)
2025-09-07T08:18:00.1724354Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1724704Z     new_features = layer(features)
2025-09-07T08:18:00.1725045Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1725426Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1725814Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1726341Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1726583Z 
2025-09-07T08:18:00.1726684Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1727041Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1727369Z     return mod(*inputs)
2025-09-07T08:18:00.1727691Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1728041Z     features = self.features(x)
2025-09-07T08:18:00.1728378Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1728733Z     new_features = layer(features)
2025-09-07T08:18:00.1729072Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1729453Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1729837Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1730300Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1730534Z 
2025-09-07T08:18:00.1730631Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1730986Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1731305Z     return mod(*inputs)
2025-09-07T08:18:00.1731627Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1731985Z     features = self.features(x)
2025-09-07T08:18:00.1732325Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1732683Z     new_features = layer(features)
2025-09-07T08:18:00.1733020Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1733434Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1733631Z 
2025-09-07T08:18:00.1733727Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1734084Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1734410Z     return mod(*inputs)
2025-09-07T08:18:00.1734723Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1735076Z     features = self.features(x)
2025-09-07T08:18:00.1735487Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1735844Z     new_features = layer(features)
2025-09-07T08:18:00.1736177Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1736592Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1736789Z 
2025-09-07T08:18:00.1736884Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1737242Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1737564Z     return mod(*inputs)
2025-09-07T08:18:00.1737875Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1738224Z     features = self.features(x)
2025-09-07T08:18:00.1738554Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1738912Z     new_features = layer(features)
2025-09-07T08:18:00.1739244Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1739624Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1740081Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1740466Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1740600Z 
2025-09-07T08:18:00.1740706Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1741059Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1741386Z     return mod(*inputs)
2025-09-07T08:18:00.1741706Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1742065Z     features = self.features(x)
2025-09-07T08:18:00.1742397Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1742755Z     new_features = layer(features)
2025-09-07T08:18:00.1743097Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1743488Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1743876Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1744330Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1744565Z 
2025-09-07T08:18:00.1744662Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1745014Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1745335Z     return mod(*inputs)
2025-09-07T08:18:00.1745700Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1746052Z     features = self.features(x)
2025-09-07T08:18:00.1746394Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1746753Z     new_features = layer(features)
2025-09-07T08:18:00.1747096Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1747478Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1747865Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1748326Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1748557Z 
2025-09-07T08:18:00.1748666Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1749152Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1749475Z     return mod(*inputs)
2025-09-07T08:18:00.1749797Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1750153Z     features = self.features(x)
2025-09-07T08:18:00.1750494Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1750854Z     new_features = layer(features)
2025-09-07T08:18:00.1751191Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1751607Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1751803Z 
2025-09-07T08:18:00.1751902Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1752260Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1752581Z     return mod(*inputs)
2025-09-07T08:18:00.1752900Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1753255Z     features = self.features(x)
2025-09-07T08:18:00.1753660Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1754021Z     new_features = layer(features)
2025-09-07T08:18:00.1754356Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1754775Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1754970Z 
2025-09-07T08:18:00.1755068Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1755430Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1755757Z     return mod(*inputs)
2025-09-07T08:18:00.1756080Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1756429Z     features = self.features(x)
2025-09-07T08:18:00.1756770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1757129Z     new_features = layer(features)
2025-09-07T08:18:00.1757464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1757842Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1758228Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1758604Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1758739Z 
2025-09-07T08:18:00.1758840Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1759189Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1759523Z     return mod(*inputs)
2025-09-07T08:18:00.1759852Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1760216Z     features = self.features(x)
2025-09-07T08:18:00.1760553Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1760908Z     new_features = layer(features)
2025-09-07T08:18:00.1761252Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1761637Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1762029Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1762489Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1762806Z 
2025-09-07T08:18:00.1762911Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1763274Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1763604Z     return mod(*inputs)
2025-09-07T08:18:00.1763928Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1764279Z     features = self.features(x)
2025-09-07T08:18:00.1764626Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1764991Z     new_features = layer(features)
2025-09-07T08:18:00.1765340Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1765716Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1766105Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1766573Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1766801Z 
2025-09-07T08:18:00.1766908Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1767339Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1767666Z     return mod(*inputs)
2025-09-07T08:18:00.1767993Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1768352Z     features = self.features(x)
2025-09-07T08:18:00.1768693Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1769047Z     new_features = layer(features)
2025-09-07T08:18:00.1769399Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1769819Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1770011Z 
2025-09-07T08:18:00.1770121Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1770486Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1770812Z     return mod(*inputs)
2025-09-07T08:18:00.1771132Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1771495Z     features = self.features(x)
2025-09-07T08:18:00.1771832Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1772183Z     new_features = layer(features)
2025-09-07T08:18:00.1789844Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1790310Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1790518Z 
2025-09-07T08:18:00.1790625Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1790991Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1791317Z     return mod(*inputs)
2025-09-07T08:18:00.1791655Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1792014Z     features = self.features(x)
2025-09-07T08:18:00.1792348Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1792696Z     new_features = layer(features)
2025-09-07T08:18:00.1793039Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1793418Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1793804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1794301Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1794438Z 
2025-09-07T08:18:00.1794535Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1794885Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1795201Z     return mod(*inputs)
2025-09-07T08:18:00.1795513Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1795857Z     features = self.features(x)
2025-09-07T08:18:00.1796179Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1796523Z     new_features = layer(features)
2025-09-07T08:18:00.1796849Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1797215Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1797597Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1798055Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1798288Z 
2025-09-07T08:18:00.1798456Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1798996Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1799313Z     return mod(*inputs)
2025-09-07T08:18:00.1799627Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1799971Z     features = self.features(x)
2025-09-07T08:18:00.1800296Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1800636Z     new_features = layer(features)
2025-09-07T08:18:00.1800980Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1801351Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1801728Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1802181Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1802408Z 
2025-09-07T08:18:00.1802502Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1802847Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1803156Z     return mod(*inputs)
2025-09-07T08:18:00.1803463Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1803803Z     features = self.features(x)
2025-09-07T08:18:00.1804127Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1804467Z     new_features = layer(features)
2025-09-07T08:18:00.1804800Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1805201Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1805394Z 
2025-09-07T08:18:00.1805489Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1805835Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1806148Z     return mod(*inputs)
2025-09-07T08:18:00.1806463Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1806805Z     features = self.features(x)
2025-09-07T08:18:00.1807130Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1807620Z     new_features = layer(features)
2025-09-07T08:18:00.1807960Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1808363Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1808548Z 
2025-09-07T08:18:00.1808651Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1808997Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1809309Z     return mod(*inputs)
2025-09-07T08:18:00.1809622Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1809980Z     features = self.features(x)
2025-09-07T08:18:00.1810302Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1810646Z     new_features = layer(features)
2025-09-07T08:18:00.1810982Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1811354Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1811736Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1812194Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1812334Z 
2025-09-07T08:18:00.1812429Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1812770Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1813079Z     return mod(*inputs)
2025-09-07T08:18:00.1813381Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1813722Z     features = self.features(x)
2025-09-07T08:18:00.1814046Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1814394Z     new_features = layer(features)
2025-09-07T08:18:00.1814723Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1815111Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1815494Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1815942Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1816165Z 
2025-09-07T08:18:00.1816259Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1816599Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1816905Z     return mod(*inputs)
2025-09-07T08:18:00.1817210Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1817555Z     features = self.features(x)
2025-09-07T08:18:00.1817884Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1818225Z     new_features = layer(features)
2025-09-07T08:18:00.1818560Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1818931Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1819313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1819770Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1819995Z 
2025-09-07T08:18:00.1820093Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1820438Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1821241Z     return mod(*inputs)
2025-09-07T08:18:00.1821560Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1821901Z     features = self.features(x)
2025-09-07T08:18:00.1822234Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1822582Z     new_features = layer(features)
2025-09-07T08:18:00.1822922Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1823328Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1823515Z 
2025-09-07T08:18:00.1823611Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1823960Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1824270Z     return mod(*inputs)
2025-09-07T08:18:00.1824578Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1824931Z     features = self.features(x)
2025-09-07T08:18:00.1825254Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1825667Z     new_features = layer(features)
2025-09-07T08:18:00.1826081Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1826499Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1826687Z 
2025-09-07T08:18:00.1826784Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1827133Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1827448Z     return mod(*inputs)
2025-09-07T08:18:00.1827758Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1828114Z     features = self.features(x)
2025-09-07T08:18:00.1828429Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1828771Z     new_features = layer(features)
2025-09-07T08:18:00.1829102Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1829474Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1829850Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1830216Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1830354Z 
2025-09-07T08:18:00.1830446Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1830791Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1831106Z     return mod(*inputs)
2025-09-07T08:18:00.1831423Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1831769Z     features = self.features(x)
2025-09-07T08:18:00.1832095Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1832443Z     new_features = layer(features)
2025-09-07T08:18:00.1832770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1833136Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1833517Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1833974Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1834198Z 
2025-09-07T08:18:00.1834298Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1834721Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1835031Z     return mod(*inputs)
2025-09-07T08:18:00.1835344Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1835688Z     features = self.features(x)
2025-09-07T08:18:00.1836018Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1836358Z     new_features = layer(features)
2025-09-07T08:18:00.1836690Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1837058Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1837437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1837887Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1838120Z 
2025-09-07T08:18:00.1838213Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1838559Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1838869Z     return mod(*inputs)
2025-09-07T08:18:00.1839267Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1839610Z     features = self.features(x)
2025-09-07T08:18:00.1839938Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1840276Z     new_features = layer(features)
2025-09-07T08:18:00.1840602Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1841003Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1841190Z 
2025-09-07T08:18:00.1841289Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1841634Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1841943Z     return mod(*inputs)
2025-09-07T08:18:00.1842248Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1842591Z     features = self.features(x)
2025-09-07T08:18:00.1842914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1843257Z     new_features = layer(features)
2025-09-07T08:18:00.1843584Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1843981Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1844164Z 
2025-09-07T08:18:00.1844256Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1844605Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1844913Z     return mod(*inputs)
2025-09-07T08:18:00.1845221Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1845561Z     features = self.features(x)
2025-09-07T08:18:00.1845884Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1846225Z     new_features = layer(features)
2025-09-07T08:18:00.1846551Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1846918Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1847289Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1847653Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1847879Z 
2025-09-07T08:18:00.1847970Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1848317Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1848630Z     return mod(*inputs)
2025-09-07T08:18:00.1848937Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1849279Z     features = self.features(x)
2025-09-07T08:18:00.1849609Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1849970Z     new_features = layer(features)
2025-09-07T08:18:00.1850315Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1850695Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1851082Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1851551Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1851778Z 
2025-09-07T08:18:00.1851879Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1852291Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1852623Z     return mod(*inputs)
2025-09-07T08:18:00.1852945Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1853296Z     features = self.features(x)
2025-09-07T08:18:00.1853618Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1853971Z     new_features = layer(features)
2025-09-07T08:18:00.1854307Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1854690Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1855071Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1855528Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1855765Z 
2025-09-07T08:18:00.1855864Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1856223Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1856540Z     return mod(*inputs)
2025-09-07T08:18:00.1856854Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1857203Z     features = self.features(x)
2025-09-07T08:18:00.1857536Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1857885Z     new_features = layer(features)
2025-09-07T08:18:00.1858220Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1858627Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1858821Z 
2025-09-07T08:18:00.1858913Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1859263Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1859582Z     return mod(*inputs)
2025-09-07T08:18:00.1859894Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1860235Z     features = self.features(x)
2025-09-07T08:18:00.1860557Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1860900Z     new_features = layer(features)
2025-09-07T08:18:00.1861245Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1861737Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1861926Z 
2025-09-07T08:18:00.1862021Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1862375Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1862694Z     return mod(*inputs)
2025-09-07T08:18:00.1863007Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1863352Z     features = self.features(x)
2025-09-07T08:18:00.1863678Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1864024Z     new_features = layer(features)
2025-09-07T08:18:00.1864358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1864738Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1865118Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1865486Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1865677Z 
2025-09-07T08:18:00.1865837Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1866194Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1866508Z     return mod(*inputs)
2025-09-07T08:18:00.1866818Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1867158Z     features = self.features(x)
2025-09-07T08:18:00.1867488Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1867834Z     new_features = layer(features)
2025-09-07T08:18:00.1868169Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1868535Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1868914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1869382Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1869611Z 
2025-09-07T08:18:00.1869717Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1870067Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1870389Z     return mod(*inputs)
2025-09-07T08:18:00.1870705Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1871052Z     features = self.features(x)
2025-09-07T08:18:00.1871379Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1871744Z     new_features = layer(features)
2025-09-07T08:18:00.1872085Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1872463Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1872846Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1873328Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1873557Z 
2025-09-07T08:18:00.1873651Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1873998Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1874313Z     return mod(*inputs)
2025-09-07T08:18:00.1874624Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1875052Z     features = self.features(x)
2025-09-07T08:18:00.1875379Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1875726Z     new_features = layer(features)
2025-09-07T08:18:00.1876068Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1876477Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1876670Z 
2025-09-07T08:18:00.1876765Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1877109Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1877427Z     return mod(*inputs)
2025-09-07T08:18:00.1877734Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1878077Z     features = self.features(x)
2025-09-07T08:18:00.1878402Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1878747Z     new_features = layer(features)
2025-09-07T08:18:00.1879076Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1879542Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1879735Z 
2025-09-07T08:18:00.1879838Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1880190Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1880502Z     return mod(*inputs)
2025-09-07T08:18:00.1880812Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1881153Z     features = self.features(x)
2025-09-07T08:18:00.1881477Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1881828Z     new_features = layer(features)
2025-09-07T08:18:00.1882162Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1882530Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1882910Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1883279Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1883414Z 
2025-09-07T08:18:00.1883508Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1883850Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1884158Z     return mod(*inputs)
2025-09-07T08:18:00.1884465Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1884810Z     features = self.features(x)
2025-09-07T08:18:00.1885140Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1885484Z     new_features = layer(features)
2025-09-07T08:18:00.1885809Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1886181Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1886559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1887013Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1887237Z 
2025-09-07T08:18:00.1887335Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1887675Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1888068Z     return mod(*inputs)
2025-09-07T08:18:00.1888377Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1888719Z     features = self.features(x)
2025-09-07T08:18:00.1889038Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1889384Z     new_features = layer(features)
2025-09-07T08:18:00.1889717Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1890086Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1890462Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1890912Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1891140Z 
2025-09-07T08:18:00.1891234Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1891582Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1891897Z     return mod(*inputs)
2025-09-07T08:18:00.1892202Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1892543Z     features = self.features(x)
2025-09-07T08:18:00.1892947Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1893302Z     new_features = layer(features)
2025-09-07T08:18:00.1893628Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1894030Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1894219Z 
2025-09-07T08:18:00.1894310Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1894654Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1894970Z     return mod(*inputs)
2025-09-07T08:18:00.1895282Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1895623Z     features = self.features(x)
2025-09-07T08:18:00.1895951Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1896292Z     new_features = layer(features)
2025-09-07T08:18:00.1896618Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1897015Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1897199Z 
2025-09-07T08:18:00.1897274Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1897470Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1897661Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1897851Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1898040Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1898228Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.1898442Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1898925Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1899242Z     return mod(*inputs)
2025-09-07T08:18:00.1899551Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1899895Z     features = self.features(x)
2025-09-07T08:18:00.1900217Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T08:18:00.1900560Z     return torch.cat(features, 1)
2025-09-07T08:18:00.1900682Z 
2025-09-07T08:18:00.1900775Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1901274Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1901706Z     return mod(*inputs)
2025-09-07T08:18:00.1902022Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1902367Z     features = self.features(x)
2025-09-07T08:18:00.1902483Z 
2025-09-07T08:18:00.1902582Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1902930Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1903247Z     return mod(*inputs)
2025-09-07T08:18:00.1903552Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1903897Z     features = self.features(x)
2025-09-07T08:18:00.1904006Z 
2025-09-07T08:18:00.1904101Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1904448Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1904758Z     return mod(*inputs)
2025-09-07T08:18:00.1905069Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1905410Z     features = self.features(x)
2025-09-07T08:18:00.1905924Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1906289Z     new_features = layer(features)
2025-09-07T08:18:00.1906623Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1907001Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1907382Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1907841Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1908067Z 
2025-09-07T08:18:00.1908173Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1908516Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1908831Z     return mod(*inputs)
2025-09-07T08:18:00.1909140Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1909488Z     features = self.features(x)
2025-09-07T08:18:00.1909812Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1910154Z     new_features = layer(features)
2025-09-07T08:18:00.1910486Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1910893Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1911079Z 
2025-09-07T08:18:00.1911177Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1911521Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1911837Z     return mod(*inputs)
2025-09-07T08:18:00.1912143Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1912486Z     features = self.features(x)
2025-09-07T08:18:00.1912812Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1913154Z     new_features = layer(features)
2025-09-07T08:18:00.1913479Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1913870Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1914055Z 
2025-09-07T08:18:00.1914150Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1914488Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1914904Z     return mod(*inputs)
2025-09-07T08:18:00.1915220Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1915564Z     features = self.features(x)
2025-09-07T08:18:00.1915888Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1915972Z     new_features = layer(features)
2025-09-07T08:18:00.1916196Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1916297Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1916524Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1916608Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1916612Z 
2025-09-07T08:18:00.1916710Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1916925Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1916985Z     return mod(*inputs)
2025-09-07T08:18:00.1917203Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1917353Z     features = self.features(x)
2025-09-07T08:18:00.1917576Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1917645Z     new_features = layer(features)
2025-09-07T08:18:00.1917860Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1917951Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1918183Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1918349Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1918357Z 
2025-09-07T08:18:00.1918465Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1918659Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1918715Z     return mod(*inputs)
2025-09-07T08:18:00.1918944Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1919007Z     features = self.features(x)
2025-09-07T08:18:00.1919226Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1919293Z     new_features = layer(features)
2025-09-07T08:18:00.1919512Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1919606Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1919832Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1920000Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1920003Z 
2025-09-07T08:18:00.1920095Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1920306Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1920365Z     return mod(*inputs)
2025-09-07T08:18:00.1920581Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1920650Z     features = self.features(x)
2025-09-07T08:18:00.1920870Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1920945Z     new_features = layer(features)
2025-09-07T08:18:00.1921160Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1921355Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1921362Z 
2025-09-07T08:18:00.1921454Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1921645Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1921712Z     return mod(*inputs)
2025-09-07T08:18:00.1921930Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1921998Z     features = self.features(x)
2025-09-07T08:18:00.1922213Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1922277Z     new_features = layer(features)
2025-09-07T08:18:00.1922497Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1922635Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1922638Z 
2025-09-07T08:18:00.1922740Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1922935Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1922993Z     return mod(*inputs)
2025-09-07T08:18:00.1923276Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1923349Z     features = self.features(x)
2025-09-07T08:18:00.1923570Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1923634Z     new_features = layer(features)
2025-09-07T08:18:00.1923844Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1923940Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1924168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1924247Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1924250Z 
2025-09-07T08:18:00.1924344Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1924551Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1924609Z     return mod(*inputs)
2025-09-07T08:18:00.1924825Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1924889Z     features = self.features(x)
2025-09-07T08:18:00.1925107Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1925175Z     new_features = layer(features)
2025-09-07T08:18:00.1925396Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1925495Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1925724Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1925888Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1925893Z 
2025-09-07T08:18:00.1925988Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1926183Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1926255Z     return mod(*inputs)
2025-09-07T08:18:00.1926467Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1926529Z     features = self.features(x)
2025-09-07T08:18:00.1926742Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1926870Z     new_features = layer(features)
2025-09-07T08:18:00.1927095Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1927185Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1927413Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1927578Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1927582Z 
2025-09-07T08:18:00.1927674Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1927872Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1927941Z     return mod(*inputs)
2025-09-07T08:18:00.1928159Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1928225Z     features = self.features(x)
2025-09-07T08:18:00.1928443Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1928509Z     new_features = layer(features)
2025-09-07T08:18:00.1928722Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1928934Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1928937Z 
2025-09-07T08:18:00.1929032Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1929229Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1929295Z     return mod(*inputs)
2025-09-07T08:18:00.1929509Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1929574Z     features = self.features(x)
2025-09-07T08:18:00.1929787Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1929856Z     new_features = layer(features)
2025-09-07T08:18:00.1930076Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1930203Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1930208Z 
2025-09-07T08:18:00.1930308Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1930496Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1930568Z     return mod(*inputs)
2025-09-07T08:18:00.1930784Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1930846Z     features = self.features(x)
2025-09-07T08:18:00.1931069Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1931135Z     new_features = layer(features)
2025-09-07T08:18:00.1931353Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1931443Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1931683Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1931765Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1931768Z 
2025-09-07T08:18:00.1931859Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1932054Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1932134Z     return mod(*inputs)
2025-09-07T08:18:00.1932353Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1932419Z     features = self.features(x)
2025-09-07T08:18:00.1932699Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1932767Z     new_features = layer(features)
2025-09-07T08:18:00.1932980Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1933075Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1933306Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1933469Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1933473Z 
2025-09-07T08:18:00.1933569Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1933759Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1933822Z     return mod(*inputs)
2025-09-07T08:18:00.1934039Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1934106Z     features = self.features(x)
2025-09-07T08:18:00.1934337Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1934400Z     new_features = layer(features)
2025-09-07T08:18:00.1934679Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1934771Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1934996Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1935179Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1935183Z 
2025-09-07T08:18:00.1935277Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1935466Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1935528Z     return mod(*inputs)
2025-09-07T08:18:00.1935746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1935809Z     features = self.features(x)
2025-09-07T08:18:00.1936042Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1936114Z     new_features = layer(features)
2025-09-07T08:18:00.1936327Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1936456Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1936459Z 
2025-09-07T08:18:00.1936552Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1936748Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1936820Z     return mod(*inputs)
2025-09-07T08:18:00.1937036Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1937100Z     features = self.features(x)
2025-09-07T08:18:00.1937317Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1937384Z     new_features = layer(features)
2025-09-07T08:18:00.1937600Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1937723Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1937726Z 
2025-09-07T08:18:00.1937823Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1938014Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1938075Z     return mod(*inputs)
2025-09-07T08:18:00.1938291Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1938418Z     features = self.features(x)
2025-09-07T08:18:00.1938635Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1938697Z     new_features = layer(features)
2025-09-07T08:18:00.1938914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1939005Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1939241Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1939329Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1939333Z 
2025-09-07T08:18:00.1939425Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1939624Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1939684Z     return mod(*inputs)
2025-09-07T08:18:00.1939907Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1939974Z     features = self.features(x)
2025-09-07T08:18:00.1940303Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1940385Z     new_features = layer(features)
2025-09-07T08:18:00.1940608Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1940703Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1940929Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1941093Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1941097Z 
2025-09-07T08:18:00.1941205Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1941389Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1941451Z     return mod(*inputs)
2025-09-07T08:18:00.1941670Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1941733Z     features = self.features(x)
2025-09-07T08:18:00.1941954Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1942017Z     new_features = layer(features)
2025-09-07T08:18:00.1942247Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1942334Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1942561Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1942724Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1942727Z 
2025-09-07T08:18:00.1942821Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1943015Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1943081Z     return mod(*inputs)
2025-09-07T08:18:00.1943307Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1943368Z     features = self.features(x)
2025-09-07T08:18:00.1943584Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1943650Z     new_features = layer(features)
2025-09-07T08:18:00.1943866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1943998Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1944062Z 
2025-09-07T08:18:00.1944160Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1944364Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1944423Z     return mod(*inputs)
2025-09-07T08:18:00.1944658Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1944734Z     features = self.features(x)
2025-09-07T08:18:00.1944952Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1945020Z     new_features = layer(features)
2025-09-07T08:18:00.1945237Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1945362Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1945365Z 
2025-09-07T08:18:00.1945470Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1945718Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1945782Z     return mod(*inputs)
2025-09-07T08:18:00.1946001Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1946136Z     features = self.features(x)
2025-09-07T08:18:00.1946384Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1946477Z     new_features = layer(features)
2025-09-07T08:18:00.1946735Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1946860Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1947123Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1947208Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1947211Z 
2025-09-07T08:18:00.1947307Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1947506Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1947565Z     return mod(*inputs)
2025-09-07T08:18:00.1947790Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1947861Z     features = self.features(x)
2025-09-07T08:18:00.1948075Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1948144Z     new_features = layer(features)
2025-09-07T08:18:00.1948359Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1948455Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1948693Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1948869Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1948877Z 
2025-09-07T08:18:00.1948971Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1949168Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1949231Z     return mod(*inputs)
2025-09-07T08:18:00.1949448Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1949524Z     features = self.features(x)
2025-09-07T08:18:00.1949739Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1949802Z     new_features = layer(features)
2025-09-07T08:18:00.1950016Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1950196Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1950441Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1950611Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1950614Z 
2025-09-07T08:18:00.1950707Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1950903Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1950963Z     return mod(*inputs)
2025-09-07T08:18:00.1951180Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1951254Z     features = self.features(x)
2025-09-07T08:18:00.1951475Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1951546Z     new_features = layer(features)
2025-09-07T08:18:00.1951760Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1951891Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1951894Z 
2025-09-07T08:18:00.1952057Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1952258Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1952314Z     return mod(*inputs)
2025-09-07T08:18:00.1952528Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1952604Z     features = self.features(x)
2025-09-07T08:18:00.1952819Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1952887Z     new_features = layer(features)
2025-09-07T08:18:00.1953107Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1953232Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1953249Z 
2025-09-07T08:18:00.1953344Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1953534Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1953594Z     return mod(*inputs)
2025-09-07T08:18:00.1953809Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1953876Z     features = self.features(x)
2025-09-07T08:18:00.1954090Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1954156Z     new_features = layer(features)
2025-09-07T08:18:00.1954382Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1954478Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1954705Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1954782Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1954785Z 
2025-09-07T08:18:00.1954878Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1955082Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1955142Z     return mod(*inputs)
2025-09-07T08:18:00.1955363Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1955424Z     features = self.features(x)
2025-09-07T08:18:00.1955640Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1955773Z     new_features = layer(features)
2025-09-07T08:18:00.1955997Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1956099Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1956326Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1956493Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1956497Z 
2025-09-07T08:18:00.1956590Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1956793Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1956854Z     return mod(*inputs)
2025-09-07T08:18:00.1957069Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1957138Z     features = self.features(x)
2025-09-07T08:18:00.1957358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1957423Z     new_features = layer(features)
2025-09-07T08:18:00.1957638Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1957789Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1958020Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1958183Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1958186Z 
2025-09-07T08:18:00.1958285Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1958479Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1958536Z     return mod(*inputs)
2025-09-07T08:18:00.1958761Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1958827Z     features = self.features(x)
2025-09-07T08:18:00.1959073Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1959138Z     new_features = layer(features)
2025-09-07T08:18:00.1959356Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1959485Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1959488Z 
2025-09-07T08:18:00.1959582Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1959775Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1959831Z     return mod(*inputs)
2025-09-07T08:18:00.1960045Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1960132Z     features = self.features(x)
2025-09-07T08:18:00.1960346Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1960413Z     new_features = layer(features)
2025-09-07T08:18:00.1960630Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1960763Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1960766Z 
2025-09-07T08:18:00.1960856Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1961046Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1961111Z     return mod(*inputs)
2025-09-07T08:18:00.1961326Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1961397Z     features = self.features(x)
2025-09-07T08:18:00.1961682Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1961747Z     new_features = layer(features)
2025-09-07T08:18:00.1961964Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1962059Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1962286Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1962361Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1962365Z 
2025-09-07T08:18:00.1962455Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1962660Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1962718Z     return mod(*inputs)
2025-09-07T08:18:00.1962938Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1963004Z     features = self.features(x)
2025-09-07T08:18:00.1963221Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1963284Z     new_features = layer(features)
2025-09-07T08:18:00.1963559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1963657Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1963881Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1964048Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1964052Z 
2025-09-07T08:18:00.1964143Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1964331Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1964401Z     return mod(*inputs)
2025-09-07T08:18:00.1964616Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1964683Z     features = self.features(x)
2025-09-07T08:18:00.1964902Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1964965Z     new_features = layer(features)
2025-09-07T08:18:00.1965182Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1965273Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1965501Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1965663Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1965670Z 
2025-09-07T08:18:00.1965770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1965963Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1966021Z     return mod(*inputs)
2025-09-07T08:18:00.1966244Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1966307Z     features = self.features(x)
2025-09-07T08:18:00.1966525Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1966586Z     new_features = layer(features)
2025-09-07T08:18:00.1966803Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1966931Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1966935Z 
2025-09-07T08:18:00.1967026Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1967289Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1967348Z     return mod(*inputs)
2025-09-07T08:18:00.1967567Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1967629Z     features = self.features(x)
2025-09-07T08:18:00.1967845Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1967914Z     new_features = layer(features)
2025-09-07T08:18:00.1968127Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1968255Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1968258Z 
2025-09-07T08:18:00.1968350Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1968542Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1968607Z     return mod(*inputs)
2025-09-07T08:18:00.1968825Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1968893Z     features = self.features(x)
2025-09-07T08:18:00.1969171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1969237Z     new_features = layer(features)
2025-09-07T08:18:00.1969454Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1969542Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1969770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1969855Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1969859Z 
2025-09-07T08:18:00.1969955Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1970151Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1970210Z     return mod(*inputs)
2025-09-07T08:18:00.1970428Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1970490Z     features = self.features(x)
2025-09-07T08:18:00.1970714Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1970779Z     new_features = layer(features)
2025-09-07T08:18:00.1970996Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1971095Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1971318Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1971493Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1971496Z 
2025-09-07T08:18:00.1971588Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1971784Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1971841Z     return mod(*inputs)
2025-09-07T08:18:00.1972061Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1972133Z     features = self.features(x)
2025-09-07T08:18:00.1972346Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1972416Z     new_features = layer(features)
2025-09-07T08:18:00.1972631Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1972724Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1973056Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1973215Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1973219Z 
2025-09-07T08:18:00.1973323Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1973520Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1973583Z     return mod(*inputs)
2025-09-07T08:18:00.1973806Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1973868Z     features = self.features(x)
2025-09-07T08:18:00.1974086Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1974151Z     new_features = layer(features)
2025-09-07T08:18:00.1974373Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1974503Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1974506Z 
2025-09-07T08:18:00.1974600Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1974861Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1974921Z     return mod(*inputs)
2025-09-07T08:18:00.1975142Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1975205Z     features = self.features(x)
2025-09-07T08:18:00.1975420Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1975491Z     new_features = layer(features)
2025-09-07T08:18:00.1975704Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1975833Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1975836Z 
2025-09-07T08:18:00.1975929Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1976123Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1976191Z     return mod(*inputs)
2025-09-07T08:18:00.1976411Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1976483Z     features = self.features(x)
2025-09-07T08:18:00.1976701Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1976773Z     new_features = layer(features)
2025-09-07T08:18:00.1976985Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1977077Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1977313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1977389Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1977392Z 
2025-09-07T08:18:00.1977493Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1977684Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1977744Z     return mod(*inputs)
2025-09-07T08:18:00.1977968Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1978032Z     features = self.features(x)
2025-09-07T08:18:00.1978254Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1978317Z     new_features = layer(features)
2025-09-07T08:18:00.1978532Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1978694Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1978920Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1979088Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1979093Z 
2025-09-07T08:18:00.1979188Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1979394Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1979453Z     return mod(*inputs)
2025-09-07T08:18:00.1979671Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1979747Z     features = self.features(x)
2025-09-07T08:18:00.1980004Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1980132Z     new_features = layer(features)
2025-09-07T08:18:00.1980374Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1980494Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1980864Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1981060Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1981066Z 
2025-09-07T08:18:00.1981383Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1981607Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1981714Z     return mod(*inputs)
2025-09-07T08:18:00.1981994Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1982090Z     features = self.features(x)
2025-09-07T08:18:00.1982409Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1982551Z     new_features = layer(features)
2025-09-07T08:18:00.1982859Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1983019Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1983023Z 
2025-09-07T08:18:00.1983147Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1983387Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1983523Z     return mod(*inputs)
2025-09-07T08:18:00.1983824Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1983919Z     features = self.features(x)
2025-09-07T08:18:00.1984161Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1984290Z     new_features = layer(features)
2025-09-07T08:18:00.1984522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1984776Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1984779Z 
2025-09-07T08:18:00.1984910Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1985167Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1985254Z     return mod(*inputs)
2025-09-07T08:18:00.1985502Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1985716Z     features = self.features(x)
2025-09-07T08:18:00.1985988Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1986204Z     new_features = layer(features)
2025-09-07T08:18:00.1986459Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1986581Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1986898Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1987061Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1987064Z 
2025-09-07T08:18:00.1987234Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1987458Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1987571Z     return mod(*inputs)
2025-09-07T08:18:00.1987823Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1987917Z     features = self.features(x)
2025-09-07T08:18:00.1988255Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1988354Z     new_features = layer(features)
2025-09-07T08:18:00.1988633Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1988833Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1989103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1989357Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1989361Z 
2025-09-07T08:18:00.1989506Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1989763Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1989852Z     return mod(*inputs)
2025-09-07T08:18:00.1990148Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1990235Z     features = self.features(x)
2025-09-07T08:18:00.1990535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1990677Z     new_features = layer(features)
2025-09-07T08:18:00.1990932Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1991141Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1991401Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1991671Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1991676Z 
2025-09-07T08:18:00.1991824Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1992051Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1992184Z     return mod(*inputs)
2025-09-07T08:18:00.1992436Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1992545Z     features = self.features(x)
2025-09-07T08:18:00.1992840Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1992952Z     new_features = layer(features)
2025-09-07T08:18:00.1993253Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1993413Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1993417Z 
2025-09-07T08:18:00.1993570Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1993786Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1994029Z     return mod(*inputs)
2025-09-07T08:18:00.1994291Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1994384Z     features = self.features(x)
2025-09-07T08:18:00.1994658Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1994756Z     new_features = layer(features)
2025-09-07T08:18:00.1995062Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.1995248Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.1995252Z 
2025-09-07T08:18:00.1995406Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1995663Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1995751Z     return mod(*inputs)
2025-09-07T08:18:00.1996012Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1996146Z     features = self.features(x)
2025-09-07T08:18:00.1996447Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1996544Z     new_features = layer(features)
2025-09-07T08:18:00.1996855Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1997012Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1997258Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.1997463Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.1997467Z 
2025-09-07T08:18:00.1997595Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.1997852Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.1997948Z     return mod(*inputs)
2025-09-07T08:18:00.1998198Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.1998366Z     features = self.features(x)
2025-09-07T08:18:00.1998632Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.1998918Z     new_features = layer(features)
2025-09-07T08:18:00.1999165Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.1999297Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.1999584Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.1999830Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.1999833Z 
2025-09-07T08:18:00.2000039Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2000265Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2000383Z     return mod(*inputs)
2025-09-07T08:18:00.2000644Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2000726Z     features = self.features(x)
2025-09-07T08:18:00.2001062Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2001157Z     new_features = layer(features)
2025-09-07T08:18:00.2001430Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2001564Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2001820Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2002200Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2002203Z 
2025-09-07T08:18:00.2002342Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2002591Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2002695Z     return mod(*inputs)
2025-09-07T08:18:00.2002972Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2003067Z     features = self.features(x)
2025-09-07T08:18:00.2003364Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2003498Z     new_features = layer(features)
2025-09-07T08:18:00.2003754Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2003941Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2003949Z 
2025-09-07T08:18:00.2004073Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2004352Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2004485Z     return mod(*inputs)
2025-09-07T08:18:00.2004836Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2004962Z     features = self.features(x)
2025-09-07T08:18:00.2005212Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2005320Z     new_features = layer(features)
2025-09-07T08:18:00.2005611Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2005793Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2005797Z 
2025-09-07T08:18:00.2005959Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2006182Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2006300Z     return mod(*inputs)
2025-09-07T08:18:00.2006538Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2006729Z     features = self.features(x)
2025-09-07T08:18:00.2006973Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2007069Z     new_features = layer(features)
2025-09-07T08:18:00.2007341Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2007465Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2007806Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2007942Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2007946Z 
2025-09-07T08:18:00.2008070Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2008321Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2008413Z     return mod(*inputs)
2025-09-07T08:18:00.2008678Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2008877Z     features = self.features(x)
2025-09-07T08:18:00.2009164Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2009257Z     new_features = layer(features)
2025-09-07T08:18:00.2009499Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2009656Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2009982Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2010276Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2010280Z 
2025-09-07T08:18:00.2010404Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2010631Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2010753Z     return mod(*inputs)
2025-09-07T08:18:00.2011013Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2011167Z     features = self.features(x)
2025-09-07T08:18:00.2011425Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2011544Z     new_features = layer(features)
2025-09-07T08:18:00.2011789Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2011928Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2012204Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2012501Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2012505Z 
2025-09-07T08:18:00.2012675Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2012904Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2013003Z     return mod(*inputs)
2025-09-07T08:18:00.2013315Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2013395Z     features = self.features(x)
2025-09-07T08:18:00.2013749Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2013846Z     new_features = layer(features)
2025-09-07T08:18:00.2014140Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2014296Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2014299Z 
2025-09-07T08:18:00.2014423Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2014708Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2014807Z     return mod(*inputs)
2025-09-07T08:18:00.2015098Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2015189Z     features = self.features(x)
2025-09-07T08:18:00.2015430Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2015539Z     new_features = layer(features)
2025-09-07T08:18:00.2015826Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2016039Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2016042Z 
2025-09-07T08:18:00.2016167Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2016420Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2016509Z     return mod(*inputs)
2025-09-07T08:18:00.2016742Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2016917Z     features = self.features(x)
2025-09-07T08:18:00.2017172Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2017335Z     new_features = layer(features)
2025-09-07T08:18:00.2017578Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2017767Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2018082Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2018213Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2018220Z 
2025-09-07T08:18:00.2018378Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2018595Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2018709Z     return mod(*inputs)
2025-09-07T08:18:00.2018942Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2019088Z     features = self.features(x)
2025-09-07T08:18:00.2019376Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2019473Z     new_features = layer(features)
2025-09-07T08:18:00.2019746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2019866Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2020248Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2020464Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2020469Z 
2025-09-07T08:18:00.2020596Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2020852Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2020938Z     return mod(*inputs)
2025-09-07T08:18:00.2021218Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2021355Z     features = self.features(x)
2025-09-07T08:18:00.2021619Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2021775Z     new_features = layer(features)
2025-09-07T08:18:00.2022022Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2022192Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2022436Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2022717Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2022719Z 
2025-09-07T08:18:00.2022845Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2023068Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2023200Z     return mod(*inputs)
2025-09-07T08:18:00.2023452Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2023608Z     features = self.features(x)
2025-09-07T08:18:00.2023866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2023958Z     new_features = layer(features)
2025-09-07T08:18:00.2024249Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2024407Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2024410Z 
2025-09-07T08:18:00.2024549Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2024819Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2024951Z     return mod(*inputs)
2025-09-07T08:18:00.2025212Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2025382Z     features = self.features(x)
2025-09-07T08:18:00.2025733Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2025815Z     new_features = layer(features)
2025-09-07T08:18:00.2026189Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2026364Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2026367Z 
2025-09-07T08:18:00.2026518Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2026739Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2026826Z     return mod(*inputs)
2025-09-07T08:18:00.2027136Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2027243Z     features = self.features(x)
2025-09-07T08:18:00.2027536Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2027629Z     new_features = layer(features)
2025-09-07T08:18:00.2027874Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2028081Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2028412Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2028573Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2028578Z 
2025-09-07T08:18:00.2028699Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2028949Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2029036Z     return mod(*inputs)
2025-09-07T08:18:00.2029270Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2029464Z     features = self.features(x)
2025-09-07T08:18:00.2029710Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2029828Z     new_features = layer(features)
2025-09-07T08:18:00.2030078Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2030199Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2030561Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2030764Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2030769Z 
2025-09-07T08:18:00.2030917Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2031136Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2031255Z     return mod(*inputs)
2025-09-07T08:18:00.2031503Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2031640Z     features = self.features(x)
2025-09-07T08:18:00.2031934Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2032027Z     new_features = layer(features)
2025-09-07T08:18:00.2032321Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2032458Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2032700Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2032983Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2033053Z 
2025-09-07T08:18:00.2033178Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2033436Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2033537Z     return mod(*inputs)
2025-09-07T08:18:00.2033804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2033934Z     features = self.features(x)
2025-09-07T08:18:00.2034198Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2034321Z     new_features = layer(features)
2025-09-07T08:18:00.2034582Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2034800Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2034803Z 
2025-09-07T08:18:00.2034910Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2035216Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2035303Z     return mod(*inputs)
2025-09-07T08:18:00.2035551Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2035754Z     features = self.features(x)
2025-09-07T08:18:00.2036001Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2036149Z     new_features = layer(features)
2025-09-07T08:18:00.2036407Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2036576Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2036611Z 
2025-09-07T08:18:00.2036733Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2036959Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2037066Z     return mod(*inputs)
2025-09-07T08:18:00.2037351Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2037498Z     features = self.features(x)
2025-09-07T08:18:00.2037749Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2037842Z     new_features = layer(features)
2025-09-07T08:18:00.2038117Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2038226Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2038569Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2038677Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2038681Z 
2025-09-07T08:18:00.2038812Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2039110Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2039199Z     return mod(*inputs)
2025-09-07T08:18:00.2043849Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2043954Z     features = self.features(x)
2025-09-07T08:18:00.2044215Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2044288Z     new_features = layer(features)
2025-09-07T08:18:00.2044526Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2044627Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2044876Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2045150Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2045154Z 
2025-09-07T08:18:00.2045260Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2045473Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2045540Z     return mod(*inputs)
2025-09-07T08:18:00.2045776Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2045840Z     features = self.features(x)
2025-09-07T08:18:00.2046070Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2046134Z     new_features = layer(features)
2025-09-07T08:18:00.2046358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2046458Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2046689Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2046861Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2046864Z 
2025-09-07T08:18:00.2046962Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2047247Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2047311Z     return mod(*inputs)
2025-09-07T08:18:00.2047534Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2047604Z     features = self.features(x)
2025-09-07T08:18:00.2047830Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2047897Z     new_features = layer(features)
2025-09-07T08:18:00.2048113Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2048254Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2048257Z 
2025-09-07T08:18:00.2048357Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2048557Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2048621Z     return mod(*inputs)
2025-09-07T08:18:00.2048840Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2048908Z     features = self.features(x)
2025-09-07T08:18:00.2049128Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2049192Z     new_features = layer(features)
2025-09-07T08:18:00.2049412Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2049538Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2049541Z 
2025-09-07T08:18:00.2049636Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2049827Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2049886Z     return mod(*inputs)
2025-09-07T08:18:00.2050100Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2050161Z     features = self.features(x)
2025-09-07T08:18:00.2050380Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2050442Z     new_features = layer(features)
2025-09-07T08:18:00.2050659Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2050756Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2051050Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2051138Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2051141Z 
2025-09-07T08:18:00.2051235Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2051431Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2051496Z     return mod(*inputs)
2025-09-07T08:18:00.2051715Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2051783Z     features = self.features(x)
2025-09-07T08:18:00.2051999Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2052062Z     new_features = layer(features)
2025-09-07T08:18:00.2052279Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2052374Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2052602Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2052826Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2052829Z 
2025-09-07T08:18:00.2052928Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2053120Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2053176Z     return mod(*inputs)
2025-09-07T08:18:00.2053396Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2053457Z     features = self.features(x)
2025-09-07T08:18:00.2053678Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2053745Z     new_features = layer(features)
2025-09-07T08:18:00.2053960Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2054054Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2054280Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2054443Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2054446Z 
2025-09-07T08:18:00.2054537Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2054729Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2054787Z     return mod(*inputs)
2025-09-07T08:18:00.2055003Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2055075Z     features = self.features(x)
2025-09-07T08:18:00.2055288Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2055354Z     new_features = layer(features)
2025-09-07T08:18:00.2055567Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2055696Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2055699Z 
2025-09-07T08:18:00.2055792Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2055987Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2056047Z     return mod(*inputs)
2025-09-07T08:18:00.2056262Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2056324Z     features = self.features(x)
2025-09-07T08:18:00.2056549Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2056676Z     new_features = layer(features)
2025-09-07T08:18:00.2056893Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2057015Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2057019Z 
2025-09-07T08:18:00.2057117Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2057305Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2057362Z     return mod(*inputs)
2025-09-07T08:18:00.2057583Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2057644Z     features = self.features(x)
2025-09-07T08:18:00.2057863Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2057938Z     new_features = layer(features)
2025-09-07T08:18:00.2058152Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2058246Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2058533Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2058614Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2058617Z 
2025-09-07T08:18:00.2058711Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2058908Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2058966Z     return mod(*inputs)
2025-09-07T08:18:00.2059180Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2059246Z     features = self.features(x)
2025-09-07T08:18:00.2059466Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2059530Z     new_features = layer(features)
2025-09-07T08:18:00.2059746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2059838Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2060065Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2060225Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2060229Z 
2025-09-07T08:18:00.2060328Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2060515Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2060571Z     return mod(*inputs)
2025-09-07T08:18:00.2060793Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2060854Z     features = self.features(x)
2025-09-07T08:18:00.2061081Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2061146Z     new_features = layer(features)
2025-09-07T08:18:00.2061371Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2061463Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2061704Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2061875Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2061878Z 
2025-09-07T08:18:00.2061973Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2062180Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2062306Z     return mod(*inputs)
2025-09-07T08:18:00.2062540Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2062616Z     features = self.features(x)
2025-09-07T08:18:00.2062840Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2062911Z     new_features = layer(features)
2025-09-07T08:18:00.2063135Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2063268Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2063276Z 
2025-09-07T08:18:00.2063379Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2063579Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2063644Z     return mod(*inputs)
2025-09-07T08:18:00.2063872Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2063939Z     features = self.features(x)
2025-09-07T08:18:00.2064224Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2064292Z     new_features = layer(features)
2025-09-07T08:18:00.2064516Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2064644Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2064647Z 
2025-09-07T08:18:00.2064749Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2064948Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2065007Z     return mod(*inputs)
2025-09-07T08:18:00.2065240Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2065305Z     features = self.features(x)
2025-09-07T08:18:00.2065626Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2065694Z     new_features = layer(features)
2025-09-07T08:18:00.2065917Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2066019Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2066249Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2066334Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2066337Z 
2025-09-07T08:18:00.2066432Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2066631Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2066694Z     return mod(*inputs)
2025-09-07T08:18:00.2066924Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2066990Z     features = self.features(x)
2025-09-07T08:18:00.2067214Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2067281Z     new_features = layer(features)
2025-09-07T08:18:00.2067501Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2067594Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2067827Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2067996Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2068088Z 
2025-09-07T08:18:00.2068186Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2068378Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2068442Z     return mod(*inputs)
2025-09-07T08:18:00.2068669Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2068733Z     features = self.features(x)
2025-09-07T08:18:00.2068957Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2069019Z     new_features = layer(features)
2025-09-07T08:18:00.2069240Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2069331Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2069558Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2069729Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2069732Z 
2025-09-07T08:18:00.2069826Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2070028Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2070148Z     return mod(*inputs)
2025-09-07T08:18:00.2070375Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2070437Z     features = self.features(x)
2025-09-07T08:18:00.2070659Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2070726Z     new_features = layer(features)
2025-09-07T08:18:00.2070942Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2071072Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2071081Z 
2025-09-07T08:18:00.2071176Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2071370Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2071433Z     return mod(*inputs)
2025-09-07T08:18:00.2071652Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2071719Z     features = self.features(x)
2025-09-07T08:18:00.2071940Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2072003Z     new_features = layer(features)
2025-09-07T08:18:00.2072221Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2072345Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2072352Z 
2025-09-07T08:18:00.2072449Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2072643Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2072705Z     return mod(*inputs)
2025-09-07T08:18:00.2072922Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2072985Z     features = self.features(x)
2025-09-07T08:18:00.2073204Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2073266Z     new_features = layer(features)
2025-09-07T08:18:00.2073485Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2073577Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2073803Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2073945Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2073949Z 
2025-09-07T08:18:00.2074039Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2074230Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2074288Z     return mod(*inputs)
2025-09-07T08:18:00.2074510Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2074575Z     features = self.features(x)
2025-09-07T08:18:00.2074792Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2074858Z     new_features = layer(features)
2025-09-07T08:18:00.2075074Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2075167Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2075396Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2075556Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2075559Z 
2025-09-07T08:18:00.2075655Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2075906Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2075970Z     return mod(*inputs)
2025-09-07T08:18:00.2076188Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2076250Z     features = self.features(x)
2025-09-07T08:18:00.2076468Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2076530Z     new_features = layer(features)
2025-09-07T08:18:00.2076746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2076838Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2077064Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2077233Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2077236Z 
2025-09-07T08:18:00.2077329Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2077524Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2077581Z     return mod(*inputs)
2025-09-07T08:18:00.2077799Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2077861Z     features = self.features(x)
2025-09-07T08:18:00.2078079Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2078147Z     new_features = layer(features)
2025-09-07T08:18:00.2078360Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2078489Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2078492Z 
2025-09-07T08:18:00.2078584Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2078773Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2078838Z     return mod(*inputs)
2025-09-07T08:18:00.2079053Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2079117Z     features = self.features(x)
2025-09-07T08:18:00.2079332Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2079477Z     new_features = layer(features)
2025-09-07T08:18:00.2079692Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2079814Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2079818Z 
2025-09-07T08:18:00.2079915Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2080110Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2080171Z     return mod(*inputs)
2025-09-07T08:18:00.2080387Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2080450Z     features = self.features(x)
2025-09-07T08:18:00.2080673Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2080735Z     new_features = layer(features)
2025-09-07T08:18:00.2080956Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2081051Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2081275Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2081419Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2081422Z 
2025-09-07T08:18:00.2081515Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2081709Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2081770Z     return mod(*inputs)
2025-09-07T08:18:00.2081994Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2082057Z     features = self.features(x)
2025-09-07T08:18:00.2082272Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2082345Z     new_features = layer(features)
2025-09-07T08:18:00.2082561Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2082656Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2082881Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2083043Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2083046Z 
2025-09-07T08:18:00.2083145Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2083338Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2083400Z     return mod(*inputs)
2025-09-07T08:18:00.2083615Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2083682Z     features = self.features(x)
2025-09-07T08:18:00.2083903Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2083966Z     new_features = layer(features)
2025-09-07T08:18:00.2084183Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2084276Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2084508Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2084671Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2084674Z 
2025-09-07T08:18:00.2084767Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2084964Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2085022Z     return mod(*inputs)
2025-09-07T08:18:00.2085307Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2085370Z     features = self.features(x)
2025-09-07T08:18:00.2085581Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2085657Z     new_features = layer(features)
2025-09-07T08:18:00.2085872Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2086001Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2086005Z 
2025-09-07T08:18:00.2086099Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2086292Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2086351Z     return mod(*inputs)
2025-09-07T08:18:00.2086564Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2086631Z     features = self.features(x)
2025-09-07T08:18:00.2086846Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2086912Z     new_features = layer(features)
2025-09-07T08:18:00.2087191Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2087317Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2087319Z 
2025-09-07T08:18:00.2087414Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2087607Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2087669Z     return mod(*inputs)
2025-09-07T08:18:00.2087885Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2087951Z     features = self.features(x)
2025-09-07T08:18:00.2088168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2088234Z     new_features = layer(features)
2025-09-07T08:18:00.2088450Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2088542Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2088773Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2088848Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2088851Z 
2025-09-07T08:18:00.2088941Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2089133Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2089194Z     return mod(*inputs)
2025-09-07T08:18:00.2089411Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2089478Z     features = self.features(x)
2025-09-07T08:18:00.2089690Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2089755Z     new_features = layer(features)
2025-09-07T08:18:00.2089969Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2090062Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2090288Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2090452Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2090458Z 
2025-09-07T08:18:00.2090550Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2090742Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2090887Z     return mod(*inputs)
2025-09-07T08:18:00.2091101Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2091171Z     features = self.features(x)
2025-09-07T08:18:00.2091391Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2091452Z     new_features = layer(features)
2025-09-07T08:18:00.2091671Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2091762Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2091991Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2092155Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2092161Z 
2025-09-07T08:18:00.2092254Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2092451Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2092506Z     return mod(*inputs)
2025-09-07T08:18:00.2092781Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2092845Z     features = self.features(x)
2025-09-07T08:18:00.2093067Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2093128Z     new_features = layer(features)
2025-09-07T08:18:00.2093341Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2093469Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2093472Z 
2025-09-07T08:18:00.2093565Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2093764Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2093822Z     return mod(*inputs)
2025-09-07T08:18:00.2094036Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2094107Z     features = self.features(x)
2025-09-07T08:18:00.2094322Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2094387Z     new_features = layer(features)
2025-09-07T08:18:00.2094599Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2094724Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2094730Z 
2025-09-07T08:18:00.2094823Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2095013Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2095077Z     return mod(*inputs)
2025-09-07T08:18:00.2095288Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2095353Z     features = self.features(x)
2025-09-07T08:18:00.2095571Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2095637Z     new_features = layer(features)
2025-09-07T08:18:00.2095853Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2095942Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2096171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2096245Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2096249Z 
2025-09-07T08:18:00.2096403Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2096593Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2096650Z     return mod(*inputs)
2025-09-07T08:18:00.2096871Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2096933Z     features = self.features(x)
2025-09-07T08:18:00.2097149Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2097212Z     new_features = layer(features)
2025-09-07T08:18:00.2097429Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2097519Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2097750Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2097913Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2097916Z 
2025-09-07T08:18:00.2098013Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2098206Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2098326Z     return mod(*inputs)
2025-09-07T08:18:00.2098550Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2098611Z     features = self.features(x)
2025-09-07T08:18:00.2098992Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2099060Z     new_features = layer(features)
2025-09-07T08:18:00.2099272Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2099368Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2099598Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2099764Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2099768Z 
2025-09-07T08:18:00.2099870Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2100066Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2100125Z     return mod(*inputs)
2025-09-07T08:18:00.2100339Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2100406Z     features = self.features(x)
2025-09-07T08:18:00.2100618Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2100684Z     new_features = layer(features)
2025-09-07T08:18:00.2100902Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2101026Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2101029Z 
2025-09-07T08:18:00.2101130Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2101321Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2101381Z     return mod(*inputs)
2025-09-07T08:18:00.2101598Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2101661Z     features = self.features(x)
2025-09-07T08:18:00.2101880Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2101944Z     new_features = layer(features)
2025-09-07T08:18:00.2102158Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2102409Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2102411Z 
2025-09-07T08:18:00.2102510Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2102701Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2102763Z     return mod(*inputs)
2025-09-07T08:18:00.2102984Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2103048Z     features = self.features(x)
2025-09-07T08:18:00.2103264Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2103328Z     new_features = layer(features)
2025-09-07T08:18:00.2103542Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2103637Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2103866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2103944Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2103947Z 
2025-09-07T08:18:00.2104039Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2104322Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2104384Z     return mod(*inputs)
2025-09-07T08:18:00.2104598Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2104664Z     features = self.features(x)
2025-09-07T08:18:00.2104879Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2104943Z     new_features = layer(features)
2025-09-07T08:18:00.2105156Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2105252Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2105477Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2105706Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2105709Z 
2025-09-07T08:18:00.2105805Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2105991Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2106048Z     return mod(*inputs)
2025-09-07T08:18:00.2106271Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2106333Z     features = self.features(x)
2025-09-07T08:18:00.2106552Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2106616Z     new_features = layer(features)
2025-09-07T08:18:00.2106829Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2106925Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2107149Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2107312Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2107314Z 
2025-09-07T08:18:00.2107404Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2107601Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2107659Z     return mod(*inputs)
2025-09-07T08:18:00.2107873Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2108010Z     features = self.features(x)
2025-09-07T08:18:00.2108223Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2108292Z     new_features = layer(features)
2025-09-07T08:18:00.2108507Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2108632Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2108637Z 
2025-09-07T08:18:00.2108732Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2108918Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2108979Z     return mod(*inputs)
2025-09-07T08:18:00.2109188Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2109255Z     features = self.features(x)
2025-09-07T08:18:00.2109477Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2109540Z     new_features = layer(features)
2025-09-07T08:18:00.2109751Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2109950Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2109954Z 
2025-09-07T08:18:00.2110034Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2110106Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2110179Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2110250Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2110319Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2110389Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2110482Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2110677Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2110743Z     return mod(*inputs)
2025-09-07T08:18:00.2110966Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2111028Z     features = self.features(x)
2025-09-07T08:18:00.2111246Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T08:18:00.2111312Z     return torch.cat(features, 1)
2025-09-07T08:18:00.2111315Z 
2025-09-07T08:18:00.2111407Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2111598Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2111661Z     return mod(*inputs)
2025-09-07T08:18:00.2111872Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2111935Z     features = self.features(x)
2025-09-07T08:18:00.2111944Z 
2025-09-07T08:18:00.2112034Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2112225Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2112287Z     return mod(*inputs)
2025-09-07T08:18:00.2112501Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2112568Z     features = self.features(x)
2025-09-07T08:18:00.2112571Z 
2025-09-07T08:18:00.2112665Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2112850Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2112910Z     return mod(*inputs)
2025-09-07T08:18:00.2113130Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2113195Z     features = self.features(x)
2025-09-07T08:18:00.2113421Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2113546Z     new_features = layer(features)
2025-09-07T08:18:00.2113771Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2113863Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2114097Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2114259Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2114263Z 
2025-09-07T08:18:00.2114356Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2114548Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2114604Z     return mod(*inputs)
2025-09-07T08:18:00.2114827Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2114890Z     features = self.features(x)
2025-09-07T08:18:00.2115110Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2115172Z     new_features = layer(features)
2025-09-07T08:18:00.2115682Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2115814Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2115818Z 
2025-09-07T08:18:00.2115910Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2116105Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2116164Z     return mod(*inputs)
2025-09-07T08:18:00.2116378Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2116448Z     features = self.features(x)
2025-09-07T08:18:00.2116668Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2116739Z     new_features = layer(features)
2025-09-07T08:18:00.2116954Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2117080Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2117083Z 
2025-09-07T08:18:00.2117173Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2117361Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2117422Z     return mod(*inputs)
2025-09-07T08:18:00.2117633Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2117699Z     features = self.features(x)
2025-09-07T08:18:00.2117917Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2117983Z     new_features = layer(features)
2025-09-07T08:18:00.2118202Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2118295Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2118525Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2118601Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2118604Z 
2025-09-07T08:18:00.2118696Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2118891Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2118948Z     return mod(*inputs)
2025-09-07T08:18:00.2119167Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2119298Z     features = self.features(x)
2025-09-07T08:18:00.2119512Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2119580Z     new_features = layer(features)
2025-09-07T08:18:00.2119806Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2119897Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2120125Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2120300Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2120303Z 
2025-09-07T08:18:00.2120397Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2120589Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2120652Z     return mod(*inputs)
2025-09-07T08:18:00.2120868Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2120932Z     features = self.features(x)
2025-09-07T08:18:00.2121151Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2121321Z     new_features = layer(features)
2025-09-07T08:18:00.2121543Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2121635Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2121860Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2122023Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2122027Z 
2025-09-07T08:18:00.2122121Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2122310Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2122368Z     return mod(*inputs)
2025-09-07T08:18:00.2122587Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2122650Z     features = self.features(x)
2025-09-07T08:18:00.2122868Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2122932Z     new_features = layer(features)
2025-09-07T08:18:00.2123145Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2123275Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2123278Z 
2025-09-07T08:18:00.2123368Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2123562Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2123623Z     return mod(*inputs)
2025-09-07T08:18:00.2123843Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2123905Z     features = self.features(x)
2025-09-07T08:18:00.2124121Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2124190Z     new_features = layer(features)
2025-09-07T08:18:00.2124406Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2124528Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2124531Z 
2025-09-07T08:18:00.2124621Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2124815Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2124939Z     return mod(*inputs)
2025-09-07T08:18:00.2125155Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2125220Z     features = self.features(x)
2025-09-07T08:18:00.2125433Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2125500Z     new_features = layer(features)
2025-09-07T08:18:00.2125718Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2125809Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2126035Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2126109Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2126113Z 
2025-09-07T08:18:00.2126209Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2126404Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2126461Z     return mod(*inputs)
2025-09-07T08:18:00.2126680Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2126742Z     features = self.features(x)
2025-09-07T08:18:00.2127025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2127090Z     new_features = layer(features)
2025-09-07T08:18:00.2127304Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2127397Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2127621Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2127780Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2127787Z 
2025-09-07T08:18:00.2127875Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2128067Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2128124Z     return mod(*inputs)
2025-09-07T08:18:00.2128337Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2128404Z     features = self.features(x)
2025-09-07T08:18:00.2128615Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2128680Z     new_features = layer(features)
2025-09-07T08:18:00.2128891Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2128981Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2129209Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2129374Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2129377Z 
2025-09-07T08:18:00.2129471Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2129662Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2129721Z     return mod(*inputs)
2025-09-07T08:18:00.2129946Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2130007Z     features = self.features(x)
2025-09-07T08:18:00.2130225Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2130287Z     new_features = layer(features)
2025-09-07T08:18:00.2130499Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2130691Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2130695Z 
2025-09-07T08:18:00.2130785Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2130979Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2131038Z     return mod(*inputs)
2025-09-07T08:18:00.2131251Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2131313Z     features = self.features(x)
2025-09-07T08:18:00.2131526Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2131590Z     new_features = layer(features)
2025-09-07T08:18:00.2131804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2131930Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2131935Z 
2025-09-07T08:18:00.2132028Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2132215Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2132273Z     return mod(*inputs)
2025-09-07T08:18:00.2132563Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2132628Z     features = self.features(x)
2025-09-07T08:18:00.2132841Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2132907Z     new_features = layer(features)
2025-09-07T08:18:00.2133119Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2133211Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2133445Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2133522Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2133525Z 
2025-09-07T08:18:00.2133620Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2133817Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2133874Z     return mod(*inputs)
2025-09-07T08:18:00.2134095Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2134155Z     features = self.features(x)
2025-09-07T08:18:00.2134371Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2134434Z     new_features = layer(features)
2025-09-07T08:18:00.2134646Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2134743Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2134967Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2135134Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2135137Z 
2025-09-07T08:18:00.2135228Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2135422Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2135477Z     return mod(*inputs)
2025-09-07T08:18:00.2135688Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2135758Z     features = self.features(x)
2025-09-07T08:18:00.2135971Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2136034Z     new_features = layer(features)
2025-09-07T08:18:00.2136314Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2136403Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2136633Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2136797Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2136800Z 
2025-09-07T08:18:00.2136894Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2137083Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2137143Z     return mod(*inputs)
2025-09-07T08:18:00.2137357Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2137418Z     features = self.features(x)
2025-09-07T08:18:00.2137638Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2137699Z     new_features = layer(features)
2025-09-07T08:18:00.2137914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2138096Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2138099Z 
2025-09-07T08:18:00.2138191Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2138390Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2138446Z     return mod(*inputs)
2025-09-07T08:18:00.2138663Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2138724Z     features = self.features(x)
2025-09-07T08:18:00.2138938Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2139007Z     new_features = layer(features)
2025-09-07T08:18:00.2139219Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2139345Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2139348Z 
2025-09-07T08:18:00.2139441Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2139633Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2139690Z     return mod(*inputs)
2025-09-07T08:18:00.2139903Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2139970Z     features = self.features(x)
2025-09-07T08:18:00.2140183Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2140250Z     new_features = layer(features)
2025-09-07T08:18:00.2140464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2140556Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2140784Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2140860Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2140863Z 
2025-09-07T08:18:00.2140958Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2141145Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2141202Z     return mod(*inputs)
2025-09-07T08:18:00.2141422Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2141483Z     features = self.features(x)
2025-09-07T08:18:00.2141701Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2141828Z     new_features = layer(features)
2025-09-07T08:18:00.2142043Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2142133Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2142358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2142523Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2142526Z 
2025-09-07T08:18:00.2142619Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2142815Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2142871Z     return mod(*inputs)
2025-09-07T08:18:00.2143082Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2143150Z     features = self.features(x)
2025-09-07T08:18:00.2143366Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2143432Z     new_features = layer(features)
2025-09-07T08:18:00.2143707Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2143799Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2144027Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2144187Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2144191Z 
2025-09-07T08:18:00.2144285Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2144472Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2144534Z     return mod(*inputs)
2025-09-07T08:18:00.2144747Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2144809Z     features = self.features(x)
2025-09-07T08:18:00.2145028Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2145090Z     new_features = layer(features)
2025-09-07T08:18:00.2145306Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2145432Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2145435Z 
2025-09-07T08:18:00.2145596Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2145791Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2145847Z     return mod(*inputs)
2025-09-07T08:18:00.2146067Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2146128Z     features = self.features(x)
2025-09-07T08:18:00.2146341Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2146409Z     new_features = layer(features)
2025-09-07T08:18:00.2146621Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2146749Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2146752Z 
2025-09-07T08:18:00.2146845Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2147042Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2147098Z     return mod(*inputs)
2025-09-07T08:18:00.2147313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2147451Z     features = self.features(x)
2025-09-07T08:18:00.2147663Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2147729Z     new_features = layer(features)
2025-09-07T08:18:00.2147945Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2148035Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2148262Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2148335Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2148338Z 
2025-09-07T08:18:00.2148431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2148615Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2148676Z     return mod(*inputs)
2025-09-07T08:18:00.2148887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2148949Z     features = self.features(x)
2025-09-07T08:18:00.2149162Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2149287Z     new_features = layer(features)
2025-09-07T08:18:00.2149505Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2149602Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2149828Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2149994Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2149997Z 
2025-09-07T08:18:00.2150089Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2150295Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2150354Z     return mod(*inputs)
2025-09-07T08:18:00.2150569Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2150634Z     features = self.features(x)
2025-09-07T08:18:00.2150852Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2150927Z     new_features = layer(features)
2025-09-07T08:18:00.2151147Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2151244Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2151472Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2151638Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2151643Z 
2025-09-07T08:18:00.2151741Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2151938Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2152003Z     return mod(*inputs)
2025-09-07T08:18:00.2152223Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2152288Z     features = self.features(x)
2025-09-07T08:18:00.2152510Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2152579Z     new_features = layer(features)
2025-09-07T08:18:00.2152808Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2152938Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2153019Z 
2025-09-07T08:18:00.2153121Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2153316Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2153374Z     return mod(*inputs)
2025-09-07T08:18:00.2153598Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2153662Z     features = self.features(x)
2025-09-07T08:18:00.2153881Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2153944Z     new_features = layer(features)
2025-09-07T08:18:00.2154160Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2154287Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2154290Z 
2025-09-07T08:18:00.2154379Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2154579Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2154638Z     return mod(*inputs)
2025-09-07T08:18:00.2154854Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2154981Z     features = self.features(x)
2025-09-07T08:18:00.2155201Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2155270Z     new_features = layer(features)
2025-09-07T08:18:00.2155484Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2155582Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2155807Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2155884Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2155891Z 
2025-09-07T08:18:00.2155990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2156179Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2156239Z     return mod(*inputs)
2025-09-07T08:18:00.2156458Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2156523Z     features = self.features(x)
2025-09-07T08:18:00.2156742Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2156806Z     new_features = layer(features)
2025-09-07T08:18:00.2157023Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2157115Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2157336Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2157503Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2157506Z 
2025-09-07T08:18:00.2157597Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2157788Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2157846Z     return mod(*inputs)
2025-09-07T08:18:00.2158063Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2158127Z     features = self.features(x)
2025-09-07T08:18:00.2158338Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2158406Z     new_features = layer(features)
2025-09-07T08:18:00.2158619Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2158779Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2159006Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2159168Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2159176Z 
2025-09-07T08:18:00.2159269Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2159459Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2159522Z     return mod(*inputs)
2025-09-07T08:18:00.2159736Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2159800Z     features = self.features(x)
2025-09-07T08:18:00.2160019Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2160084Z     new_features = layer(features)
2025-09-07T08:18:00.2160304Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2160428Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2160431Z 
2025-09-07T08:18:00.2160584Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2160784Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2160843Z     return mod(*inputs)
2025-09-07T08:18:00.2161065Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2161127Z     features = self.features(x)
2025-09-07T08:18:00.2161347Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2161412Z     new_features = layer(features)
2025-09-07T08:18:00.2161625Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2161755Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2161758Z 
2025-09-07T08:18:00.2161851Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2162043Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2162103Z     return mod(*inputs)
2025-09-07T08:18:00.2162318Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2162379Z     features = self.features(x)
2025-09-07T08:18:00.2162591Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2162661Z     new_features = layer(features)
2025-09-07T08:18:00.2162875Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2162971Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2163194Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2163268Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2163271Z 
2025-09-07T08:18:00.2163368Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2163559Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2163621Z     return mod(*inputs)
2025-09-07T08:18:00.2163837Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2163900Z     features = self.features(x)
2025-09-07T08:18:00.2164118Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2164184Z     new_features = layer(features)
2025-09-07T08:18:00.2164469Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2164559Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2164788Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2164954Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2164957Z 
2025-09-07T08:18:00.2165051Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2165243Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2165302Z     return mod(*inputs)
2025-09-07T08:18:00.2165519Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2165583Z     features = self.features(x)
2025-09-07T08:18:00.2165798Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2165869Z     new_features = layer(features)
2025-09-07T08:18:00.2166081Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2166239Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2166470Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2166637Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2166640Z 
2025-09-07T08:18:00.2166733Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2166922Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2166985Z     return mod(*inputs)
2025-09-07T08:18:00.2167204Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2167274Z     features = self.features(x)
2025-09-07T08:18:00.2167488Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2167552Z     new_features = layer(features)
2025-09-07T08:18:00.2167770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2167895Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2167898Z 
2025-09-07T08:18:00.2167992Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2168187Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2168245Z     return mod(*inputs)
2025-09-07T08:18:00.2168464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2168528Z     features = self.features(x)
2025-09-07T08:18:00.2168747Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2168809Z     new_features = layer(features)
2025-09-07T08:18:00.2169030Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2169172Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2169175Z 
2025-09-07T08:18:00.2169265Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2169463Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2169521Z     return mod(*inputs)
2025-09-07T08:18:00.2169741Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2169802Z     features = self.features(x)
2025-09-07T08:18:00.2170078Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2170146Z     new_features = layer(features)
2025-09-07T08:18:00.2170359Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2170454Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2170680Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2170756Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2170765Z 
2025-09-07T08:18:00.2170856Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2171047Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2171109Z     return mod(*inputs)
2025-09-07T08:18:00.2171323Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2171390Z     features = self.features(x)
2025-09-07T08:18:00.2171604Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2171669Z     new_features = layer(features)
2025-09-07T08:18:00.2171949Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2172044Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2172270Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2172433Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2172436Z 
2025-09-07T08:18:00.2172531Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2172722Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2172783Z     return mod(*inputs)
2025-09-07T08:18:00.2173000Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2173062Z     features = self.features(x)
2025-09-07T08:18:00.2173283Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2173345Z     new_features = layer(features)
2025-09-07T08:18:00.2173559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2173652Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2173879Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2174044Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2174047Z 
2025-09-07T08:18:00.2174139Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2174334Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2174399Z     return mod(*inputs)
2025-09-07T08:18:00.2174612Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2174680Z     features = self.features(x)
2025-09-07T08:18:00.2174890Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2174953Z     new_features = layer(features)
2025-09-07T08:18:00.2175168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2175290Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2175292Z 
2025-09-07T08:18:00.2175387Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2175579Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2175719Z     return mod(*inputs)
2025-09-07T08:18:00.2175932Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2175993Z     features = self.features(x)
2025-09-07T08:18:00.2176218Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2176286Z     new_features = layer(features)
2025-09-07T08:18:00.2176507Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2176632Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2176635Z 
2025-09-07T08:18:00.2176728Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2176924Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2176983Z     return mod(*inputs)
2025-09-07T08:18:00.2177213Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2177276Z     features = self.features(x)
2025-09-07T08:18:00.2177556Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2177624Z     new_features = layer(features)
2025-09-07T08:18:00.2177842Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2177939Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2178169Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2178248Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2178252Z 
2025-09-07T08:18:00.2178343Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2178540Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2178601Z     return mod(*inputs)
2025-09-07T08:18:00.2178821Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2178886Z     features = self.features(x)
2025-09-07T08:18:00.2179109Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2179171Z     new_features = layer(features)
2025-09-07T08:18:00.2179395Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2179498Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2179737Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2179907Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2179916Z 
2025-09-07T08:18:00.2180010Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2180201Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2180259Z     return mod(*inputs)
2025-09-07T08:18:00.2180486Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2180546Z     features = self.features(x)
2025-09-07T08:18:00.2180769Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2180834Z     new_features = layer(features)
2025-09-07T08:18:00.2181050Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2181144Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2181369Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2181598Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2181601Z 
2025-09-07T08:18:00.2181702Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2181899Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2181957Z     return mod(*inputs)
2025-09-07T08:18:00.2182172Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2182240Z     features = self.features(x)
2025-09-07T08:18:00.2182456Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2182525Z     new_features = layer(features)
2025-09-07T08:18:00.2182739Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2182866Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2182869Z 
2025-09-07T08:18:00.2182965Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2183153Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2183278Z     return mod(*inputs)
2025-09-07T08:18:00.2183492Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2183554Z     features = self.features(x)
2025-09-07T08:18:00.2183770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2183840Z     new_features = layer(features)
2025-09-07T08:18:00.2184076Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2184201Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2184208Z 
2025-09-07T08:18:00.2184307Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2184504Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2184561Z     return mod(*inputs)
2025-09-07T08:18:00.2184793Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2184857Z     features = self.features(x)
2025-09-07T08:18:00.2185081Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2185145Z     new_features = layer(features)
2025-09-07T08:18:00.2185363Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2185459Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2185744Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2185828Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2185831Z 
2025-09-07T08:18:00.2185924Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2186122Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2186184Z     return mod(*inputs)
2025-09-07T08:18:00.2186402Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2186470Z     features = self.features(x)
2025-09-07T08:18:00.2186681Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2186747Z     new_features = layer(features)
2025-09-07T08:18:00.2186965Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2187126Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2187359Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2187524Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2187527Z 
2025-09-07T08:18:00.2187631Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2187821Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2187879Z     return mod(*inputs)
2025-09-07T08:18:00.2188102Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2188164Z     features = self.features(x)
2025-09-07T08:18:00.2188387Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2188455Z     new_features = layer(features)
2025-09-07T08:18:00.2188667Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2188762Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2189047Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2189214Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2189217Z 
2025-09-07T08:18:00.2189308Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2189509Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2189570Z     return mod(*inputs)
2025-09-07T08:18:00.2189797Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2189866Z     features = self.features(x)
2025-09-07T08:18:00.2190088Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2190153Z     new_features = layer(features)
2025-09-07T08:18:00.2190369Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2190497Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2190500Z 
2025-09-07T08:18:00.2190599Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2190803Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2190866Z     return mod(*inputs)
2025-09-07T08:18:00.2191080Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2191147Z     features = self.features(x)
2025-09-07T08:18:00.2191367Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2191432Z     new_features = layer(features)
2025-09-07T08:18:00.2191652Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2191776Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2191778Z 
2025-09-07T08:18:00.2191875Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2192068Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2192128Z     return mod(*inputs)
2025-09-07T08:18:00.2192348Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2192409Z     features = self.features(x)
2025-09-07T08:18:00.2192627Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2192753Z     new_features = layer(features)
2025-09-07T08:18:00.2192967Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2193065Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2193292Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2193372Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2193375Z 
2025-09-07T08:18:00.2193467Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2193662Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2193721Z     return mod(*inputs)
2025-09-07T08:18:00.2193935Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2194005Z     features = self.features(x)
2025-09-07T08:18:00.2194215Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2194286Z     new_features = layer(features)
2025-09-07T08:18:00.2194499Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2194589Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2194900Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2195063Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2195065Z 
2025-09-07T08:18:00.2195159Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2195346Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2195404Z     return mod(*inputs)
2025-09-07T08:18:00.2195625Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2195692Z     features = self.features(x)
2025-09-07T08:18:00.2195911Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2195975Z     new_features = layer(features)
2025-09-07T08:18:00.2196196Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2196287Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2196512Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2196674Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2196677Z 
2025-09-07T08:18:00.2196772Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2196968Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2197029Z     return mod(*inputs)
2025-09-07T08:18:00.2197240Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2197306Z     features = self.features(x)
2025-09-07T08:18:00.2197525Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2197593Z     new_features = layer(features)
2025-09-07T08:18:00.2197804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2197929Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2197933Z 
2025-09-07T08:18:00.2198026Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2198217Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2198278Z     return mod(*inputs)
2025-09-07T08:18:00.2198562Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2198631Z     features = self.features(x)
2025-09-07T08:18:00.2198971Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2199040Z     new_features = layer(features)
2025-09-07T08:18:00.2199262Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2199389Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2199392Z 
2025-09-07T08:18:00.2199494Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2199690Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2199747Z     return mod(*inputs)
2025-09-07T08:18:00.2199967Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2200034Z     features = self.features(x)
2025-09-07T08:18:00.2200252Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2200314Z     new_features = layer(features)
2025-09-07T08:18:00.2200632Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2200731Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2200962Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2201042Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2201046Z 
2025-09-07T08:18:00.2201143Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2201340Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2201401Z     return mod(*inputs)
2025-09-07T08:18:00.2201621Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2201686Z     features = self.features(x)
2025-09-07T08:18:00.2201903Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2201974Z     new_features = layer(features)
2025-09-07T08:18:00.2202187Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2202280Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2202512Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2202680Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2202683Z 
2025-09-07T08:18:00.2202781Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2202985Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2203048Z     return mod(*inputs)
2025-09-07T08:18:00.2203259Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2203322Z     features = self.features(x)
2025-09-07T08:18:00.2203545Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2203606Z     new_features = layer(features)
2025-09-07T08:18:00.2203825Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2203916Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2204142Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2204407Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2204410Z 
2025-09-07T08:18:00.2204511Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2204708Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2204766Z     return mod(*inputs)
2025-09-07T08:18:00.2204992Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2205060Z     features = self.features(x)
2025-09-07T08:18:00.2205274Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2205345Z     new_features = layer(features)
2025-09-07T08:18:00.2205559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2205692Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2205698Z 
2025-09-07T08:18:00.2205794Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2205990Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2206051Z     return mod(*inputs)
2025-09-07T08:18:00.2206327Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2206396Z     features = self.features(x)
2025-09-07T08:18:00.2206612Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2206677Z     new_features = layer(features)
2025-09-07T08:18:00.2206897Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2207024Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2207027Z 
2025-09-07T08:18:00.2207121Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2207319Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2207379Z     return mod(*inputs)
2025-09-07T08:18:00.2207599Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2207666Z     features = self.features(x)
2025-09-07T08:18:00.2207883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2207946Z     new_features = layer(features)
2025-09-07T08:18:00.2208163Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2208254Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2208478Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2208562Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2208565Z 
2025-09-07T08:18:00.2208656Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2208851Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2208907Z     return mod(*inputs)
2025-09-07T08:18:00.2209123Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2209189Z     features = self.features(x)
2025-09-07T08:18:00.2209403Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2209470Z     new_features = layer(features)
2025-09-07T08:18:00.2209680Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2209772Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2209997Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2210227Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2210230Z 
2025-09-07T08:18:00.2210325Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2210517Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2210582Z     return mod(*inputs)
2025-09-07T08:18:00.2210797Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2210859Z     features = self.features(x)
2025-09-07T08:18:00.2211077Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2211143Z     new_features = layer(features)
2025-09-07T08:18:00.2211364Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2211455Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2211681Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2211847Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2211951Z 
2025-09-07T08:18:00.2212047Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2212242Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2212299Z     return mod(*inputs)
2025-09-07T08:18:00.2212521Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2212584Z     features = self.features(x)
2025-09-07T08:18:00.2212799Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2212868Z     new_features = layer(features)
2025-09-07T08:18:00.2213082Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2213211Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2213214Z 
2025-09-07T08:18:00.2213309Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2213502Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2213567Z     return mod(*inputs)
2025-09-07T08:18:00.2213782Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2213848Z     features = self.features(x)
2025-09-07T08:18:00.2214063Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2214130Z     new_features = layer(features)
2025-09-07T08:18:00.2214347Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2214473Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2214476Z 
2025-09-07T08:18:00.2214571Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2214767Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2214828Z     return mod(*inputs)
2025-09-07T08:18:00.2215042Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2215105Z     features = self.features(x)
2025-09-07T08:18:00.2215328Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2215393Z     new_features = layer(features)
2025-09-07T08:18:00.2215611Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2215765Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2215990Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2216067Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2216070Z 
2025-09-07T08:18:00.2216164Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2216358Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2216417Z     return mod(*inputs)
2025-09-07T08:18:00.2216637Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2216702Z     features = self.features(x)
2025-09-07T08:18:00.2216919Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2216988Z     new_features = layer(features)
2025-09-07T08:18:00.2217202Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2217298Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2217523Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2217773Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2217777Z 
2025-09-07T08:18:00.2217875Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2218069Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2218131Z     return mod(*inputs)
2025-09-07T08:18:00.2218344Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2218407Z     features = self.features(x)
2025-09-07T08:18:00.2218629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2218693Z     new_features = layer(features)
2025-09-07T08:18:00.2218911Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2219005Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2219236Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2219395Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2219398Z 
2025-09-07T08:18:00.2219494Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2219692Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2219751Z     return mod(*inputs)
2025-09-07T08:18:00.2219971Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2220037Z     features = self.features(x)
2025-09-07T08:18:00.2220253Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2220322Z     new_features = layer(features)
2025-09-07T08:18:00.2220535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2220665Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2220667Z 
2025-09-07T08:18:00.2220758Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2220949Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2221009Z     return mod(*inputs)
2025-09-07T08:18:00.2221226Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2221366Z     features = self.features(x)
2025-09-07T08:18:00.2221580Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2221646Z     new_features = layer(features)
2025-09-07T08:18:00.2221866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2221985Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2221989Z 
2025-09-07T08:18:00.2222087Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2222276Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2222341Z     return mod(*inputs)
2025-09-07T08:18:00.2222559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2222625Z     features = self.features(x)
2025-09-07T08:18:00.2222858Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2222928Z     new_features = layer(features)
2025-09-07T08:18:00.2223146Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2223307Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2223541Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T08:18:00.2223619Z     concated_features = torch.cat(inputs, 1)
2025-09-07T08:18:00.2223622Z 
2025-09-07T08:18:00.2223719Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2223918Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2223976Z     return mod(*inputs)
2025-09-07T08:18:00.2224196Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2224263Z     features = self.features(x)
2025-09-07T08:18:00.2224478Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2224548Z     new_features = layer(features)
2025-09-07T08:18:00.2224762Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2224862Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2225088Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2225251Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2225258Z 
2025-09-07T08:18:00.2225353Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2225635Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2225705Z     return mod(*inputs)
2025-09-07T08:18:00.2225916Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2225984Z     features = self.features(x)
2025-09-07T08:18:00.2226199Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2226263Z     new_features = layer(features)
2025-09-07T08:18:00.2226484Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T08:18:00.2226575Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T08:18:00.2226803Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T08:18:00.2226964Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T08:18:00.2226967Z 
2025-09-07T08:18:00.2227136Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2227334Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2227393Z     return mod(*inputs)
2025-09-07T08:18:00.2227613Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2227682Z     features = self.features(x)
2025-09-07T08:18:00.2227909Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2227975Z     new_features = layer(features)
2025-09-07T08:18:00.2228187Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2228322Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2228325Z 
2025-09-07T08:18:00.2228416Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2228612Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2228670Z     return mod(*inputs)
2025-09-07T08:18:00.2228887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2228956Z     features = self.features(x)
2025-09-07T08:18:00.2229241Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T08:18:00.2229313Z     new_features = layer(features)
2025-09-07T08:18:00.2229526Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T08:18:00.2229649Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T08:18:00.2229660Z 
2025-09-07T08:18:00.2229738Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2229810Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2229884Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2229954Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2230025Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2230101Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2230172Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2230268Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2230461Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2230522Z     return mod(*inputs)
2025-09-07T08:18:00.2230744Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T08:18:00.2230809Z     features = self.features(x)
2025-09-07T08:18:00.2231040Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T08:18:00.2231108Z     return torch.cat(features, 1)
2025-09-07T08:18:00.2231111Z 
2025-09-07T08:18:00.2231190Z cudagraph partition due to non gpu ops
2025-09-07T08:18:00.2231283Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2231476Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2231544Z     return mod(*inputs)
2025-09-07T08:18:00.2231765Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 215, in forward
2025-09-07T08:18:00.2231847Z     out = F.adaptive_avg_pool2d(out, (1, 1))
2025-09-07T08:18:00.2231850Z 
2025-09-07T08:18:00.2231941Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T08:18:00.2232134Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T08:18:00.2232199Z     return mod(*inputs)
2025-09-07T08:18:00.2232413Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 217, in forward
2025-09-07T08:18:00.2232485Z     out = self.classifier(out)
2025-09-07T08:18:00.2232558Z 
2025-09-07T08:18:14.4784172Z pass
2025-09-07T08:18:14.4786319Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:18:16.9591662Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:18:16.9592534Z   import pynvml  # type: ignore[import]
2025-09-07T08:18:18.9719284Z 
2025-09-07T08:18:19.1904152Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:18:19.1904579Z   what():  std::bad_array_new_length
2025-09-07T08:20:03.8026932Z Run failed with return code:  -6
2025-09-07T08:20:03.8027201Z Output:  None
2025-09-07T08:20:03.8027364Z Error:  None
2025-09-07T08:20:04.2138081Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:20:04.2139023Z   import pynvml  # type: ignore[import]
2025-09-07T08:20:06.2192946Z 
2025-09-07T08:20:06.4371178Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:20:06.4371580Z   what():  std::bad_array_new_length
2025-09-07T08:21:49.6557968Z Run failed with return code:  -6
2025-09-07T08:21:49.6558235Z Output:  None
2025-09-07T08:21:49.6558396Z Error:  None
2025-09-07T08:21:50.0672755Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:21:50.0673667Z   import pynvml  # type: ignore[import]
2025-09-07T08:21:52.0879982Z 
2025-09-07T08:21:52.3060262Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:21:52.3060648Z   what():  std::bad_array_new_length
2025-09-07T08:23:35.2587596Z Run failed with return code:  -6
2025-09-07T08:23:35.2587855Z Output:  None
2025-09-07T08:23:35.2588046Z Error:  None
2025-09-07T08:23:35.6666365Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:23:35.6667263Z   import pynvml  # type: ignore[import]
2025-09-07T08:23:37.6741962Z 
2025-09-07T08:23:37.8898545Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:23:37.8899039Z   what():  std::bad_array_new_length
2025-09-07T08:25:21.1126521Z Run failed with return code:  -6
2025-09-07T08:25:21.1126769Z Output:  None
2025-09-07T08:25:21.1126923Z Error:  None
2025-09-07T08:25:21.5243210Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:25:21.5244097Z   import pynvml  # type: ignore[import]
2025-09-07T08:25:23.5381534Z 
2025-09-07T08:25:23.7568473Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:25:23.7568881Z   what():  std::bad_array_new_length
2025-09-07T08:27:06.7145391Z Run failed with return code:  -6
2025-09-07T08:27:06.7145659Z Output:  None
2025-09-07T08:27:06.7145809Z Error:  None
2025-09-07T08:27:07.1235554Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:27:07.1236913Z   import pynvml  # type: ignore[import]
2025-09-07T08:27:09.1430359Z 
2025-09-07T08:27:09.3621791Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:27:09.3622203Z   what():  std::bad_array_new_length
2025-09-07T08:28:52.8693792Z Run failed with return code:  -6
2025-09-07T08:28:52.8694040Z Output:  None
2025-09-07T08:28:52.8694209Z Error:  None
2025-09-07T08:28:53.2786237Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:28:53.2787145Z   import pynvml  # type: ignore[import]
2025-09-07T08:28:55.2873388Z 
2025-09-07T08:28:55.5050950Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:28:55.5051347Z   what():  std::bad_array_new_length
2025-09-07T08:30:38.7251515Z Run failed with return code:  -6
2025-09-07T08:30:38.7251771Z Output:  None
2025-09-07T08:30:38.7252471Z Error:  None
2025-09-07T08:30:39.1337481Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:30:39.1338384Z   import pynvml  # type: ignore[import]
2025-09-07T08:30:41.1489971Z 
2025-09-07T08:30:41.3675051Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:30:41.3675433Z   what():  std::bad_array_new_length
2025-09-07T08:32:25.1322642Z Run failed with return code:  -6
2025-09-07T08:32:25.1322901Z Output:  None
2025-09-07T08:32:25.1323056Z Error:  None
2025-09-07T08:32:25.5395831Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:32:25.5396720Z   import pynvml  # type: ignore[import]
2025-09-07T08:32:27.5532122Z 
2025-09-07T08:32:27.7718258Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:32:27.7718653Z   what():  std::bad_array_new_length
2025-09-07T08:34:11.3394837Z Run failed with return code:  -6
2025-09-07T08:34:11.3395088Z Output:  None
2025-09-07T08:34:11.3395246Z Error:  None
2025-09-07T08:34:11.7465950Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:34:11.7466963Z   import pynvml  # type: ignore[import]
2025-09-07T08:34:13.7686519Z 
2025-09-07T08:34:13.9861675Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:34:13.9862058Z   what():  std::bad_array_new_length
2025-09-07T08:35:57.2475240Z Run failed with return code:  -6
2025-09-07T08:35:57.2475497Z Output:  None
2025-09-07T08:35:57.2475652Z Error:  None
2025-09-07T08:35:57.6569722Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:35:57.6570598Z   import pynvml  # type: ignore[import]
2025-09-07T08:35:59.6739787Z 
2025-09-07T08:35:59.8911083Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:35:59.8911477Z   what():  std::bad_array_new_length
2025-09-07T08:37:43.0502393Z Run failed with return code:  -6
2025-09-07T08:37:43.0502669Z Output:  None
2025-09-07T08:37:43.0502868Z Error:  None
2025-09-07T08:37:43.0544053Z accuracy            pass_rate=91.67%
2025-09-07T08:37:43.0549892Z calls_captured      gmean=0.00x mean=145.000x
2025-09-07T08:37:43.0552721Z unique_graphs       gmean=0.00x mean=1.500x
2025-09-07T08:37:43.0555048Z graph_breaks        gmean=0.00x mean=0.750x
2025-09-07T08:37:43.0557236Z unique_graph_breaks gmean=0.00x mean=0.167x
2025-09-07T08:37:43.0559344Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T08:37:43.0561451Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T08:37:43.0563570Z cudagraph_skips     gmean=0.00x mean=1.500x
2025-09-07T08:37:43.0564334Z compilation_latency mean=15.162 seconds
2025-09-07T08:37:43.5987749Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *cppwrapper-true* ]]
2025-09-07T08:37:43.5988276Z + TORCHINDUCTOR_CPP_WRAPPER=1
2025-09-07T08:37:43.5990628Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --backend inductor --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv
2025-09-07T08:37:43.9963618Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:37:43.9964500Z   import pynvml  # type: ignore[import]
2025-09-07T08:37:46.4504297Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:37:46.4505167Z   import pynvml  # type: ignore[import]
2025-09-07T08:37:48.4550776Z 
2025-09-07T08:37:50.3539139Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:37:50.3539449Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:37:50.3751712Z cpu  eval  BERT_pytorch                       
2025-09-07T08:37:50.9294079Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:37:51.1896607Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:37:51.4409580Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:15.5447744Z pass
2025-09-07T08:38:15.5450442Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:17.9745848Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:38:17.9746724Z   import pynvml  # type: ignore[import]
2025-09-07T08:38:19.9892665Z 
2025-09-07T08:38:22.1981478Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:38:22.1981782Z loading model: 0it [00:02, ?it/s]
2025-09-07T08:38:22.2080149Z cpu  eval  Background_Matting                 
2025-09-07T08:38:22.3188813Z pass_due_to_skip
2025-09-07T08:38:22.3189206Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:23.6693951Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:38:23.6695259Z   import pynvml  # type: ignore[import]
2025-09-07T08:38:25.6799459Z 
2025-09-07T08:38:27.7303883Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:38:27.7304222Z loading model: 0it [00:02, ?it/s]
2025-09-07T08:38:27.7345832Z cpu  eval  LearningToPaint                    
2025-09-07T08:38:27.9799030Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:28.0219537Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:28.0570440Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:39.4988584Z pass
2025-09-07T08:38:39.4991381Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:38:41.7797886Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:38:41.7799300Z   import pynvml  # type: ignore[import]
2025-09-07T08:38:43.7922712Z 
2025-09-07T08:38:45.2189786Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T08:38:45.6142037Z 
2025-09-07T08:38:45.6143116Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:38:45.6143481Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T08:38:45.6143829Z cpu  eval  Super_SloMo                        
2025-09-07T08:39:05.7715092Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:39:05.7716569Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T08:39:06.3842711Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:39:06.9869853Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:39:46.6370182Z pass
2025-09-07T08:39:46.6374608Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:39:49.9732634Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:39:49.9733509Z   import pynvml  # type: ignore[import]
2025-09-07T08:39:51.9858385Z 
2025-09-07T08:39:52.6841850Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:39:52.6842193Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:39:52.6876789Z cpu  eval  alexnet                            
2025-09-07T08:39:52.8982135Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:39:52.9172447Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:39:52.9292920Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:02.6696278Z pass
2025-09-07T08:40:02.6697095Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:04.7259682Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:40:04.7260734Z   import pynvml  # type: ignore[import]
2025-09-07T08:40:06.7393966Z 
2025-09-07T08:40:08.2516685Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:40:08.2516961Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:40:08.2526906Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T08:40:08.4183466Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:08.4701665Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:08.5229824Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:15.6274239Z pass
2025-09-07T08:40:15.6274644Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:17.7304331Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:40:17.7305231Z   import pynvml  # type: ignore[import]
2025-09-07T08:40:19.7535516Z 
2025-09-07T08:40:21.3225655Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:40:21.3225944Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:40:21.3231378Z cpu  eval  basic_gnn_gcn                      
2025-09-07T08:40:21.4024862Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:21.4628060Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:21.5195766Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:31.5622510Z pass
2025-09-07T08:40:31.5622913Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:33.6395788Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:40:33.6396810Z   import pynvml  # type: ignore[import]
2025-09-07T08:40:35.6550977Z 
2025-09-07T08:40:37.1471875Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:40:37.1472167Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:40:37.1478888Z cpu  eval  basic_gnn_gin                      
2025-09-07T08:40:37.2343774Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:37.2875173Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:37.3366973Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:44.0845819Z pass
2025-09-07T08:40:44.0846223Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:46.1414085Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:40:46.1414987Z   import pynvml  # type: ignore[import]
2025-09-07T08:40:48.1617725Z 
2025-09-07T08:40:49.6510615Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:40:49.6510884Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:40:49.6517943Z cpu  eval  basic_gnn_sage                     
2025-09-07T08:40:49.7230758Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:49.8406881Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:49.8873096Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:56.6670392Z pass
2025-09-07T08:40:56.6670792Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:40:58.6917321Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:40:58.6918173Z   import pynvml  # type: ignore[import]
2025-09-07T08:41:00.7071166Z 
2025-09-07T08:41:00.9493207Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:41:00.9493624Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:41:00.9501510Z cpu  eval  dcgan                              
2025-09-07T08:41:01.0020964Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:01.0142063Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:01.0214119Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:09.2134963Z pass
2025-09-07T08:41:09.2135490Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:11.1954845Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:41:11.1955715Z   import pynvml  # type: ignore[import]
2025-09-07T08:41:13.2105702Z 
2025-09-07T08:41:14.8204330Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:41:14.8204640Z loading model: 0it [00:01, ?it/s]
2025-09-07T08:41:14.8391246Z cpu  eval  demucs                             
2025-09-07T08:41:19.5828909Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:19.7434683Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:19.8900608Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:32.0410901Z pass
2025-09-07T08:41:32.0413899Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:34.2623109Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:41:34.2623975Z   import pynvml  # type: ignore[import]
2025-09-07T08:41:36.2746076Z 
2025-09-07T08:41:37.0291038Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:41:37.0291314Z loading model: 0it [00:00, ?it/s]
2025-09-07T08:41:37.0455638Z cpu  eval  densenet121                        
2025-09-07T08:41:38.1959200Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:38.4531594Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:41:38.7713384Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:42:31.4141112Z pass
2025-09-07T08:42:31.4145686Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T08:42:34.5890938Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:42:34.5891811Z   import pynvml  # type: ignore[import]
2025-09-07T08:42:36.6044722Z 
2025-09-07T08:42:36.8228913Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:42:36.8229292Z   what():  std::bad_array_new_length
2025-09-07T08:44:19.7797129Z Run failed with return code:  -6
2025-09-07T08:44:19.7797391Z Output:  None
2025-09-07T08:44:19.7797543Z Error:  None
2025-09-07T08:44:20.1939033Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:44:20.1939983Z   import pynvml  # type: ignore[import]
2025-09-07T08:44:22.2037330Z 
2025-09-07T08:44:22.4211322Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:44:22.4211725Z   what():  std::bad_array_new_length
2025-09-07T08:46:05.6804511Z Run failed with return code:  -6
2025-09-07T08:46:05.6804785Z Output:  None
2025-09-07T08:46:05.6804944Z Error:  None
2025-09-07T08:46:06.0884204Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:46:06.0885086Z   import pynvml  # type: ignore[import]
2025-09-07T08:46:08.0994691Z 
2025-09-07T08:46:08.3159162Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:46:08.3159563Z   what():  std::bad_array_new_length
2025-09-07T08:47:51.4823874Z Run failed with return code:  -6
2025-09-07T08:47:51.4824130Z Output:  None
2025-09-07T08:47:51.4824285Z Error:  None
2025-09-07T08:47:51.8919795Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:47:51.8920692Z   import pynvml  # type: ignore[import]
2025-09-07T08:47:53.9061089Z 
2025-09-07T08:47:54.1238003Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:47:54.1238390Z   what():  std::bad_array_new_length
2025-09-07T08:49:37.7348577Z Run failed with return code:  -6
2025-09-07T08:49:37.7348837Z Output:  None
2025-09-07T08:49:37.7349006Z Error:  None
2025-09-07T08:49:38.1421942Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:49:38.1422897Z   import pynvml  # type: ignore[import]
2025-09-07T08:49:40.1575717Z 
2025-09-07T08:49:40.3758932Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:49:40.3761156Z   what():  std::bad_array_new_length
2025-09-07T08:51:23.5876673Z Run failed with return code:  -6
2025-09-07T08:51:23.5876930Z Output:  None
2025-09-07T08:51:23.5877086Z Error:  None
2025-09-07T08:51:23.9953982Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:51:23.9954820Z   import pynvml  # type: ignore[import]
2025-09-07T08:51:26.0104055Z 
2025-09-07T08:51:26.2288586Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:51:26.2288998Z   what():  std::bad_array_new_length
2025-09-07T08:53:09.2411653Z Run failed with return code:  -6
2025-09-07T08:53:09.2411923Z Output:  None
2025-09-07T08:53:09.2412087Z Error:  None
2025-09-07T08:53:09.6532855Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:53:09.6533798Z   import pynvml  # type: ignore[import]
2025-09-07T08:53:11.6702726Z 
2025-09-07T08:53:11.8872470Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:53:11.8872872Z   what():  std::bad_array_new_length
2025-09-07T08:54:54.9925482Z Run failed with return code:  -6
2025-09-07T08:54:54.9925744Z Output:  None
2025-09-07T08:54:54.9925910Z Error:  None
2025-09-07T08:54:55.4041417Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:54:55.4042392Z   import pynvml  # type: ignore[import]
2025-09-07T08:54:57.4336180Z 
2025-09-07T08:54:57.6513681Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:54:57.6514085Z   what():  std::bad_array_new_length
2025-09-07T08:56:41.2945624Z Run failed with return code:  -6
2025-09-07T08:56:41.2945895Z Output:  None
2025-09-07T08:56:41.2946041Z Error:  None
2025-09-07T08:56:41.7052931Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:56:41.7053861Z   import pynvml  # type: ignore[import]
2025-09-07T08:56:43.7193459Z 
2025-09-07T08:56:43.9374838Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:56:43.9375257Z   what():  std::bad_array_new_length
2025-09-07T08:58:27.3464419Z Run failed with return code:  -6
2025-09-07T08:58:27.3464677Z Output:  None
2025-09-07T08:58:27.3464831Z Error:  None
2025-09-07T08:58:27.7546874Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T08:58:27.7547740Z   import pynvml  # type: ignore[import]
2025-09-07T08:58:29.7700206Z 
2025-09-07T08:58:29.9876713Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T08:58:29.9877097Z   what():  std::bad_array_new_length
2025-09-07T09:00:13.0453175Z Run failed with return code:  -6
2025-09-07T09:00:13.0453479Z Output:  None
2025-09-07T09:00:13.0453635Z Error:  None
2025-09-07T09:00:13.4574611Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:00:13.4575476Z   import pynvml  # type: ignore[import]
2025-09-07T09:00:15.4611595Z 
2025-09-07T09:00:15.6771375Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:00:15.6771766Z   what():  std::bad_array_new_length
2025-09-07T09:01:58.6473226Z Run failed with return code:  -6
2025-09-07T09:01:58.6473472Z Output:  None
2025-09-07T09:01:58.6473626Z Error:  None
2025-09-07T09:01:58.6509340Z accuracy            pass_rate=91.67%
2025-09-07T09:01:58.6514689Z calls_captured      gmean=0.00x mean=145.000x
2025-09-07T09:01:58.6517273Z unique_graphs       gmean=0.00x mean=1.500x
2025-09-07T09:01:58.6519531Z graph_breaks        gmean=0.00x mean=0.750x
2025-09-07T09:01:58.6521604Z unique_graph_breaks gmean=0.00x mean=0.167x
2025-09-07T09:01:58.6523734Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T09:01:58.6525805Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T09:01:58.6527897Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T09:01:58.6528892Z compilation_latency mean=15.462 seconds
2025-09-07T09:01:59.1780907Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *freezing_cudagraphs-true* ]]
2025-09-07T09:01:59.1781737Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *freeze_autotune_cudagraphs-true* ]]
2025-09-07T09:01:59.1782481Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *aotinductor-true* ]]
2025-09-07T09:01:59.1782948Z + [[ inference == \i\n\f\e\r\e\n\c\e ]]
2025-09-07T09:01:59.1783194Z + [[ accuracy == \a\c\c\u\r\a\c\y ]]
2025-09-07T09:01:59.1784625Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_export_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv
2025-09-07T09:01:59.5741105Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:01:59.5741978Z   import pynvml  # type: ignore[import]
2025-09-07T09:02:02.0249044Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:02:02.0249961Z   import pynvml  # type: ignore[import]
2025-09-07T09:02:04.0482706Z 
2025-09-07T09:02:05.9887098Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:02:05.9887399Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:02:06.0103870Z cpu  eval  BERT_pytorch                       
2025-09-07T09:02:06.4908491Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:06.7514038Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:07.0028156Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:07.2352842Z ERROR:common:
2025-09-07T09:02:07.2353067Z Traceback (most recent call last):
2025-09-07T09:02:07.2353441Z   File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 2320, in check_accuracy
2025-09-07T09:02:07.2353843Z     optimized_model_iter_fn = optimize_ctx(
2025-09-07T09:02:07.2354158Z   File "/var/lib/jenkins/workspace/benchmarks/dynamo/common.py", line 1523, in export
2025-09-07T09:02:07.2354474Z     ep = torch.export.export(
2025-09-07T09:02:07.2354820Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/__init__.py", line 311, in export
2025-09-07T09:02:07.2355164Z     raise e
2025-09-07T09:02:07.2355451Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/__init__.py", line 277, in export
2025-09-07T09:02:07.2355778Z     return _export(
2025-09-07T09:02:07.2356082Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 1163, in wrapper
2025-09-07T09:02:07.2356402Z     raise e
2025-09-07T09:02:07.2356678Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 1129, in wrapper
2025-09-07T09:02:07.2357004Z     ep = fn(*args, **kwargs)
2025-09-07T09:02:07.2357349Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/exported_program.py", line 124, in wrapper
2025-09-07T09:02:07.2358098Z     return fn(*args, **kwargs)
2025-09-07T09:02:07.2358410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 2255, in _export
2025-09-07T09:02:07.2358736Z     ep = _export_for_training(
2025-09-07T09:02:07.2359038Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 1163, in wrapper
2025-09-07T09:02:07.2359352Z     raise e
2025-09-07T09:02:07.2359627Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 1129, in wrapper
2025-09-07T09:02:07.2359966Z     ep = fn(*args, **kwargs)
2025-09-07T09:02:07.2360295Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/exported_program.py", line 124, in wrapper
2025-09-07T09:02:07.2360648Z     return fn(*args, **kwargs)
2025-09-07T09:02:07.2360997Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 2071, in _export_for_training
2025-09-07T09:02:07.2361373Z     export_artifact = export_func(
2025-09-07T09:02:07.2361746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 1415, in _strict_export
2025-09-07T09:02:07.2362101Z     gm_torch_level = _export_to_torch_ir(
2025-09-07T09:02:07.2362610Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/export/_trace.py", line 812, in _export_to_torch_ir
2025-09-07T09:02:07.2362983Z     gm_torch_level, _ = torch._dynamo.export(
2025-09-07T09:02:07.2363343Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py", line 2002, in inner
2025-09-07T09:02:07.2363689Z     result_traced = opt_f(*args, **kwargs)
2025-09-07T09:02:07.2364043Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py", line 414, in __call__
2025-09-07T09:02:07.2364394Z     return super().__call__(*args, **kwargs)
2025-09-07T09:02:07.2364767Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
2025-09-07T09:02:07.2365153Z     return self._call_impl(*args, **kwargs)
2025-09-07T09:02:07.2365502Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
2025-09-07T09:02:07.2365877Z     return forward_call(*args, **kwargs)
2025-09-07T09:02:07.2366252Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py", line 832, in compile_wrapper
2025-09-07T09:02:07.2366620Z     return fn(*args, **kwargs)
2025-09-07T09:02:07.2366985Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1775, in _wrapped_call_impl
2025-09-07T09:02:07.2367369Z     return self._call_impl(*args, **kwargs)
2025-09-07T09:02:07.2367726Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
2025-09-07T09:02:07.2368077Z     return forward_call(*args, **kwargs)
2025-09-07T09:02:07.2368438Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 1875, in __call__
2025-09-07T09:02:07.2368804Z     result = self._torchdynamo_orig_backend(
2025-09-07T09:02:07.2369161Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 688, in __call__
2025-09-07T09:02:07.2369512Z     result = _compile(
2025-09-07T09:02:07.2369828Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 1433, in _compile
2025-09-07T09:02:07.2370253Z     guarded_code, tracer_output = compile_inner(code, one_graph, hooks)
2025-09-07T09:02:07.2370670Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_utils_internal.py", line 92, in wrapper_function
2025-09-07T09:02:07.2371028Z     return function(*args, **kwargs)
2025-09-07T09:02:07.2371384Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 1117, in compile_inner
2025-09-07T09:02:07.2374236Z     return _compile_inner(code, one_graph, hooks)
2025-09-07T09:02:07.2374624Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 1151, in _compile_inner
2025-09-07T09:02:07.2375001Z     dynamo_output = compile_frame(
2025-09-07T09:02:07.2375367Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 1032, in compile_frame
2025-09-07T09:02:07.2375785Z     bytecode, tracer_output = transform_code_object(code, transform)
2025-09-07T09:02:07.2376261Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/bytecode_transformation.py", line 1592, in transform_code_object
2025-09-07T09:02:07.2376725Z     tracer_output = transformations(instructions, code_options)
2025-09-07T09:02:07.2377127Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 1004, in transform
2025-09-07T09:02:07.2377484Z     tracer_output = trace_frame(
2025-09-07T09:02:07.2377809Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 312, in _fn
2025-09-07T09:02:07.2378150Z     return fn(*args, **kwargs)
2025-09-07T09:02:07.2378488Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 815, in trace_frame
2025-09-07T09:02:07.2378832Z     run_tracer()
2025-09-07T09:02:07.2379208Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py", line 797, in run_tracer
2025-09-07T09:02:07.2379559Z     tracer.run()
2025-09-07T09:02:07.2379866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1487, in run
2025-09-07T09:02:07.2380213Z     while self.step():
2025-09-07T09:02:07.2380523Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1348, in step
2025-09-07T09:02:07.2380895Z     self.dispatch_table[inst.opcode](self, inst)
2025-09-07T09:02:07.2381262Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 904, in wrapper
2025-09-07T09:02:07.2381615Z     return inner_fn(self, inst)
2025-09-07T09:02:07.2381975Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2320, in CALL_FUNCTION
2025-09-07T09:02:07.2382340Z     self.call_function(fn, args, {})
2025-09-07T09:02:07.2382711Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1266, in call_function
2025-09-07T09:02:07.2383155Z     self.push(fn.call_function(self, args, kwargs))  # type: ignore[arg-type]
2025-09-07T09:02:07.2383610Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/lazy.py", line 212, in realize_and_forward
2025-09-07T09:02:07.2384026Z     return getattr(self.realize(), name)(*args, **kwargs)
2025-09-07T09:02:07.2384428Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/nn_module.py", line 528, in call_function
2025-09-07T09:02:07.2384818Z     return tx.inline_user_function_return(
2025-09-07T09:02:07.2385228Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1288, in inline_user_function_return
2025-09-07T09:02:07.2385810Z     return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
2025-09-07T09:02:07.2386269Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4112, in inline_call
2025-09-07T09:02:07.2386632Z     return tracer.inline_call_()
2025-09-07T09:02:07.2386991Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4315, in inline_call_
2025-09-07T09:02:07.2387350Z     self.run()
2025-09-07T09:02:07.2387654Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1487, in run
2025-09-07T09:02:07.2387992Z     while self.step():
2025-09-07T09:02:07.2388310Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1348, in step
2025-09-07T09:02:07.2388813Z     self.dispatch_table[inst.opcode](self, inst)
2025-09-07T09:02:07.2389185Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 904, in wrapper
2025-09-07T09:02:07.2389536Z     return inner_fn(self, inst)
2025-09-07T09:02:07.2389901Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2371, in CALL_FUNCTION_EX
2025-09-07T09:02:07.2390309Z     self.call_function(fn, argsvars.items, kwargsvars)
2025-09-07T09:02:07.2390710Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1266, in call_function
2025-09-07T09:02:07.2391148Z     self.push(fn.call_function(self, args, kwargs))  # type: ignore[arg-type]
2025-09-07T09:02:07.2391595Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 1154, in call_function
2025-09-07T09:02:07.2392000Z     return super().call_function(tx, args, kwargs)
2025-09-07T09:02:07.2392393Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 598, in call_function
2025-09-07T09:02:07.2392789Z     return super().call_function(tx, args, kwargs)
2025-09-07T09:02:07.2393258Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 342, in call_function
2025-09-07T09:02:07.2393721Z     return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)
2025-09-07T09:02:07.2394210Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1288, in inline_user_function_return
2025-09-07T09:02:07.2394705Z     return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
2025-09-07T09:02:07.2395159Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4112, in inline_call
2025-09-07T09:02:07.2395521Z     return tracer.inline_call_()
2025-09-07T09:02:07.2395875Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4315, in inline_call_
2025-09-07T09:02:07.2396229Z     self.run()
2025-09-07T09:02:07.2396530Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1487, in run
2025-09-07T09:02:07.2396874Z     while self.step():
2025-09-07T09:02:07.2397189Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1348, in step
2025-09-07T09:02:07.2397550Z     self.dispatch_table[inst.opcode](self, inst)
2025-09-07T09:02:07.2397915Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 904, in wrapper
2025-09-07T09:02:07.2398272Z     return inner_fn(self, inst)
2025-09-07T09:02:07.2398626Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2320, in CALL_FUNCTION
2025-09-07T09:02:07.2399167Z     self.call_function(fn, args, {})
2025-09-07T09:02:07.2399533Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1266, in call_function
2025-09-07T09:02:07.2399974Z     self.push(fn.call_function(self, args, kwargs))  # type: ignore[arg-type]
2025-09-07T09:02:07.2400426Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 1154, in call_function
2025-09-07T09:02:07.2400823Z     return super().call_function(tx, args, kwargs)
2025-09-07T09:02:07.2401207Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 598, in call_function
2025-09-07T09:02:07.2401593Z     return super().call_function(tx, args, kwargs)
2025-09-07T09:02:07.2401983Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 342, in call_function
2025-09-07T09:02:07.2402449Z     return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)
2025-09-07T09:02:07.2403093Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1288, in inline_user_function_return
2025-09-07T09:02:07.2403584Z     return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
2025-09-07T09:02:07.2404046Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4112, in inline_call
2025-09-07T09:02:07.2404418Z     return tracer.inline_call_()
2025-09-07T09:02:07.2404780Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4315, in inline_call_
2025-09-07T09:02:07.2405139Z     self.run()
2025-09-07T09:02:07.2405436Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1487, in run
2025-09-07T09:02:07.2405780Z     while self.step():
2025-09-07T09:02:07.2406101Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1348, in step
2025-09-07T09:02:07.2406476Z     self.dispatch_table[inst.opcode](self, inst)
2025-09-07T09:02:07.2406841Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 904, in wrapper
2025-09-07T09:02:07.2407192Z     return inner_fn(self, inst)
2025-09-07T09:02:07.2407677Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2320, in CALL_FUNCTION
2025-09-07T09:02:07.2408070Z     self.call_function(fn, args, {})
2025-09-07T09:02:07.2408447Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1266, in call_function
2025-09-07T09:02:07.2408893Z     self.push(fn.call_function(self, args, kwargs))  # type: ignore[arg-type]
2025-09-07T09:02:07.2409357Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 1154, in call_function
2025-09-07T09:02:07.2409767Z     return super().call_function(tx, args, kwargs)
2025-09-07T09:02:07.2410173Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 598, in call_function
2025-09-07T09:02:07.2410593Z     return super().call_function(tx, args, kwargs)
2025-09-07T09:02:07.2410986Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/variables/functions.py", line 342, in call_function
2025-09-07T09:02:07.2411452Z     return tx.inline_user_function_return(self, [*self.self_args(), *args], kwargs)
2025-09-07T09:02:07.2411950Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1288, in inline_user_function_return
2025-09-07T09:02:07.2412453Z     return InliningInstructionTranslator.inline_call(self, fn, args, kwargs)
2025-09-07T09:02:07.2413002Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4112, in inline_call
2025-09-07T09:02:07.2413370Z     return tracer.inline_call_()
2025-09-07T09:02:07.2413736Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 4315, in inline_call_
2025-09-07T09:02:07.2414104Z     self.run()
2025-09-07T09:02:07.2414412Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1487, in run
2025-09-07T09:02:07.2414750Z     while self.step():
2025-09-07T09:02:07.2415075Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 1348, in step
2025-09-07T09:02:07.2415442Z     self.dispatch_table[inst.opcode](self, inst)
2025-09-07T09:02:07.2415826Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py", line 2448, in STORE_ATTR
2025-09-07T09:02:07.2416194Z     assert not self.export, (
2025-09-07T09:02:07.2416427Z AssertionError: Mutating module attribute mask during export.
2025-09-07T09:02:07.2416620Z 
2025-09-07T09:02:07.2416678Z from user code:
2025-09-07T09:02:07.2417022Z    File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T09:02:07.2417478Z     x = self.bert(x, segment_label)
2025-09-07T09:02:07.2417826Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1786, in _call_impl
2025-09-07T09:02:07.2418186Z     return forward_call(*args, **kwargs)
2025-09-07T09:02:07.2418538Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T09:02:07.2418891Z     x = transformer.forward(x, mask)
2025-09-07T09:02:07.2419248Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 47, in forward
2025-09-07T09:02:07.2419608Z     self.lambda_module.set_mask(mask)
2025-09-07T09:02:07.2419965Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 16, in set_mask
2025-09-07T09:02:07.2420322Z     self.mask = mask
2025-09-07T09:02:07.2420417Z 
2025-09-07T09:02:07.2420782Z Set TORCHDYNAMO_VERBOSE=1 for the internal stack trace (please do this especially if you're reporting a bug to PyTorch). For even more developer context, set TORCH_LOGS="+dynamo"
2025-09-07T09:02:07.2421191Z 
2025-09-07T09:02:07.2421333Z TorchDynamo optimized model failed to run because of following error
2025-09-07T09:02:07.3235739Z fail_to_run
2025-09-07T09:02:07.3239644Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:08.5657283Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:02:08.5658171Z   import pynvml  # type: ignore[import]
2025-09-07T09:02:10.5752998Z 
2025-09-07T09:02:12.7784990Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:02:12.7785273Z loading model: 0it [00:02, ?it/s]
2025-09-07T09:02:12.7880343Z cpu  eval  Background_Matting                 
2025-09-07T09:02:12.8966161Z pass_due_to_skip
2025-09-07T09:02:12.8966556Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:14.2601496Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:02:14.2602507Z   import pynvml  # type: ignore[import]
2025-09-07T09:02:16.2745122Z 
2025-09-07T09:02:18.2697841Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:02:18.2698200Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:02:18.2740260Z cpu  eval  LearningToPaint                    
2025-09-07T09:02:18.5185771Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:18.5606260Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:18.5957755Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:23.8413716Z pass
2025-09-07T09:02:23.8414115Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:25.2583059Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:02:25.2583934Z   import pynvml  # type: ignore[import]
2025-09-07T09:02:27.2727801Z 
2025-09-07T09:02:28.7014172Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:02:29.0952801Z 
2025-09-07T09:02:29.0953179Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:02:29.0954763Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:02:29.0955152Z cpu  eval  Super_SloMo                        
2025-09-07T09:02:49.2354501Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:49.2359141Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:02:49.9168908Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:50.5239790Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:02:58.7318751Z pass
2025-09-07T09:02:58.7319151Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:00.5492030Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:00.5492941Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:02.5616925Z 
2025-09-07T09:03:03.2602498Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:03.2602794Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:03.2640366Z cpu  eval  alexnet                            
2025-09-07T09:03:03.4179285Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:03.4368657Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:03.4487106Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:08.3547382Z pass
2025-09-07T09:03:08.3547792Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:09.5467639Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:09.5468546Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:11.5712053Z 
2025-09-07T09:03:13.0808538Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:13.0808809Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:03:13.0816725Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T09:03:13.2450959Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:13.2972956Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:13.3506772Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:18.5037789Z pass
2025-09-07T09:03:18.5038190Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:20.0420268Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:20.0421139Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:22.0547603Z 
2025-09-07T09:03:23.5584470Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:23.5584752Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:03:23.5589618Z cpu  eval  basic_gnn_gcn                      
2025-09-07T09:03:23.6392521Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:23.7015072Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:23.7604269Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:28.5072752Z pass
2025-09-07T09:03:28.5073159Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:29.9883371Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:29.9884248Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:32.0030871Z 
2025-09-07T09:03:33.4926653Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:33.4926945Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:03:33.4933277Z cpu  eval  basic_gnn_gin                      
2025-09-07T09:03:33.5788133Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:33.6328681Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:33.6835521Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:37.9269611Z pass
2025-09-07T09:03:37.9270029Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:39.3896019Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:39.3896889Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:41.4065651Z 
2025-09-07T09:03:42.9011653Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:42.9011934Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:03:42.9018361Z cpu  eval  basic_gnn_sage                     
2025-09-07T09:03:42.9733457Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:43.0234932Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:43.0709574Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:47.2884811Z pass
2025-09-07T09:03:47.2885261Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:48.7360344Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:48.7361210Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:50.7547724Z 
2025-09-07T09:03:51.0358453Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:51.0358927Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:03:51.0367628Z cpu  eval  dcgan                              
2025-09-07T09:03:51.0895857Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:51.1020236Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:51.1093163Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:55.8262188Z pass
2025-09-07T09:03:55.8262795Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:03:56.9822012Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:03:56.9822879Z   import pynvml  # type: ignore[import]
2025-09-07T09:03:59.0027581Z 
2025-09-07T09:04:00.6281803Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:04:00.6282095Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:04:00.6481673Z cpu  eval  demucs                             
2025-09-07T09:04:05.4645213Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:05.6261259Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:05.7734392Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:13.2444583Z pass
2025-09-07T09:04:13.2444976Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:14.6445891Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:04:14.6446820Z   import pynvml  # type: ignore[import]
2025-09-07T09:04:16.6535604Z 
2025-09-07T09:04:17.4116302Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:04:17.4116618Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:04:17.4281689Z cpu  eval  densenet121                        
2025-09-07T09:04:18.5705646Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:18.8305942Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:19.0816980Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:26.4579822Z pass
2025-09-07T09:04:26.4580227Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:04:27.7493083Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:04:27.7493986Z   import pynvml  # type: ignore[import]
2025-09-07T09:04:29.7610694Z 
2025-09-07T09:04:29.9782745Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:04:29.9783144Z   what():  std::bad_array_new_length
2025-09-07T09:06:12.9426167Z Run failed with return code:  -6
2025-09-07T09:06:12.9426424Z Output:  None
2025-09-07T09:06:12.9426574Z Error:  None
2025-09-07T09:06:13.3530075Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:06:13.3531029Z   import pynvml  # type: ignore[import]
2025-09-07T09:06:15.3753808Z 
2025-09-07T09:06:15.5924709Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:06:15.5925186Z   what():  std::bad_array_new_length
2025-09-07T09:07:58.6942804Z Run failed with return code:  -6
2025-09-07T09:07:58.6943067Z Output:  None
2025-09-07T09:07:58.6943255Z Error:  None
2025-09-07T09:07:59.1028392Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:07:59.1029340Z   import pynvml  # type: ignore[import]
2025-09-07T09:08:01.1212320Z 
2025-09-07T09:08:01.3395201Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:08:01.3395589Z   what():  std::bad_array_new_length
2025-09-07T09:09:44.1957398Z Run failed with return code:  -6
2025-09-07T09:09:44.1957653Z Output:  None
2025-09-07T09:09:44.1959548Z Error:  None
2025-09-07T09:09:44.6037745Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:09:44.6038622Z   import pynvml  # type: ignore[import]
2025-09-07T09:09:46.6183938Z 
2025-09-07T09:09:46.8362014Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:09:46.8362417Z   what():  std::bad_array_new_length
2025-09-07T09:11:30.1471730Z Run failed with return code:  -6
2025-09-07T09:11:30.1472001Z Output:  None
2025-09-07T09:11:30.1472161Z Error:  None
2025-09-07T09:11:30.5583389Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:11:30.5584344Z   import pynvml  # type: ignore[import]
2025-09-07T09:11:32.5745243Z 
2025-09-07T09:11:32.7932405Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:11:32.7932807Z   what():  std::bad_array_new_length
2025-09-07T09:13:16.6001148Z Run failed with return code:  -6
2025-09-07T09:13:16.6001401Z Output:  None
2025-09-07T09:13:16.6001556Z Error:  None
2025-09-07T09:13:17.0090109Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:13:17.0091031Z   import pynvml  # type: ignore[import]
2025-09-07T09:13:19.0187219Z 
2025-09-07T09:13:19.2363957Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:13:19.2364359Z   what():  std::bad_array_new_length
2025-09-07T09:15:02.2494031Z Run failed with return code:  -6
2025-09-07T09:15:02.2494289Z Output:  None
2025-09-07T09:15:02.2494474Z Error:  None
2025-09-07T09:15:02.6616632Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:15:02.6617597Z   import pynvml  # type: ignore[import]
2025-09-07T09:15:04.6742872Z 
2025-09-07T09:15:04.8925300Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:15:04.8925685Z   what():  std::bad_array_new_length
2025-09-07T09:16:48.4021713Z Run failed with return code:  -6
2025-09-07T09:16:48.4021968Z Output:  None
2025-09-07T09:16:48.4022123Z Error:  None
2025-09-07T09:16:48.8111934Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:16:48.8112931Z   import pynvml  # type: ignore[import]
2025-09-07T09:16:50.8257853Z 
2025-09-07T09:16:51.0441441Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:16:51.0441828Z   what():  std::bad_array_new_length
2025-09-07T09:18:34.4552422Z Run failed with return code:  -6
2025-09-07T09:18:34.4552683Z Output:  None
2025-09-07T09:18:34.4552837Z Error:  None
2025-09-07T09:18:34.8632956Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:18:34.8634403Z   import pynvml  # type: ignore[import]
2025-09-07T09:18:36.8772474Z 
2025-09-07T09:18:37.0951010Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:18:37.0951400Z   what():  std::bad_array_new_length
2025-09-07T09:20:20.5611393Z Run failed with return code:  -6
2025-09-07T09:20:20.5611637Z Output:  None
2025-09-07T09:20:20.5611796Z Error:  None
2025-09-07T09:20:20.9673341Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:20:20.9674213Z   import pynvml  # type: ignore[import]
2025-09-07T09:20:22.9935139Z 
2025-09-07T09:20:23.2121456Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:20:23.2121836Z   what():  std::bad_array_new_length
2025-09-07T09:22:06.5632311Z Run failed with return code:  -6
2025-09-07T09:22:06.5632565Z Output:  None
2025-09-07T09:22:06.5633326Z Error:  None
2025-09-07T09:22:06.9847499Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:22:06.9848373Z   import pynvml  # type: ignore[import]
2025-09-07T09:22:09.0096286Z 
2025-09-07T09:22:09.2274620Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:22:09.2275030Z   what():  std::bad_array_new_length
2025-09-07T09:23:52.6179944Z Run failed with return code:  -6
2025-09-07T09:23:52.6180231Z Output:  None
2025-09-07T09:23:52.6180381Z Error:  None
2025-09-07T09:23:52.6222393Z accuracy            pass_rate=83.33%
2025-09-07T09:23:52.6227200Z calls_captured      gmean=0.00x mean=104.833x
2025-09-07T09:23:52.6229563Z unique_graphs       gmean=0.00x mean=0.833x
2025-09-07T09:23:52.6231831Z graph_breaks        gmean=0.00x mean=0.000x
2025-09-07T09:23:52.6233974Z unique_graph_breaks gmean=0.00x mean=0.000x
2025-09-07T09:23:52.6236118Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T09:23:52.6238221Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T09:23:52.6240246Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T09:23:52.6240897Z compilation_latency mean=4.119 seconds
2025-09-07T09:23:53.1528870Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --accuracy --no-translation-validation --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv
2025-09-07T09:23:53.5511014Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:23:53.5512013Z   import pynvml  # type: ignore[import]
2025-09-07T09:23:55.9953181Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:23:55.9954087Z   import pynvml  # type: ignore[import]
2025-09-07T09:23:58.0126945Z 
2025-09-07T09:23:59.9119766Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:23:59.9120844Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:23:59.9335210Z cpu  eval  BERT_pytorch                       
2025-09-07T09:24:00.4142571Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:00.6769328Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:00.9997987Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:21.6804381Z pass
2025-09-07T09:24:21.6805802Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:23.7734769Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:24:23.7735688Z   import pynvml  # type: ignore[import]
2025-09-07T09:24:25.7888256Z 
2025-09-07T09:24:27.9950456Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:24:27.9950752Z loading model: 0it [00:02, ?it/s]
2025-09-07T09:24:28.0046930Z cpu  eval  Background_Matting                 
2025-09-07T09:24:28.1154904Z pass_due_to_skip
2025-09-07T09:24:28.1155866Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:29.4650070Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:24:29.4650944Z   import pynvml  # type: ignore[import]
2025-09-07T09:24:31.4740975Z 
2025-09-07T09:24:33.4691693Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:24:33.4691996Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:24:33.4732086Z cpu  eval  LearningToPaint                    
2025-09-07T09:24:33.7847266Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:33.8259988Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:33.8615969Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:43.5233040Z pass
2025-09-07T09:24:43.5235253Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:24:45.4244875Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:24:45.4245768Z   import pynvml  # type: ignore[import]
2025-09-07T09:24:47.4250733Z 
2025-09-07T09:24:48.8599847Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:24:49.2539237Z 
2025-09-07T09:24:49.2539762Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:24:49.2542741Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:24:49.2543153Z cpu  eval  Super_SloMo                        
2025-09-07T09:25:09.3735546Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:09.3736101Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:25:09.9851153Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:10.6528417Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:41.3338823Z pass
2025-09-07T09:25:41.3340404Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:44.3051601Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:25:44.3052488Z   import pynvml  # type: ignore[import]
2025-09-07T09:25:46.3083725Z 
2025-09-07T09:25:47.0727774Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:25:47.0728058Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:25:47.0763752Z cpu  eval  alexnet                            
2025-09-07T09:25:47.2299217Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:47.2522451Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:47.2637451Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:57.0143618Z pass
2025-09-07T09:25:57.0148704Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:25:58.6591803Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:25:58.6592688Z   import pynvml  # type: ignore[import]
2025-09-07T09:26:00.6688233Z 
2025-09-07T09:26:02.1768272Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:26:02.1769651Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:26:02.1778963Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T09:26:02.3366409Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:02.3892581Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:02.4457247Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:09.2167030Z pass
2025-09-07T09:26:09.2167457Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:10.8636634Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:26:10.8637514Z   import pynvml  # type: ignore[import]
2025-09-07T09:26:12.8781926Z 
2025-09-07T09:26:14.3780585Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:26:14.3780930Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:26:14.3788061Z cpu  eval  basic_gnn_gcn                      
2025-09-07T09:26:14.4593099Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:14.5217315Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:14.5798316Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:22.2239735Z pass
2025-09-07T09:26:22.2240258Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:23.9150895Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:26:23.9151777Z   import pynvml  # type: ignore[import]
2025-09-07T09:26:25.9273586Z 
2025-09-07T09:26:27.4149134Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:26:27.4149422Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:26:27.4155692Z cpu  eval  basic_gnn_gin                      
2025-09-07T09:26:27.4994505Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:27.5531922Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:27.6747283Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:33.9684965Z pass
2025-09-07T09:26:33.9685358Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:35.5646910Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:26:35.5647798Z   import pynvml  # type: ignore[import]
2025-09-07T09:26:37.5732725Z 
2025-09-07T09:26:39.0598920Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:26:39.0599214Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:26:39.0606472Z cpu  eval  basic_gnn_sage                     
2025-09-07T09:26:39.1319899Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:39.1817587Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:39.2289459Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:45.5641378Z pass
2025-09-07T09:26:45.5641793Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:47.1639656Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:26:47.1640627Z   import pynvml  # type: ignore[import]
2025-09-07T09:26:49.1731535Z 
2025-09-07T09:26:49.4159661Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:26:49.4159977Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:26:49.4169482Z cpu  eval  dcgan                              
2025-09-07T09:26:49.4694507Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:49.4820416Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:49.4891445Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:57.1743525Z pass
2025-09-07T09:26:57.1746284Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:26:58.7185473Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:26:58.7186415Z   import pynvml  # type: ignore[import]
2025-09-07T09:27:00.7349637Z 
2025-09-07T09:27:02.3527103Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:27:02.3527425Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:27:02.3757204Z cpu  eval  demucs                             
2025-09-07T09:27:07.0914297Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:07.2538952Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:07.4014918Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:20.4234813Z pass
2025-09-07T09:27:20.4237720Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:22.2910393Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:27:22.2911302Z   import pynvml  # type: ignore[import]
2025-09-07T09:27:24.3154914Z 
2025-09-07T09:27:25.1296680Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:27:25.1296956Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:27:25.1462800Z cpu  eval  densenet121                        
2025-09-07T09:27:26.3514870Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:26.6070064Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:26.8605908Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:49.3051032Z pass
2025-09-07T09:27:49.3053944Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:27:52.0203606Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:27:52.0204531Z   import pynvml  # type: ignore[import]
2025-09-07T09:27:54.0390717Z 
2025-09-07T09:27:54.2567136Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:27:54.2567541Z   what():  std::bad_array_new_length
2025-09-07T09:29:36.7589385Z Run failed with return code:  -6
2025-09-07T09:29:36.7589631Z Output:  None
2025-09-07T09:29:36.7589789Z Error:  None
2025-09-07T09:29:37.1671128Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:29:37.1672037Z   import pynvml  # type: ignore[import]
2025-09-07T09:29:39.1935121Z 
2025-09-07T09:29:39.4152011Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:29:39.4152420Z   what():  std::bad_array_new_length
2025-09-07T09:31:21.6568990Z Run failed with return code:  -6
2025-09-07T09:31:21.6569253Z Output:  None
2025-09-07T09:31:21.6569413Z Error:  None
2025-09-07T09:31:22.0635864Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:31:22.0636754Z   import pynvml  # type: ignore[import]
2025-09-07T09:31:24.0779026Z 
2025-09-07T09:31:24.2947688Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:31:24.2948084Z   what():  std::bad_array_new_length
2025-09-07T09:33:06.6047010Z Run failed with return code:  -6
2025-09-07T09:33:06.6047294Z Output:  None
2025-09-07T09:33:06.6047441Z Error:  None
2025-09-07T09:33:07.0144480Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:33:07.0145338Z   import pynvml  # type: ignore[import]
2025-09-07T09:33:09.0279516Z 
2025-09-07T09:33:09.2451454Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:33:09.2452376Z   what():  std::bad_array_new_length
2025-09-07T09:34:51.4023818Z Run failed with return code:  -6
2025-09-07T09:34:51.4024083Z Output:  None
2025-09-07T09:34:51.4024232Z Error:  None
2025-09-07T09:34:51.8116110Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:34:51.8116985Z   import pynvml  # type: ignore[import]
2025-09-07T09:34:53.8285801Z 
2025-09-07T09:34:54.0467231Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:34:54.0467621Z   what():  std::bad_array_new_length
2025-09-07T09:36:37.3009774Z Run failed with return code:  -6
2025-09-07T09:36:37.3010027Z Output:  None
2025-09-07T09:36:37.3010183Z Error:  None
2025-09-07T09:36:37.7125462Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:36:37.7126393Z   import pynvml  # type: ignore[import]
2025-09-07T09:36:39.7287763Z 
2025-09-07T09:36:39.9466056Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:36:39.9466466Z   what():  std::bad_array_new_length
2025-09-07T09:38:22.3989325Z Run failed with return code:  -6
2025-09-07T09:38:22.3989580Z Output:  None
2025-09-07T09:38:22.3989739Z Error:  None
2025-09-07T09:38:22.8082502Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:38:22.8083503Z   import pynvml  # type: ignore[import]
2025-09-07T09:38:24.8333920Z 
2025-09-07T09:38:25.0509956Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:38:25.0510498Z   what():  std::bad_array_new_length
2025-09-07T09:40:07.0449959Z Run failed with return code:  -6
2025-09-07T09:40:07.0450216Z Output:  None
2025-09-07T09:40:07.0450404Z Error:  None
2025-09-07T09:40:07.4550275Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:40:07.4551212Z   import pynvml  # type: ignore[import]
2025-09-07T09:40:09.4687631Z 
2025-09-07T09:40:09.6862519Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:40:09.6862916Z   what():  std::bad_array_new_length
2025-09-07T09:41:51.8424319Z Run failed with return code:  -6
2025-09-07T09:41:51.8424579Z Output:  None
2025-09-07T09:41:51.8424737Z Error:  None
2025-09-07T09:41:52.2504078Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:41:52.2505035Z   import pynvml  # type: ignore[import]
2025-09-07T09:41:54.2695999Z 
2025-09-07T09:41:54.4857261Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:41:54.4857651Z   what():  std::bad_array_new_length
2025-09-07T09:43:39.1943064Z Run failed with return code:  -6
2025-09-07T09:43:39.1943326Z Output:  None
2025-09-07T09:43:39.1943478Z Error:  None
2025-09-07T09:43:39.6043685Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:43:39.6045207Z   import pynvml  # type: ignore[import]
2025-09-07T09:43:41.6222217Z 
2025-09-07T09:43:41.8403628Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:43:41.8404029Z   what():  std::bad_array_new_length
2025-09-07T09:45:23.7435721Z Run failed with return code:  -6
2025-09-07T09:45:23.7435975Z Output:  None
2025-09-07T09:45:23.7436131Z Error:  None
2025-09-07T09:45:23.7479260Z accuracy            pass_rate=91.67%
2025-09-07T09:45:23.7484296Z calls_captured      gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7486576Z unique_graphs       gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7488901Z graph_breaks        gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7491081Z unique_graph_breaks gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7493511Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7495368Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7497433Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T09:45:23.7498080Z compilation_latency mean=0.000 seconds
2025-09-07T09:45:24.2825489Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *maxautotune-true* ]]
2025-09-07T09:45:24.2826365Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *cudagraphs_low_precision-true* ]]
2025-09-07T09:45:24.2826871Z + for target in "${targets[@]}"
2025-09-07T09:45:24.2827069Z + target_flag=('--performance')
2025-09-07T09:45:24.2827251Z + local target_flag
2025-09-07T09:45:24.2827420Z + [[ performance == \p\e\r\f\o\r\m\a\n\c\e ]]
2025-09-07T09:45:24.2827642Z + target_flag+=(--cold-start-latency)
2025-09-07T09:45:24.2828093Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *freezing-true* ]]
2025-09-07T09:45:24.2828791Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *default-true* ]]
2025-09-07T09:45:24.2829990Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv
2025-09-07T09:45:24.6763168Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:45:24.6764037Z   import pynvml  # type: ignore[import]
2025-09-07T09:45:27.1264649Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:45:27.1265635Z   import pynvml  # type: ignore[import]
2025-09-07T09:45:29.1494279Z 
2025-09-07T09:45:30.7817246Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:45:30.7817576Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:45:30.7995136Z cpu  eval  BERT_pytorch                       
2025-09-07T09:45:55.5254378Z 
2025-09-07T09:45:55.6567223Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:45:55.7855869Z running benchmark:   3% 1/30 [00:00<00:03,  7.63it/s]
2025-09-07T09:45:55.9159390Z running benchmark:   7% 2/30 [00:00<00:03,  7.71it/s]
2025-09-07T09:45:56.0428017Z running benchmark:  10% 3/30 [00:00<00:03,  7.69it/s]
2025-09-07T09:45:56.1712478Z running benchmark:  13% 4/30 [00:00<00:03,  7.77it/s]
2025-09-07T09:45:56.3712774Z running benchmark:  17% 5/30 [00:00<00:03,  7.77it/s]
2025-09-07T09:45:56.4997754Z running benchmark:  20% 6/30 [00:00<00:03,  6.54it/s]
2025-09-07T09:45:56.6277199Z running benchmark:  23% 7/30 [00:00<00:03,  6.90it/s]
2025-09-07T09:45:56.7562702Z running benchmark:  27% 8/30 [00:01<00:03,  7.17it/s]
2025-09-07T09:45:56.8832577Z running benchmark:  30% 9/30 [00:01<00:02,  7.35it/s]
2025-09-07T09:45:57.0120758Z running benchmark:  33% 10/30 [00:01<00:02,  7.50it/s]
2025-09-07T09:45:57.1390880Z running benchmark:  37% 11/30 [00:01<00:02,  7.58it/s]
2025-09-07T09:45:57.2678531Z running benchmark:  40% 12/30 [00:01<00:02,  7.67it/s]
2025-09-07T09:45:57.3946707Z running benchmark:  43% 13/30 [00:01<00:02,  7.70it/s]
2025-09-07T09:45:57.5216903Z running benchmark:  47% 14/30 [00:01<00:02,  7.75it/s]
2025-09-07T09:45:57.6483452Z running benchmark:  50% 15/30 [00:01<00:01,  7.79it/s]
2025-09-07T09:45:57.7763262Z running benchmark:  53% 16/30 [00:02<00:01,  7.82it/s]
2025-09-07T09:45:57.9035907Z running benchmark:  57% 17/30 [00:02<00:01,  7.82it/s]
2025-09-07T09:45:58.0318511Z running benchmark:  60% 18/30 [00:02<00:01,  7.83it/s]
2025-09-07T09:45:58.1583227Z running benchmark:  63% 19/30 [00:02<00:01,  7.82it/s]
2025-09-07T09:45:58.2863919Z running benchmark:  67% 20/30 [00:02<00:01,  7.85it/s]
2025-09-07T09:45:58.4133200Z running benchmark:  70% 21/30 [00:02<00:01,  7.84it/s]
2025-09-07T09:45:58.5414431Z running benchmark:  73% 22/30 [00:02<00:01,  7.85it/s]
2025-09-07T09:45:58.6691211Z running benchmark:  77% 23/30 [00:03<00:00,  7.84it/s]
2025-09-07T09:45:58.7982353Z running benchmark:  80% 24/30 [00:03<00:00,  7.83it/s]
2025-09-07T09:45:58.9261316Z running benchmark:  83% 25/30 [00:03<00:00,  7.81it/s]
2025-09-07T09:45:59.0548118Z running benchmark:  87% 26/30 [00:03<00:00,  7.81it/s]
2025-09-07T09:45:59.1814536Z running benchmark:  90% 27/30 [00:03<00:00,  7.80it/s]
2025-09-07T09:45:59.3097714Z running benchmark:  93% 28/30 [00:03<00:00,  7.83it/s]
2025-09-07T09:45:59.4359720Z running benchmark:  97% 29/30 [00:03<00:00,  7.82it/s]
2025-09-07T09:45:59.4360081Z running benchmark: 100% 30/30 [00:03<00:00,  7.85it/s]
2025-09-07T09:45:59.4360350Z running benchmark: 100% 30/30 [00:03<00:00,  7.67it/s]
2025-09-07T09:45:59.5219108Z 1.406x
2025-09-07T09:45:59.5221787Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:46:01.7163294Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:46:01.7164252Z   import pynvml  # type: ignore[import]
2025-09-07T09:46:03.7228702Z 
2025-09-07T09:46:05.9478002Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:46:05.9478296Z loading model: 0it [00:02, ?it/s]
2025-09-07T09:46:05.9590020Z cpu  eval  Background_Matting                 
2025-09-07T09:46:40.1418768Z 
2025-09-07T09:46:40.5687504Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:46:40.9820113Z running benchmark:   3% 1/30 [00:00<00:12,  2.34it/s]
2025-09-07T09:46:41.4588803Z running benchmark:   7% 2/30 [00:00<00:11,  2.39it/s]
2025-09-07T09:46:41.8726874Z running benchmark:  10% 3/30 [00:01<00:12,  2.25it/s]
2025-09-07T09:46:42.2838712Z running benchmark:  13% 4/30 [00:01<00:11,  2.31it/s]
2025-09-07T09:46:42.6933015Z running benchmark:  17% 5/30 [00:02<00:10,  2.35it/s]
2025-09-07T09:46:43.1067697Z running benchmark:  20% 6/30 [00:02<00:10,  2.38it/s]
2025-09-07T09:46:43.5146157Z running benchmark:  23% 7/30 [00:02<00:09,  2.39it/s]
2025-09-07T09:46:43.9260014Z running benchmark:  27% 8/30 [00:03<00:09,  2.41it/s]
2025-09-07T09:46:44.3405988Z running benchmark:  30% 9/30 [00:03<00:08,  2.42it/s]
2025-09-07T09:46:44.7536317Z running benchmark:  33% 10/30 [00:04<00:08,  2.42it/s]
2025-09-07T09:46:45.1679633Z running benchmark:  37% 11/30 [00:04<00:07,  2.42it/s]
2025-09-07T09:46:45.6489529Z running benchmark:  40% 12/30 [00:05<00:07,  2.42it/s]
2025-09-07T09:46:46.0601432Z running benchmark:  43% 13/30 [00:05<00:07,  2.30it/s]
2025-09-07T09:46:46.4801673Z running benchmark:  47% 14/30 [00:05<00:06,  2.34it/s]
2025-09-07T09:46:46.8992777Z running benchmark:  50% 15/30 [00:06<00:06,  2.35it/s]
2025-09-07T09:46:47.3196461Z running benchmark:  53% 16/30 [00:06<00:05,  2.36it/s]
2025-09-07T09:46:47.7442354Z running benchmark:  57% 17/30 [00:07<00:05,  2.37it/s]
2025-09-07T09:46:48.1601632Z running benchmark:  60% 18/30 [00:07<00:05,  2.36it/s]
2025-09-07T09:46:48.5791338Z running benchmark:  63% 19/30 [00:08<00:04,  2.38it/s]
2025-09-07T09:46:48.9974170Z running benchmark:  67% 20/30 [00:08<00:04,  2.38it/s]
2025-09-07T09:46:49.4156656Z running benchmark:  70% 21/30 [00:08<00:03,  2.38it/s]
2025-09-07T09:46:49.9010832Z running benchmark:  73% 22/30 [00:09<00:03,  2.39it/s]
2025-09-07T09:46:50.3200645Z running benchmark:  77% 23/30 [00:09<00:03,  2.28it/s]
2025-09-07T09:46:50.7426235Z running benchmark:  80% 24/30 [00:10<00:02,  2.31it/s]
2025-09-07T09:46:51.1589759Z running benchmark:  83% 25/30 [00:10<00:02,  2.33it/s]
2025-09-07T09:46:51.5735470Z running benchmark:  87% 26/30 [00:11<00:01,  2.35it/s]
2025-09-07T09:46:51.9946556Z running benchmark:  90% 27/30 [00:11<00:01,  2.37it/s]
2025-09-07T09:46:52.4178630Z running benchmark:  93% 28/30 [00:11<00:00,  2.37it/s]
2025-09-07T09:46:52.8382409Z running benchmark:  97% 29/30 [00:12<00:00,  2.37it/s]
2025-09-07T09:46:52.8382746Z running benchmark: 100% 30/30 [00:12<00:00,  2.37it/s]
2025-09-07T09:46:52.8383025Z running benchmark: 100% 30/30 [00:12<00:00,  2.36it/s]
2025-09-07T09:46:52.9588620Z 0.904x
2025-09-07T09:46:52.9591793Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:46:55.3432035Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:46:55.3432950Z   import pynvml  # type: ignore[import]
2025-09-07T09:46:57.3585394Z 
2025-09-07T09:46:59.4115558Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:46:59.4115860Z loading model: 0it [00:02, ?it/s]
2025-09-07T09:46:59.4149679Z cpu  eval  LearningToPaint                    
2025-09-07T09:47:18.1614973Z 
2025-09-07T09:47:18.3075233Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:47:18.4475480Z running benchmark:  10% 3/30 [00:00<00:01, 20.61it/s]
2025-09-07T09:47:18.5884854Z running benchmark:  20% 6/30 [00:00<00:01, 21.08it/s]
2025-09-07T09:47:18.7291030Z running benchmark:  30% 9/30 [00:00<00:00, 21.17it/s]
2025-09-07T09:47:18.8684709Z running benchmark:  40% 12/30 [00:00<00:00, 21.24it/s]
2025-09-07T09:47:19.0093280Z running benchmark:  50% 15/30 [00:00<00:00, 21.34it/s]
2025-09-07T09:47:19.1482681Z running benchmark:  60% 18/30 [00:00<00:00, 21.32it/s]
2025-09-07T09:47:19.2887977Z running benchmark:  70% 21/30 [00:00<00:00, 21.41it/s]
2025-09-07T09:47:19.4296199Z running benchmark:  80% 24/30 [00:01<00:00, 21.39it/s]
2025-09-07T09:47:19.5683467Z running benchmark:  90% 27/30 [00:01<00:00, 21.37it/s]
2025-09-07T09:47:19.5683811Z running benchmark: 100% 30/30 [00:01<00:00, 21.45it/s]
2025-09-07T09:47:19.5684104Z running benchmark: 100% 30/30 [00:01<00:00, 21.33it/s]
2025-09-07T09:47:19.6556837Z 1.202x
2025-09-07T09:47:19.6559715Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:47:21.9119429Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:47:21.9120317Z   import pynvml  # type: ignore[import]
2025-09-07T09:47:23.9249748Z 
2025-09-07T09:47:25.3937882Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:47:25.9751572Z 
2025-09-07T09:47:25.9751958Z loading model: 0it [00:02, ?it/s]
2025-09-07T09:47:25.9752953Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:47:25.9753304Z cpu  eval  Super_SloMo                        
2025-09-07T09:47:25.9755602Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T09:48:26.9590690Z 
2025-09-07T09:48:27.7331393Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:48:28.4932058Z running benchmark:   3% 1/30 [00:00<00:22,  1.29it/s]
2025-09-07T09:48:29.3152920Z running benchmark:   7% 2/30 [00:01<00:21,  1.31it/s]
2025-09-07T09:48:30.0699427Z running benchmark:  10% 3/30 [00:02<00:21,  1.26it/s]
2025-09-07T09:48:30.8293149Z running benchmark:  13% 4/30 [00:03<00:20,  1.29it/s]
2025-09-07T09:48:31.5840607Z running benchmark:  17% 5/30 [00:03<00:19,  1.30it/s]
2025-09-07T09:48:32.3484404Z running benchmark:  20% 6/30 [00:04<00:18,  1.31it/s]
2025-09-07T09:48:33.1709744Z running benchmark:  23% 7/30 [00:05<00:17,  1.31it/s]
2025-09-07T09:48:33.9274521Z running benchmark:  27% 8/30 [00:06<00:17,  1.28it/s]
2025-09-07T09:48:34.6870144Z running benchmark:  30% 9/30 [00:06<00:16,  1.29it/s]
2025-09-07T09:48:35.4440022Z running benchmark:  33% 10/30 [00:07<00:15,  1.30it/s]
2025-09-07T09:48:36.2039517Z running benchmark:  37% 11/30 [00:08<00:14,  1.31it/s]
2025-09-07T09:48:36.9532087Z running benchmark:  40% 12/30 [00:09<00:13,  1.31it/s]
2025-09-07T09:48:37.7774045Z running benchmark:  43% 13/30 [00:09<00:12,  1.32it/s]
2025-09-07T09:48:38.5282993Z running benchmark:  47% 14/30 [00:10<00:12,  1.28it/s]
2025-09-07T09:48:39.2854420Z running benchmark:  50% 15/30 [00:11<00:11,  1.30it/s]
2025-09-07T09:48:40.0405317Z running benchmark:  53% 16/30 [00:12<00:10,  1.30it/s]
2025-09-07T09:48:40.7943467Z running benchmark:  57% 17/30 [00:13<00:09,  1.31it/s]
2025-09-07T09:48:41.6189316Z running benchmark:  60% 18/30 [00:13<00:09,  1.32it/s]
2025-09-07T09:48:42.3749376Z running benchmark:  63% 19/30 [00:14<00:08,  1.28it/s]
2025-09-07T09:48:43.1284231Z running benchmark:  67% 20/30 [00:15<00:07,  1.30it/s]
2025-09-07T09:48:43.8881040Z running benchmark:  70% 21/30 [00:16<00:06,  1.30it/s]
2025-09-07T09:48:44.6432162Z running benchmark:  73% 22/30 [00:16<00:06,  1.31it/s]
2025-09-07T09:48:45.4775401Z running benchmark:  77% 23/30 [00:17<00:05,  1.31it/s]
2025-09-07T09:48:46.2265422Z running benchmark:  80% 24/30 [00:18<00:04,  1.28it/s]
2025-09-07T09:48:46.9796057Z running benchmark:  83% 25/30 [00:19<00:03,  1.29it/s]
2025-09-07T09:48:47.7294322Z running benchmark:  87% 26/30 [00:20<00:03,  1.30it/s]
2025-09-07T09:48:48.4890811Z running benchmark:  90% 27/30 [00:20<00:02,  1.31it/s]
2025-09-07T09:48:49.2516971Z running benchmark:  93% 28/30 [00:21<00:01,  1.31it/s]
2025-09-07T09:48:50.0788071Z running benchmark:  97% 29/30 [00:22<00:00,  1.31it/s]
2025-09-07T09:48:50.0790721Z running benchmark: 100% 30/30 [00:23<00:00,  1.28it/s]
2025-09-07T09:48:50.0791060Z running benchmark: 100% 30/30 [00:23<00:00,  1.30it/s]
2025-09-07T09:48:50.2195784Z 1.109x
2025-09-07T09:48:50.2199070Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:48:52.7606943Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:48:52.7607895Z   import pynvml  # type: ignore[import]
2025-09-07T09:48:54.7773274Z 
2025-09-07T09:48:55.6189664Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:48:55.6189968Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:48:55.6254255Z cpu  eval  alexnet                            
2025-09-07T09:49:08.5124725Z 
2025-09-07T09:49:08.6493206Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:49:08.7785298Z running benchmark:   7% 2/30 [00:00<00:01, 14.66it/s]
2025-09-07T09:49:08.9122130Z running benchmark:  13% 4/30 [00:00<00:01, 15.13it/s]
2025-09-07T09:49:09.0444240Z running benchmark:  20% 6/30 [00:00<00:01, 15.07it/s]
2025-09-07T09:49:09.1743150Z running benchmark:  27% 8/30 [00:00<00:01, 15.08it/s]
2025-09-07T09:49:09.3034375Z running benchmark:  33% 10/30 [00:00<00:01, 15.19it/s]
2025-09-07T09:49:09.4326020Z running benchmark:  40% 12/30 [00:00<00:01, 15.29it/s]
2025-09-07T09:49:09.5653331Z running benchmark:  47% 14/30 [00:00<00:01, 15.36it/s]
2025-09-07T09:49:09.7624687Z running benchmark:  53% 16/30 [00:01<00:00, 15.26it/s]
2025-09-07T09:49:09.8955376Z running benchmark:  60% 18/30 [00:01<00:00, 13.18it/s]
2025-09-07T09:49:10.0281545Z running benchmark:  67% 20/30 [00:01<00:00, 13.70it/s]
2025-09-07T09:49:10.1563913Z running benchmark:  73% 22/30 [00:01<00:00, 14.10it/s]
2025-09-07T09:49:10.2859931Z running benchmark:  80% 24/30 [00:01<00:00, 14.52it/s]
2025-09-07T09:49:10.4155150Z running benchmark:  87% 26/30 [00:01<00:00, 14.79it/s]
2025-09-07T09:49:10.5463515Z running benchmark:  93% 28/30 [00:01<00:00, 14.98it/s]
2025-09-07T09:49:10.5463918Z running benchmark: 100% 30/30 [00:02<00:00, 15.07it/s]
2025-09-07T09:49:10.5464209Z running benchmark: 100% 30/30 [00:02<00:00, 14.75it/s]
2025-09-07T09:49:10.6171278Z 1.426x
2025-09-07T09:49:10.6175125Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:49:12.6711374Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:49:12.6712262Z   import pynvml  # type: ignore[import]
2025-09-07T09:49:14.6883378Z 
2025-09-07T09:49:16.1848986Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:49:16.1849267Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:49:16.1857457Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T09:49:24.3090854Z 
2025-09-07T09:49:24.4283305Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:49:24.5446091Z running benchmark:  10% 3/30 [00:00<00:01, 25.24it/s]
2025-09-07T09:49:24.6600618Z running benchmark:  20% 6/30 [00:00<00:00, 25.56it/s]
2025-09-07T09:49:24.7789190Z running benchmark:  30% 9/30 [00:00<00:00, 25.75it/s]
2025-09-07T09:49:24.8942883Z running benchmark:  40% 12/30 [00:00<00:00, 25.55it/s]
2025-09-07T09:49:25.0099070Z running benchmark:  50% 15/30 [00:00<00:00, 25.71it/s]
2025-09-07T09:49:25.1288765Z running benchmark:  60% 18/30 [00:00<00:00, 25.79it/s]
2025-09-07T09:49:25.2458547Z running benchmark:  70% 21/30 [00:00<00:00, 25.60it/s]
2025-09-07T09:49:25.3602169Z running benchmark:  80% 24/30 [00:00<00:00, 25.62it/s]
2025-09-07T09:49:25.4770935Z running benchmark:  90% 27/30 [00:01<00:00, 25.81it/s]
2025-09-07T09:49:25.4771398Z running benchmark: 100% 30/30 [00:01<00:00, 25.76it/s]
2025-09-07T09:49:25.4771680Z running benchmark: 100% 30/30 [00:01<00:00, 25.69it/s]
2025-09-07T09:49:25.5350361Z 1.601x
2025-09-07T09:49:25.5353729Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:49:27.5811759Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:49:27.5812630Z   import pynvml  # type: ignore[import]
2025-09-07T09:49:29.5972482Z 
2025-09-07T09:49:31.0881039Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:49:31.0881339Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:49:31.0884318Z cpu  eval  basic_gnn_gcn                      
2025-09-07T09:49:40.7016826Z 
2025-09-07T09:49:40.8185933Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:49:40.9284610Z running benchmark:   7% 2/30 [00:00<00:01, 17.16it/s]
2025-09-07T09:49:41.0399486Z running benchmark:  13% 4/30 [00:00<00:01, 17.75it/s]
2025-09-07T09:49:41.1474062Z running benchmark:  20% 6/30 [00:00<00:01, 17.85it/s]
2025-09-07T09:49:41.2561679Z running benchmark:  27% 8/30 [00:00<00:01, 18.13it/s]
2025-09-07T09:49:41.3660930Z running benchmark:  33% 10/30 [00:00<00:01, 18.23it/s]
2025-09-07T09:49:41.4746934Z running benchmark:  40% 12/30 [00:00<00:00, 18.22it/s]
2025-09-07T09:49:41.5857450Z running benchmark:  47% 14/30 [00:00<00:00, 18.27it/s]
2025-09-07T09:49:41.6942831Z running benchmark:  53% 16/30 [00:00<00:00, 18.19it/s]
2025-09-07T09:49:41.8084798Z running benchmark:  60% 18/30 [00:00<00:00, 18.27it/s]
2025-09-07T09:49:41.9198666Z running benchmark:  67% 20/30 [00:01<00:00, 18.03it/s]
2025-09-07T09:49:42.0298033Z running benchmark:  73% 22/30 [00:01<00:00, 18.00it/s]
2025-09-07T09:49:42.1410081Z running benchmark:  80% 24/30 [00:01<00:00, 18.06it/s]
2025-09-07T09:49:42.2490301Z running benchmark:  87% 26/30 [00:01<00:00, 18.04it/s]
2025-09-07T09:49:42.4308232Z running benchmark:  93% 28/30 [00:01<00:00, 18.18it/s]
2025-09-07T09:49:42.4308586Z running benchmark: 100% 30/30 [00:01<00:00, 15.19it/s]
2025-09-07T09:49:42.4308845Z running benchmark: 100% 30/30 [00:01<00:00, 17.35it/s]
2025-09-07T09:49:42.4799441Z 1.114x
2025-09-07T09:49:42.4803096Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:49:44.4862558Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:49:44.4863441Z   import pynvml  # type: ignore[import]
2025-09-07T09:49:46.5108677Z 
2025-09-07T09:49:47.9890860Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:49:47.9891145Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:49:47.9897192Z cpu  eval  basic_gnn_gin                      
2025-09-07T09:49:56.4572295Z 
2025-09-07T09:49:56.6001225Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:49:56.7372769Z running benchmark:  10% 3/30 [00:00<00:01, 21.06it/s]
2025-09-07T09:49:56.8754304Z running benchmark:  20% 6/30 [00:00<00:01, 21.53it/s]
2025-09-07T09:49:57.0126766Z running benchmark:  30% 9/30 [00:00<00:00, 21.61it/s]
2025-09-07T09:49:57.1512811Z running benchmark:  40% 12/30 [00:00<00:00, 21.71it/s]
2025-09-07T09:49:57.2896403Z running benchmark:  50% 15/30 [00:00<00:00, 21.69it/s]
2025-09-07T09:49:57.4283290Z running benchmark:  60% 18/30 [00:00<00:00, 21.69it/s]
2025-09-07T09:49:57.5655261Z running benchmark:  70% 21/30 [00:00<00:00, 21.67it/s]
2025-09-07T09:49:57.7039616Z running benchmark:  80% 24/30 [00:01<00:00, 21.73it/s]
2025-09-07T09:49:57.8406626Z running benchmark:  90% 27/30 [00:01<00:00, 21.71it/s]
2025-09-07T09:49:57.8407063Z running benchmark: 100% 30/30 [00:01<00:00, 21.79it/s]
2025-09-07T09:49:57.8407324Z running benchmark: 100% 30/30 [00:01<00:00, 21.69it/s]
2025-09-07T09:49:57.8889857Z 1.055x
2025-09-07T09:49:57.8893488Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:49:59.8927736Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:49:59.8928606Z   import pynvml  # type: ignore[import]
2025-09-07T09:50:01.9128497Z 
2025-09-07T09:50:03.3952449Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:50:03.3952756Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:50:03.3957815Z cpu  eval  basic_gnn_sage                     
2025-09-07T09:50:10.3278246Z 
2025-09-07T09:50:10.4707255Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:50:10.6076887Z running benchmark:  10% 3/30 [00:00<00:01, 21.06it/s]
2025-09-07T09:50:10.7453169Z running benchmark:  20% 6/30 [00:00<00:01, 21.54it/s]
2025-09-07T09:50:10.9519117Z running benchmark:  30% 9/30 [00:00<00:00, 21.66it/s]
2025-09-07T09:50:11.0887507Z running benchmark:  40% 12/30 [00:00<00:00, 18.14it/s]
2025-09-07T09:50:11.2262461Z running benchmark:  50% 15/30 [00:00<00:00, 19.34it/s]
2025-09-07T09:50:11.3637866Z running benchmark:  60% 18/30 [00:00<00:00, 20.12it/s]
2025-09-07T09:50:11.4985359Z running benchmark:  70% 21/30 [00:01<00:00, 20.64it/s]
2025-09-07T09:50:11.6355161Z running benchmark:  80% 24/30 [00:01<00:00, 21.13it/s]
2025-09-07T09:50:11.7723299Z running benchmark:  90% 27/30 [00:01<00:00, 21.37it/s]
2025-09-07T09:50:11.7723622Z running benchmark: 100% 30/30 [00:01<00:00, 21.54it/s]
2025-09-07T09:50:11.7723885Z running benchmark: 100% 30/30 [00:01<00:00, 20.77it/s]
2025-09-07T09:50:11.8250148Z 1.066x
2025-09-07T09:50:11.8253941Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:50:13.8465957Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:50:13.8466984Z   import pynvml  # type: ignore[import]
2025-09-07T09:50:15.8673018Z 
2025-09-07T09:50:16.1145678Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:50:16.1146496Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:50:16.1157563Z cpu  eval  dcgan                              
2025-09-07T09:50:26.6809477Z 
2025-09-07T09:50:26.8001060Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:50:26.9188092Z running benchmark:  20% 6/30 [00:00<00:00, 50.54it/s]
2025-09-07T09:50:27.0368049Z running benchmark:  40% 12/30 [00:00<00:00, 50.53it/s]
2025-09-07T09:50:27.2245482Z running benchmark:  60% 18/30 [00:00<00:00, 50.67it/s]
2025-09-07T09:50:27.3418273Z running benchmark:  80% 24/30 [00:00<00:00, 41.16it/s]
2025-09-07T09:50:27.3418649Z running benchmark: 100% 30/30 [00:00<00:00, 44.30it/s]
2025-09-07T09:50:27.3420070Z running benchmark: 100% 30/30 [00:00<00:00, 45.42it/s]
2025-09-07T09:50:27.3982236Z 0.982x
2025-09-07T09:50:27.3985222Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:50:29.3578872Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:50:29.3580567Z   import pynvml  # type: ignore[import]
2025-09-07T09:50:31.3729420Z 
2025-09-07T09:50:33.0549669Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:50:33.0549955Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:50:33.0739841Z cpu  eval  demucs                             
2025-09-07T09:50:57.5814333Z 
2025-09-07T09:50:57.7151919Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:50:57.8451637Z running benchmark:   3% 1/30 [00:00<00:03,  7.49it/s]
2025-09-07T09:50:57.9813645Z running benchmark:   7% 2/30 [00:00<00:03,  7.61it/s]
2025-09-07T09:50:58.1128737Z running benchmark:  10% 3/30 [00:00<00:03,  7.48it/s]
2025-09-07T09:50:58.2442035Z running benchmark:  13% 4/30 [00:00<00:03,  7.53it/s]
2025-09-07T09:50:58.3741861Z running benchmark:  17% 5/30 [00:00<00:03,  7.56it/s]
2025-09-07T09:50:58.5046483Z running benchmark:  20% 6/30 [00:00<00:03,  7.61it/s]
2025-09-07T09:50:58.6365942Z running benchmark:  23% 7/30 [00:00<00:03,  7.62it/s]
2025-09-07T09:50:58.7675423Z running benchmark:  27% 8/30 [00:01<00:02,  7.61it/s]
2025-09-07T09:50:58.8988256Z running benchmark:  30% 9/30 [00:01<00:02,  7.62it/s]
2025-09-07T09:50:59.0282602Z running benchmark:  33% 10/30 [00:01<00:02,  7.62it/s]
2025-09-07T09:50:59.1575233Z running benchmark:  37% 11/30 [00:01<00:02,  7.65it/s]
2025-09-07T09:50:59.2886198Z running benchmark:  40% 12/30 [00:01<00:02,  7.68it/s]
2025-09-07T09:50:59.4193562Z running benchmark:  43% 13/30 [00:01<00:02,  7.66it/s]
2025-09-07T09:50:59.5507786Z running benchmark:  47% 14/30 [00:01<00:02,  7.66it/s]
2025-09-07T09:50:59.7516848Z running benchmark:  50% 15/30 [00:01<00:01,  7.64it/s]
2025-09-07T09:50:59.8836316Z running benchmark:  53% 16/30 [00:02<00:02,  6.58it/s]
2025-09-07T09:51:00.0137049Z running benchmark:  57% 17/30 [00:02<00:01,  6.85it/s]
2025-09-07T09:51:00.1452042Z running benchmark:  60% 18/30 [00:02<00:01,  7.09it/s]
2025-09-07T09:51:00.2752840Z running benchmark:  63% 19/30 [00:02<00:01,  7.23it/s]
2025-09-07T09:51:00.4057047Z running benchmark:  67% 20/30 [00:02<00:01,  7.36it/s]
2025-09-07T09:51:00.5368880Z running benchmark:  70% 21/30 [00:02<00:01,  7.45it/s]
2025-09-07T09:51:00.6674577Z running benchmark:  73% 22/30 [00:02<00:01,  7.50it/s]
2025-09-07T09:51:00.7979551Z running benchmark:  77% 23/30 [00:03<00:00,  7.55it/s]
2025-09-07T09:51:00.9267298Z running benchmark:  80% 24/30 [00:03<00:00,  7.58it/s]
2025-09-07T09:51:01.0578671Z running benchmark:  83% 25/30 [00:03<00:00,  7.64it/s]
2025-09-07T09:51:01.1882533Z running benchmark:  87% 26/30 [00:03<00:00,  7.63it/s]
2025-09-07T09:51:01.3187173Z running benchmark:  90% 27/30 [00:03<00:00,  7.64it/s]
2025-09-07T09:51:01.4502981Z running benchmark:  93% 28/30 [00:03<00:00,  7.65it/s]
2025-09-07T09:51:01.5803500Z running benchmark:  97% 29/30 [00:03<00:00,  7.64it/s]
2025-09-07T09:51:01.5804377Z running benchmark: 100% 30/30 [00:03<00:00,  7.65it/s]
2025-09-07T09:51:01.5804702Z running benchmark: 100% 30/30 [00:03<00:00,  7.50it/s]
2025-09-07T09:51:01.6837978Z 1.048x
2025-09-07T09:51:01.6840979Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:51:03.8027232Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:51:03.8028329Z   import pynvml  # type: ignore[import]
2025-09-07T09:51:05.8291405Z 
2025-09-07T09:51:06.8366780Z loading model: 0it [00:00, ?it/s]
2025-09-07T09:51:06.8367061Z loading model: 0it [00:01, ?it/s]
2025-09-07T09:51:06.8521270Z cpu  eval  densenet121                        
2025-09-07T09:52:15.4314251Z 
2025-09-07T09:52:15.7497386Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T09:52:16.0663101Z running benchmark:   3% 1/30 [00:00<00:09,  3.15it/s]
2025-09-07T09:52:16.3843475Z running benchmark:   7% 2/30 [00:00<00:08,  3.15it/s]
2025-09-07T09:52:16.6986908Z running benchmark:  10% 3/30 [00:00<00:08,  3.15it/s]
2025-09-07T09:52:17.0150461Z running benchmark:  13% 4/30 [00:01<00:08,  3.16it/s]
2025-09-07T09:52:17.3339746Z running benchmark:  17% 5/30 [00:01<00:07,  3.16it/s]
2025-09-07T09:52:17.6490666Z running benchmark:  20% 6/30 [00:01<00:07,  3.15it/s]
2025-09-07T09:52:17.9661930Z running benchmark:  23% 7/30 [00:02<00:07,  3.16it/s]
2025-09-07T09:52:18.2843201Z running benchmark:  27% 8/30 [00:02<00:06,  3.16it/s]
2025-09-07T09:52:18.5999974Z running benchmark:  30% 9/30 [00:02<00:06,  3.15it/s]
2025-09-07T09:52:18.9128139Z running benchmark:  33% 10/30 [00:03<00:06,  3.16it/s]
2025-09-07T09:52:19.2987697Z running benchmark:  37% 11/30 [00:03<00:05,  3.17it/s]
2025-09-07T09:52:19.6158773Z running benchmark:  40% 12/30 [00:03<00:06,  2.97it/s]
2025-09-07T09:52:19.9312840Z running benchmark:  43% 13/30 [00:04<00:05,  3.02it/s]
2025-09-07T09:52:20.2478341Z running benchmark:  47% 14/30 [00:04<00:05,  3.07it/s]
2025-09-07T09:52:20.5619115Z running benchmark:  50% 15/30 [00:04<00:04,  3.09it/s]
2025-09-07T09:52:20.8771835Z running benchmark:  53% 16/30 [00:05<00:04,  3.12it/s]
2025-09-07T09:52:21.1924908Z running benchmark:  57% 17/30 [00:05<00:04,  3.14it/s]
2025-09-07T09:52:21.5083519Z running benchmark:  60% 18/30 [00:05<00:03,  3.15it/s]
2025-09-07T09:52:21.8251589Z running benchmark:  63% 19/30 [00:06<00:03,  3.15it/s]
2025-09-07T09:52:22.1411767Z running benchmark:  67% 20/30 [00:06<00:03,  3.15it/s]
2025-09-07T09:52:22.4579565Z running benchmark:  70% 21/30 [00:06<00:02,  3.16it/s]
2025-09-07T09:52:22.7736807Z running benchmark:  73% 22/30 [00:07<00:02,  3.16it/s]
2025-09-07T09:52:23.0899034Z running benchmark:  77% 23/30 [00:07<00:02,  3.16it/s]
2025-09-07T09:52:23.4770862Z running benchmark:  80% 24/30 [00:07<00:01,  3.16it/s]
2025-09-07T09:52:23.7937983Z running benchmark:  83% 25/30 [00:08<00:01,  2.96it/s]
2025-09-07T09:52:24.1118282Z running benchmark:  87% 26/30 [00:08<00:01,  3.02it/s]
2025-09-07T09:52:24.4282535Z running benchmark:  90% 27/30 [00:08<00:00,  3.05it/s]
2025-09-07T09:52:24.7478151Z running benchmark:  93% 28/30 [00:08<00:00,  3.09it/s]
2025-09-07T09:52:25.0694877Z running benchmark:  97% 29/30 [00:09<00:00,  3.10it/s]
2025-09-07T09:52:25.0695236Z running benchmark: 100% 30/30 [00:09<00:00,  3.10it/s]
2025-09-07T09:52:25.0697281Z running benchmark: 100% 30/30 [00:09<00:00,  3.11it/s]
2025-09-07T09:52:25.2294634Z 2.140x
2025-09-07T09:52:25.2297182Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T09:52:27.9254193Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:52:27.9255588Z   import pynvml  # type: ignore[import]
2025-09-07T09:52:29.9445378Z 
2025-09-07T09:52:30.1619514Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:52:30.1619902Z   what():  std::bad_array_new_length
2025-09-07T09:54:13.3647005Z Run failed with return code:  -6
2025-09-07T09:54:13.3647281Z Output:  None
2025-09-07T09:54:13.3647435Z Error:  None
2025-09-07T09:54:13.7768566Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:54:13.7769522Z   import pynvml  # type: ignore[import]
2025-09-07T09:54:15.7974435Z 
2025-09-07T09:54:16.0147628Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:54:16.0148046Z   what():  std::bad_array_new_length
2025-09-07T09:55:58.8119728Z Run failed with return code:  -6
2025-09-07T09:55:58.8119997Z Output:  None
2025-09-07T09:55:58.8120149Z Error:  None
2025-09-07T09:55:59.2230256Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:55:59.2231182Z   import pynvml  # type: ignore[import]
2025-09-07T09:56:01.2430656Z 
2025-09-07T09:56:01.4612785Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:56:01.4613228Z   what():  std::bad_array_new_length
2025-09-07T09:57:44.4598247Z Run failed with return code:  -6
2025-09-07T09:57:44.4598511Z Output:  None
2025-09-07T09:57:44.4598666Z Error:  None
2025-09-07T09:57:44.8685928Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:57:44.8686812Z   import pynvml  # type: ignore[import]
2025-09-07T09:57:46.8836572Z 
2025-09-07T09:57:47.1014439Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:57:47.1014828Z   what():  std::bad_array_new_length
2025-09-07T09:59:30.4573871Z Run failed with return code:  -6
2025-09-07T09:59:30.4574124Z Output:  None
2025-09-07T09:59:30.4574870Z Error:  None
2025-09-07T09:59:30.8658956Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T09:59:30.8659864Z   import pynvml  # type: ignore[import]
2025-09-07T09:59:32.8817278Z 
2025-09-07T09:59:33.0992916Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T09:59:33.0993313Z   what():  std::bad_array_new_length
2025-09-07T10:01:16.4563156Z Run failed with return code:  -6
2025-09-07T10:01:16.4563440Z Output:  None
2025-09-07T10:01:16.4563587Z Error:  None
2025-09-07T10:01:16.8700554Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:01:16.8701650Z   import pynvml  # type: ignore[import]
2025-09-07T10:01:18.8865364Z 
2025-09-07T10:01:19.1043556Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:01:19.1043952Z   what():  std::bad_array_new_length
2025-09-07T10:03:02.6561589Z Run failed with return code:  -6
2025-09-07T10:03:02.6561860Z Output:  None
2025-09-07T10:03:02.6562010Z Error:  None
2025-09-07T10:03:03.0674124Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:03:03.0675122Z   import pynvml  # type: ignore[import]
2025-09-07T10:03:05.0884750Z 
2025-09-07T10:03:05.3069668Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:03:05.3070112Z   what():  std::bad_array_new_length
2025-09-07T10:04:49.1065078Z Run failed with return code:  -6
2025-09-07T10:04:49.1067239Z Output:  None
2025-09-07T10:04:49.1067417Z Error:  None
2025-09-07T10:04:49.5165160Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:04:49.5166011Z   import pynvml  # type: ignore[import]
2025-09-07T10:04:51.5393402Z 
2025-09-07T10:04:51.7588041Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:04:51.7588521Z   what():  std::bad_array_new_length
2025-09-07T10:06:35.0048433Z Run failed with return code:  -6
2025-09-07T10:06:35.0048700Z Output:  None
2025-09-07T10:06:35.0048901Z Error:  None
2025-09-07T10:06:35.4180502Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:06:35.4181453Z   import pynvml  # type: ignore[import]
2025-09-07T10:06:37.4415703Z 
2025-09-07T10:06:37.6595550Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:06:37.6595953Z   what():  std::bad_array_new_length
2025-09-07T10:08:20.8039096Z Run failed with return code:  -6
2025-09-07T10:08:20.8039357Z Output:  None
2025-09-07T10:08:20.8039503Z Error:  None
2025-09-07T10:08:21.2117643Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:08:21.2119224Z   import pynvml  # type: ignore[import]
2025-09-07T10:08:23.2421999Z 
2025-09-07T10:08:23.4633972Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:08:23.4634384Z   what():  std::bad_array_new_length
2025-09-07T10:10:06.5527262Z Run failed with return code:  -6
2025-09-07T10:10:06.5527513Z Output:  None
2025-09-07T10:10:06.5527661Z Error:  None
2025-09-07T10:10:06.9666552Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:10:06.9667441Z   import pynvml  # type: ignore[import]
2025-09-07T10:10:08.9920462Z 
2025-09-07T10:10:09.2111313Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:10:09.2111760Z   what():  std::bad_array_new_length
2025-09-07T10:11:52.1524093Z Run failed with return code:  -6
2025-09-07T10:11:52.1524375Z Output:  None
2025-09-07T10:11:52.1524524Z Error:  None
2025-09-07T10:11:52.1563840Z speedup             gmean=1.22x mean=1.254x
2025-09-07T10:11:52.1566129Z abs_latency         gmean=41.38x mean=77.942x
2025-09-07T10:11:52.1566370Z compilation_latency mean=22.740 seconds
2025-09-07T10:11:52.1566582Z compression_ratio   mean=0.923x
2025-09-07T10:11:52.1569473Z eager_peak_mem      gmean=149.09x mean=195.391x
2025-09-07T10:11:52.1571724Z dynamo_peak_mem     gmean=161.68x mean=208.134x
2025-09-07T10:11:52.1573856Z calls_captured      gmean=87.14x mean=160.250x
2025-09-07T10:11:52.1575963Z unique_graphs       gmean=1.27x mean=1.583x
2025-09-07T10:11:52.1578052Z graph_breaks        gmean=0.00x mean=0.750x
2025-09-07T10:11:52.1580180Z unique_graph_breaks gmean=0.00x mean=0.167x
2025-09-07T10:11:52.1582417Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T10:11:52.1584354Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T10:11:52.1586426Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T10:11:52.7290655Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *cudagraphs-true* ]]
2025-09-07T10:11:52.7291449Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *dynamic-true* ]]
2025-09-07T10:11:52.7292714Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --dynamic-shapes --dynamic-batch-only --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv
2025-09-07T10:11:53.1248043Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:11:53.1248946Z   import pynvml  # type: ignore[import]
2025-09-07T10:11:55.5751880Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:11:55.5752765Z   import pynvml  # type: ignore[import]
2025-09-07T10:11:57.5899117Z 
2025-09-07T10:11:59.2226407Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:11:59.2226793Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:11:59.2416059Z cpu  eval  BERT_pytorch                       
2025-09-07T10:12:09.8221999Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8222444Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8223289Z     return mod(*inputs)
2025-09-07T10:12:09.8223652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8224050Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8224410Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 44, in forward
2025-09-07T10:12:09.8224812Z     mask = (x > 0).unsqueeze(1).repeat(1, x.size(1), 1).unsqueeze(1)
2025-09-07T10:12:09.8225000Z 
2025-09-07T10:12:09.8225123Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8225495Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8225896Z     return mod(*inputs)
2025-09-07T10:12:09.8226262Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8226648Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8226993Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 47, in forward
2025-09-07T10:12:09.8227357Z     x = self.embedding(x, segment_info)
2025-09-07T10:12:09.8227733Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/embedding/bert.py", line 32, in forward
2025-09-07T10:12:09.8228360Z     x = self.token(sequence) + self.position(sequence) + self.segment(segment_label)
2025-09-07T10:12:09.8228586Z 
2025-09-07T10:12:09.8228780Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8229154Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8229495Z     return mod(*inputs)
2025-09-07T10:12:09.8229849Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8230240Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8230588Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8230953Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8231315Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8231705Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8232098Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8232512Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8232959Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8233375Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8233822Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8234215Z     query, key, value = [
2025-09-07T10:12:09.8234594Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8235049Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8235224Z 
2025-09-07T10:12:09.8235328Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8235700Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8236043Z     return mod(*inputs)
2025-09-07T10:12:09.8236377Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8236750Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8237086Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8237437Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8237819Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8238295Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8238683Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8239097Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8239535Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8239934Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8240359Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8240756Z     query, key, value = [
2025-09-07T10:12:09.8241145Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8241588Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8241762Z 
2025-09-07T10:12:09.8241866Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8242236Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8242567Z     return mod(*inputs)
2025-09-07T10:12:09.8243135Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8243529Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8243866Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8244225Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8244591Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8244989Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8245377Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8245794Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8246196Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8246600Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8247034Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8247478Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8247908Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8248403Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8248617Z 
2025-09-07T10:12:09.8248727Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8249104Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8249433Z     return mod(*inputs)
2025-09-07T10:12:09.8249780Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8250150Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8250503Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8250853Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8251211Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8251599Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8251994Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8252399Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8253002Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8253407Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8253833Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8254284Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8254741Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8255195Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8255416Z 
2025-09-07T10:12:09.8255520Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8255891Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8256219Z     return mod(*inputs)
2025-09-07T10:12:09.8256560Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8256925Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8257281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8257632Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8258063Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8258445Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8258831Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8259241Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8259638Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8260048Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8260465Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8260905Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8261344Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8261805Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8262019Z 
2025-09-07T10:12:09.8262125Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8262485Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8262809Z     return mod(*inputs)
2025-09-07T10:12:09.8263143Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8263519Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8263853Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8264200Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8264564Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8264949Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8265331Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8265776Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8266168Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8266561Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8266985Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8267449Z     query, key, value = [
2025-09-07T10:12:09.8267824Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8268269Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8268444Z 
2025-09-07T10:12:09.8268551Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8268914Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8269265Z     return mod(*inputs)
2025-09-07T10:12:09.8269604Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8269972Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8270318Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8270668Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8271019Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8271397Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8271781Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8272281Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8272704Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8284059Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8284582Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8285067Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8285522Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8285937Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8286092Z 
2025-09-07T10:12:09.8286199Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8286577Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8286917Z     return mod(*inputs)
2025-09-07T10:12:09.8287266Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8287640Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8287985Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8288342Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8288705Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8289083Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8289475Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8289894Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8290297Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8290700Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8291118Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8291564Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8291999Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8292393Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8292534Z 
2025-09-07T10:12:09.8292750Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8293115Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8293443Z     return mod(*inputs)
2025-09-07T10:12:09.8293786Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8294163Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8294494Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8294845Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8295201Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8295583Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8295968Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8296368Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8296763Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8297159Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8299181Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8299659Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8299858Z 
2025-09-07T10:12:09.8299961Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8300330Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8300665Z     return mod(*inputs)
2025-09-07T10:12:09.8301007Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8301375Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8301717Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8302063Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8302423Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8302809Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8303188Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8303596Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8303991Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8304391Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8304814Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8305198Z     return self.output_linear(x)
2025-09-07T10:12:09.8305326Z 
2025-09-07T10:12:09.8305425Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8305843Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8306173Z     return mod(*inputs)
2025-09-07T10:12:09.8306505Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8306873Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8307208Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8307557Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8307909Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8308280Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8308821Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8309227Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8309644Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8310064Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8310249Z 
2025-09-07T10:12:09.8310344Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8310698Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8311022Z     return mod(*inputs)
2025-09-07T10:12:09.8311357Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8311718Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8312051Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8312395Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8312750Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8313122Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8313598Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8314019Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8314438Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8314867Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8315040Z 
2025-09-07T10:12:09.8315142Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8315501Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8315834Z     return mod(*inputs)
2025-09-07T10:12:09.8316173Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8316541Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8316874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8317222Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8317577Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8317955Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8318330Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8318735Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8319145Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8319572Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8319739Z 
2025-09-07T10:12:09.8319845Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8320198Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8320525Z     return mod(*inputs)
2025-09-07T10:12:09.8320860Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8321229Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8321559Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8321897Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8322249Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8322723Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8323105Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8323499Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8323893Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8324289Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8324711Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8325091Z     query, key, value = [
2025-09-07T10:12:09.8329149Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8329605Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8329777Z 
2025-09-07T10:12:09.8329893Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8330259Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8330584Z     return mod(*inputs)
2025-09-07T10:12:09.8330924Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8331388Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8331731Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8332076Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8332435Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8332859Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8333237Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8333651Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8334048Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8334459Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8334894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8335278Z     query, key, value = [
2025-09-07T10:12:09.8335649Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8336084Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8336249Z 
2025-09-07T10:12:09.8336356Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8336719Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8337046Z     return mod(*inputs)
2025-09-07T10:12:09.8337387Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8337756Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8338089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8338432Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8338790Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8339168Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8339556Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8339965Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8340359Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8340808Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8341230Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8341680Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8342112Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8342572Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8342793Z 
2025-09-07T10:12:09.8342896Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8343253Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8343665Z     return mod(*inputs)
2025-09-07T10:12:09.8343996Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8344368Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8344702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8345052Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8345476Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8345921Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8346322Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8346729Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8347117Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8347509Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8347927Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8348365Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8348794Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8349252Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8349461Z 
2025-09-07T10:12:09.8349571Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8349933Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8350256Z     return mod(*inputs)
2025-09-07T10:12:09.8350591Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8350953Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8351290Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8351639Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8351993Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8352366Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8352740Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8353148Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8353537Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8353927Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8354333Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8354774Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8355244Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8355700Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8355909Z 
2025-09-07T10:12:09.8356015Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8356367Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8356690Z     return mod(*inputs)
2025-09-07T10:12:09.8357022Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8357385Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8357768Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8358113Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8358460Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8358824Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8359196Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8359591Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8360044Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8360446Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8360854Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8361228Z     query, key, value = [
2025-09-07T10:12:09.8361583Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8362017Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8362180Z 
2025-09-07T10:12:09.8362273Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8362619Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8362931Z     return mod(*inputs)
2025-09-07T10:12:09.8363259Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8363618Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8363935Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8364264Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8364602Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8364962Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8365339Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8365739Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8366133Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8366537Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8366970Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8367408Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8367852Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8368239Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8368385Z 
2025-09-07T10:12:09.8368483Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8368874Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8369248Z     return mod(*inputs)
2025-09-07T10:12:09.8369582Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8369943Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8370275Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8370623Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8371012Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8371407Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8371829Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8372252Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8372663Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8373055Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8373464Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8373999Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8374433Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8374819Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8374953Z 
2025-09-07T10:12:09.8375079Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8375436Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8375782Z     return mod(*inputs)
2025-09-07T10:12:09.8376109Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8376473Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8376796Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8377147Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8377515Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8377891Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8378260Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8378653Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8379053Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8379437Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8379847Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8380287Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8380477Z 
2025-09-07T10:12:09.8380573Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8380930Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8381255Z     return mod(*inputs)
2025-09-07T10:12:09.8381588Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8381947Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8382273Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8382602Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8382942Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8383350Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8383722Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8384139Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8384525Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8384919Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8385331Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8385807Z     return self.output_linear(x)
2025-09-07T10:12:09.8385930Z 
2025-09-07T10:12:09.8386029Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8386375Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8386700Z     return mod(*inputs)
2025-09-07T10:12:09.8387035Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8387390Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8387779Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8388131Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8388475Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8388838Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8389208Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8389611Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8390013Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8390432Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8390610Z 
2025-09-07T10:12:09.8390707Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8391064Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8391375Z     return mod(*inputs)
2025-09-07T10:12:09.8391696Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8392057Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8392384Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8392722Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8393071Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8393456Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8393819Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8394217Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8394624Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8395035Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8395207Z 
2025-09-07T10:12:09.8395308Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8395652Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8395972Z     return mod(*inputs)
2025-09-07T10:12:09.8396300Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8396662Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8397019Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8397349Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8397693Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8398069Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8398432Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8398985Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8399381Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8399877Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8400058Z 
2025-09-07T10:12:09.8400167Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8400527Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8400841Z     return mod(*inputs)
2025-09-07T10:12:09.8401173Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8401536Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8401964Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8402303Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8402667Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8403027Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8403424Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8403811Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8403968Z 
2025-09-07T10:12:09.8404062Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8404428Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8404743Z     return mod(*inputs)
2025-09-07T10:12:09.8405077Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8405447Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8405769Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8406101Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8406449Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8406814Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8407189Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8407585Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8407971Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8408368Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8408790Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8409167Z     query, key, value = [
2025-09-07T10:12:09.8409530Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8409959Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8410130Z 
2025-09-07T10:12:09.8410243Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8410613Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8411003Z     return mod(*inputs)
2025-09-07T10:12:09.8411345Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8411718Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8412069Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8412412Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8412767Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8413163Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8413544Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8413989Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8414373Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8414788Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8415207Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8415580Z     query, key, value = [
2025-09-07T10:12:09.8415998Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8416429Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8416591Z 
2025-09-07T10:12:09.8416689Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8417048Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8417374Z     return mod(*inputs)
2025-09-07T10:12:09.8417702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8418067Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8418410Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8418754Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8419107Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8419486Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8419870Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8420274Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8420665Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8421056Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8421472Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8421916Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8422343Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8422802Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8423014Z 
2025-09-07T10:12:09.8423114Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8423472Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8423792Z     return mod(*inputs)
2025-09-07T10:12:09.8424125Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8424486Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8424820Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8425209Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8425617Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8425998Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8426379Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8426782Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8427175Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8427568Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8428046Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8428478Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8428907Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8429362Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8429573Z 
2025-09-07T10:12:09.8429679Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8430118Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8430441Z     return mod(*inputs)
2025-09-07T10:12:09.8430777Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8431147Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8431478Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8431816Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8432169Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8432548Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8432927Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8433334Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8433720Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8434124Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8434564Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8435117Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8435546Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8435998Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8436216Z 
2025-09-07T10:12:09.8436316Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8436675Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8437000Z     return mod(*inputs)
2025-09-07T10:12:09.8437337Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8437697Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8438027Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8438383Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8438743Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8439115Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8439542Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8439963Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8440355Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8440751Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8441159Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8441538Z     query, key, value = [
2025-09-07T10:12:09.8441904Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8442407Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8442570Z 
2025-09-07T10:12:09.8442677Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8443026Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8443348Z     return mod(*inputs)
2025-09-07T10:12:09.8443683Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8444044Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8444438Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8444860Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8445265Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8445664Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8446046Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8446465Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8446860Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8447255Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8447723Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8448211Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8448644Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8449037Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8449176Z 
2025-09-07T10:12:09.8449289Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8449641Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8449967Z     return mod(*inputs)
2025-09-07T10:12:09.8450305Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8450671Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8450996Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8451342Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8451699Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8452076Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8452454Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8452848Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8453237Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8453630Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8454096Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8454530Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8454959Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8455345Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8455484Z 
2025-09-07T10:12:09.8455589Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8455943Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8456307Z     return mod(*inputs)
2025-09-07T10:12:09.8456641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8457007Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8457345Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8457692Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8458046Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8458488Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8458874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8459278Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8459711Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8460113Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8460557Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8461052Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8461239Z 
2025-09-07T10:12:09.8461348Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8461704Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8462024Z     return mod(*inputs)
2025-09-07T10:12:09.8462366Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8462734Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8463067Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8463410Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8463793Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8464202Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8464582Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8464987Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8465406Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8465891Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8466346Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8466733Z     return self.output_linear(x)
2025-09-07T10:12:09.8466852Z 
2025-09-07T10:12:09.8466964Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8467319Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8467645Z     return mod(*inputs)
2025-09-07T10:12:09.8467977Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8468393Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8468728Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8469064Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8469421Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8469793Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8470169Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8470604Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8471070Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8471531Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8471707Z 
2025-09-07T10:12:09.8471815Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8472175Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8472494Z     return mod(*inputs)
2025-09-07T10:12:09.8472951Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8473323Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8473650Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8474023Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8474376Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8474794Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8475183Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8475590Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8475998Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8476419Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8476600Z 
2025-09-07T10:12:09.8476700Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8477059Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8477386Z     return mod(*inputs)
2025-09-07T10:12:09.8477715Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8478082Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8478415Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8478759Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8479106Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8479479Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8479860Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8480264Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8480676Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8481091Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8481270Z 
2025-09-07T10:12:09.8481368Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8481720Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8482040Z     return mod(*inputs)
2025-09-07T10:12:09.8482460Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8482830Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8483160Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8483513Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8483869Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8484237Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8484625Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8485493Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8485901Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8486304Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8486715Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8487103Z     query, key, value = [
2025-09-07T10:12:09.8487534Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8487973Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8488133Z 
2025-09-07T10:12:09.8488242Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8488591Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8488928Z     return mod(*inputs)
2025-09-07T10:12:09.8489278Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8489655Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8489986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8490332Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8490687Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8491068Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8491447Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8491844Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8492236Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8492631Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8493050Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8493428Z     query, key, value = [
2025-09-07T10:12:09.8493797Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8494227Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8494389Z 
2025-09-07T10:12:09.8494496Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8494852Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8495170Z     return mod(*inputs)
2025-09-07T10:12:09.8495502Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8495886Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8496224Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8496570Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8496917Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8497360Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8497751Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8498155Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8498544Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8499054Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8499471Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8500011Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8500444Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8500902Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8501124Z 
2025-09-07T10:12:09.8501221Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8501585Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8502013Z     return mod(*inputs)
2025-09-07T10:12:09.8502350Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8502708Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8503041Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8503390Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8503748Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8504115Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8504500Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8504903Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8505294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8505755Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8506166Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8506606Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8507034Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8507491Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8507701Z 
2025-09-07T10:12:09.8507805Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8508159Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8508481Z     return mod(*inputs)
2025-09-07T10:12:09.8508815Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8509182Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8509505Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8509847Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8510200Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8510576Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8510950Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8511407Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8511799Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8512191Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8512612Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8513055Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8513475Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8513927Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8514189Z 
2025-09-07T10:12:09.8514290Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8514651Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8514981Z     return mod(*inputs)
2025-09-07T10:12:09.8515312Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8515684Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8516086Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8516436Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8516788Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8517163Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8517547Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8517954Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8518342Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8518732Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8519144Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8519529Z     query, key, value = [
2025-09-07T10:12:09.8519898Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8520323Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8520492Z 
2025-09-07T10:12:09.8520594Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8520949Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8521278Z     return mod(*inputs)
2025-09-07T10:12:09.8521611Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8521971Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8522299Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8522640Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8522992Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8523359Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8523744Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8524155Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8524547Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8524939Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8525346Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8525838Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8526267Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8526659Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8526799Z 
2025-09-07T10:12:09.8526908Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8527258Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8527579Z     return mod(*inputs)
2025-09-07T10:12:09.8527911Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8528338Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8528664Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8529009Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8529365Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8529741Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8530199Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8530605Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8530995Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8531387Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8531806Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8532245Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8532665Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8533051Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8533195Z 
2025-09-07T10:12:09.8533294Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8533654Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8533976Z     return mod(*inputs)
2025-09-07T10:12:09.8534302Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8534665Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8534993Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8535336Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8535682Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8536056Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8536433Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8536840Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8537232Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8537617Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8538030Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8538475Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8538667Z 
2025-09-07T10:12:09.8538770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8539126Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8539504Z     return mod(*inputs)
2025-09-07T10:12:09.8539839Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8540204Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8540535Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8540868Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8541224Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8541591Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8541965Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8542429Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8542814Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8543208Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8543624Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8544006Z     return self.output_linear(x)
2025-09-07T10:12:09.8544184Z 
2025-09-07T10:12:09.8544288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8544648Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8544972Z     return mod(*inputs)
2025-09-07T10:12:09.8545305Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8545723Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8546046Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8546392Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8546747Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8547119Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8547493Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8547891Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8548303Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8548723Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8548893Z 
2025-09-07T10:12:09.8549000Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8549349Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8549667Z     return mod(*inputs)
2025-09-07T10:12:09.8550001Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8550367Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8550696Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8551033Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8551385Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8551757Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8552136Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8552529Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8552934Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8553412Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8553579Z 
2025-09-07T10:12:09.8553771Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8554203Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8554775Z     return mod(*inputs)
2025-09-07T10:12:09.8555190Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8555605Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8556078Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8556507Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8557037Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8557549Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8557983Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8558470Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8559017Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8559600Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8559803Z 
2025-09-07T10:12:09.8559992Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8560415Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8560839Z     return mod(*inputs)
2025-09-07T10:12:09.8561281Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8561761Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8562216Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8562643Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8563107Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8563572Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8572378Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8572816Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8572992Z 
2025-09-07T10:12:09.8573096Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8573463Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8573792Z     return mod(*inputs)
2025-09-07T10:12:09.8574129Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8574508Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8574843Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8575196Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8575552Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8575937Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8576315Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8576721Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8577111Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8577504Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8577924Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8578383Z     query, key, value = [
2025-09-07T10:12:09.8578757Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8579192Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8579360Z 
2025-09-07T10:12:09.8579465Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8579825Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8580149Z     return mod(*inputs)
2025-09-07T10:12:09.8580492Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8580932Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8581265Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8581625Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8581985Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8582363Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8582749Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8583226Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8583619Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8584015Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8584431Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8584809Z     query, key, value = [
2025-09-07T10:12:09.8585180Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8585675Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8585840Z 
2025-09-07T10:12:09.8585947Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8586299Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8586618Z     return mod(*inputs)
2025-09-07T10:12:09.8586956Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8587317Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8587648Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8587991Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8588345Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8588729Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8589115Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8589522Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8589905Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8590297Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8590718Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8591164Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8591592Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8592051Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8592270Z 
2025-09-07T10:12:09.8592417Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8592775Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8593100Z     return mod(*inputs)
2025-09-07T10:12:09.8593435Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8593807Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8594138Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8594488Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8594839Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8595255Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8595631Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8596037Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8596424Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8596820Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8597311Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8597758Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8598183Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8598639Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8599003Z 
2025-09-07T10:12:09.8599106Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8599454Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8599779Z     return mod(*inputs)
2025-09-07T10:12:09.8600108Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8600470Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8600796Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8601138Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8601495Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8601870Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8602248Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8602649Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8603034Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8603431Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8603851Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8604291Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8604716Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8605166Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8605375Z 
2025-09-07T10:12:09.8605477Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8605832Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8606145Z     return mod(*inputs)
2025-09-07T10:12:09.8606474Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8606940Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8607271Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8607611Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8607961Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8608333Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8608714Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8609111Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8609567Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8609961Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8610391Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8610770Z     query, key, value = [
2025-09-07T10:12:09.8611138Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8611672Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8611840Z 
2025-09-07T10:12:09.8611940Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8612297Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8612615Z     return mod(*inputs)
2025-09-07T10:12:09.8612955Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8613316Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8613648Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8613988Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8614342Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8614711Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8615096Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8615493Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8615880Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8616272Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8616686Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8617137Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8617578Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8617967Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8618107Z 
2025-09-07T10:12:09.8618208Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8618558Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8618873Z     return mod(*inputs)
2025-09-07T10:12:09.8619206Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8619567Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8619890Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8620231Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8620583Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8621005Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8621378Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8621767Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8622160Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8622552Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8622973Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8623456Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8623874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8624264Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8624405Z 
2025-09-07T10:12:09.8624502Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8624856Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8625199Z     return mod(*inputs)
2025-09-07T10:12:09.8625654Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8626028Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8626355Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8626696Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8627053Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8627427Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8627796Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8628199Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8628588Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8628983Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8629398Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8629834Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8630027Z 
2025-09-07T10:12:09.8630127Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8630484Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8630804Z     return mod(*inputs)
2025-09-07T10:12:09.8631133Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8631492Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8631815Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8632157Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8632508Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8632880Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8633260Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8633659Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8634049Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8634436Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8634889Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8635272Z     return self.output_linear(x)
2025-09-07T10:12:09.8635391Z 
2025-09-07T10:12:09.8635487Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8635687Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8635750Z     return mod(*inputs)
2025-09-07T10:12:09.8635981Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8636050Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8636254Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8636359Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8636585Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8636671Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8636909Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8637010Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8637319Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8637430Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8637434Z 
2025-09-07T10:12:09.8637528Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8637724Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8637782Z     return mod(*inputs)
2025-09-07T10:12:09.8638019Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8638083Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8638290Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8638359Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8638583Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8638671Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8638902Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8639005Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8639267Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8639386Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8639389Z 
2025-09-07T10:12:09.8639491Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8639687Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8639750Z     return mod(*inputs)
2025-09-07T10:12:09.8639978Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8640046Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8640257Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8640325Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8640549Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8640632Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8640860Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8640968Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8641250Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8641369Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8641372Z 
2025-09-07T10:12:09.8641475Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8641676Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8641734Z     return mod(*inputs)
2025-09-07T10:12:09.8641965Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8642035Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8642294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8642367Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8642589Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8642675Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8642907Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8643068Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8643297Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8643396Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8643652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8643718Z     query, key, value = [
2025-09-07T10:12:09.8643978Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8644084Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8644090Z 
2025-09-07T10:12:09.8644188Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8644388Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8644447Z     return mod(*inputs)
2025-09-07T10:12:09.8644677Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8644743Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8644949Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8645022Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8645248Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8645329Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8645562Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8645659Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8645934Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8646035Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8646291Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8646350Z     query, key, value = [
2025-09-07T10:12:09.8646607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8646711Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8646714Z 
2025-09-07T10:12:09.8646810Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8647007Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8647110Z     return mod(*inputs)
2025-09-07T10:12:09.8647341Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8647408Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8647614Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8647685Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8647906Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8647985Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8648258Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8648359Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8648589Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8648690Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8648939Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8649125Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8649368Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8649518Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8649521Z 
2025-09-07T10:12:09.8649619Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8649819Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8649877Z     return mod(*inputs)
2025-09-07T10:12:09.8650107Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8650171Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8650374Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8650446Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8650670Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8650756Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8650983Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8651082Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8651306Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8651406Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8651661Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8651781Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8652026Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8652176Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8652179Z 
2025-09-07T10:12:09.8652273Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8652471Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8652527Z     return mod(*inputs)
2025-09-07T10:12:09.8652763Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8652826Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8653520Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8653594Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8653817Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8653908Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8654139Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8654239Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8654466Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8654603Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8654853Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8654977Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8655218Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8655366Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8655430Z 
2025-09-07T10:12:09.8655529Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8655727Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8655787Z     return mod(*inputs)
2025-09-07T10:12:09.8656021Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8656086Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8656290Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8656362Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8656583Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8656670Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8656903Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8657000Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8657224Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8657325Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8657576Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8657637Z     query, key, value = [
2025-09-07T10:12:09.8657899Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8658002Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8658005Z 
2025-09-07T10:12:09.8658099Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8658298Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8658359Z     return mod(*inputs)
2025-09-07T10:12:09.8658593Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8658658Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8658860Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8658930Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8659165Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8659249Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8659518Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8659625Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8659851Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8659950Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8660200Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8660323Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8660603Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8660683Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8660686Z 
2025-09-07T10:12:09.8660783Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8660982Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8661039Z     return mod(*inputs)
2025-09-07T10:12:09.8661275Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8661398Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8661611Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8661677Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8661899Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8661985Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8662213Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8662314Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8662535Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8662633Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8662890Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8663008Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8663251Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8663328Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8663333Z 
2025-09-07T10:12:09.8663556Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8663749Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8663810Z     return mod(*inputs)
2025-09-07T10:12:09.8664048Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8664111Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8664322Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8664389Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8664607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8664692Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8664919Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8665020Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8665241Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8665397Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8665706Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8665836Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8665843Z 
2025-09-07T10:12:09.8665943Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8666133Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8666193Z     return mod(*inputs)
2025-09-07T10:12:09.8666423Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8666528Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8666735Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8666802Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8667029Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8667107Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8667405Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8667507Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8667730Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8667832Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8668085Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8668158Z     return self.output_linear(x)
2025-09-07T10:12:09.8668161Z 
2025-09-07T10:12:09.8668255Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8668453Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8668512Z     return mod(*inputs)
2025-09-07T10:12:09.8668741Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8668812Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8669015Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8669083Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8669328Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8669433Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8669668Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8669769Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8670015Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8670126Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8670129Z 
2025-09-07T10:12:09.8670222Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8670424Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8670482Z     return mod(*inputs)
2025-09-07T10:12:09.8670718Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8670782Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8670986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8671057Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8671280Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8671398Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8671630Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8671728Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8671976Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8672085Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8672088Z 
2025-09-07T10:12:09.8672184Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8672413Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8672477Z     return mod(*inputs)
2025-09-07T10:12:09.8672707Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8672773Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8672986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8673051Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8673396Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8673476Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8673705Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8673806Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8674049Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8674160Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8674165Z 
2025-09-07T10:12:09.8674258Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8674452Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8674509Z     return mod(*inputs)
2025-09-07T10:12:09.8674741Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8674807Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8675011Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8675079Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8675299Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8675380Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8675611Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8675711Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8675714Z 
2025-09-07T10:12:09.8675811Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8676004Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8676064Z     return mod(*inputs)
2025-09-07T10:12:09.8676297Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8676359Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8676565Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8676632Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8676856Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8676936Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8677202Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8677303Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8677519Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8677631Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8677880Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8677938Z     query, key, value = [
2025-09-07T10:12:09.8678200Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8678334Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8678337Z 
2025-09-07T10:12:09.8678431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8678630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8678688Z     return mod(*inputs)
2025-09-07T10:12:09.8678922Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8678985Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8679250Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8679316Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8679543Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8679623Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8679856Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8679958Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8680183Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8680288Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8680536Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8680600Z     query, key, value = [
2025-09-07T10:12:09.8680864Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8680963Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8680967Z 
2025-09-07T10:12:09.8681065Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8681261Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8681323Z     return mod(*inputs)
2025-09-07T10:12:09.8681553Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8681620Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8681833Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8681896Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8682124Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8682204Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8682433Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8682537Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8682756Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8682858Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8683146Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8683268Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8683515Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8683663Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8683667Z 
2025-09-07T10:12:09.8683767Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8683961Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8684057Z     return mod(*inputs)
2025-09-07T10:12:09.8684289Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8684356Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8684564Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8684631Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8684855Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8685026Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8685261Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8685369Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8685594Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8685698Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8685946Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8686071Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8686312Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8686458Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8686463Z 
2025-09-07T10:12:09.8686562Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8686751Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8686812Z     return mod(*inputs)
2025-09-07T10:12:09.8687042Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8687106Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8687314Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8687381Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8687612Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8687690Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8687925Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8688023Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8688245Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8688348Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8688596Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8688722Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8688957Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8689134Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8689137Z 
2025-09-07T10:12:09.8689239Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8689435Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8689497Z     return mod(*inputs)
2025-09-07T10:12:09.8689729Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8689798Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8690005Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8690108Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8690338Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8690424Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8690658Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8690759Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8691043Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8691153Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8691400Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8691463Z     query, key, value = [
2025-09-07T10:12:09.8691730Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8691838Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8691847Z 
2025-09-07T10:12:09.8691945Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8692141Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8692203Z     return mod(*inputs)
2025-09-07T10:12:09.8692434Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8692501Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8692706Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8692771Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8693000Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8693082Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8693312Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8693411Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8693632Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8693737Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8693988Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8694113Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8694350Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8694434Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8694437Z 
2025-09-07T10:12:09.8694530Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8694724Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8694825Z     return mod(*inputs)
2025-09-07T10:12:09.8695055Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8695120Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8695325Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8695390Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8695623Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8695702Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8695935Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8696070Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8696292Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8696396Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8696641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8696762Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8697064Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8697147Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8697150Z 
2025-09-07T10:12:09.8697242Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8697440Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8697505Z     return mod(*inputs)
2025-09-07T10:12:09.8697734Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8697804Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8698005Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8698071Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8698297Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8698376Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8698610Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8698708Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8699089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8699198Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8699452Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8699588Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8699592Z 
2025-09-07T10:12:09.8699692Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8699898Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8699960Z     return mod(*inputs)
2025-09-07T10:12:09.8700210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8700280Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8700491Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8700568Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8700796Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8700940Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8701180Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8701286Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8701520Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8701623Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8701879Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8701946Z     return self.output_linear(x)
2025-09-07T10:12:09.8701996Z 
2025-09-07T10:12:09.8702095Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8702297Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8702356Z     return mod(*inputs)
2025-09-07T10:12:09.8702593Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8702657Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8702862Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8703025Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8703256Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8703347Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8703580Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8703687Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8703937Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8704047Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8704050Z 
2025-09-07T10:12:09.8704153Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8704355Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8704421Z     return mod(*inputs)
2025-09-07T10:12:09.8704657Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8704723Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8704935Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8705006Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8705233Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8705314Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8705546Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8705683Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8705928Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8706042Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8706045Z 
2025-09-07T10:12:09.8706139Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8706337Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8706394Z     return mod(*inputs)
2025-09-07T10:12:09.8706625Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8706691Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8706897Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8707005Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8707226Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8707307Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8707540Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8707638Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8707886Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8708033Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8708036Z 
2025-09-07T10:12:09.8708131Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8708326Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8708384Z     return mod(*inputs)
2025-09-07T10:12:09.8708618Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8708680Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8708963Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8709034Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8709262Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8709345Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8709579Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8709687Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8709910Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8710015Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8710270Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8710331Z     query, key, value = [
2025-09-07T10:12:09.8710599Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8710705Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8710709Z 
2025-09-07T10:12:09.8710813Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8711011Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8711067Z     return mod(*inputs)
2025-09-07T10:12:09.8711304Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8711372Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8711600Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8711668Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8711894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8711979Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8712209Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8712314Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8712536Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8712637Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8712889Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8712991Z     query, key, value = [
2025-09-07T10:12:09.8713255Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8713354Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8713357Z 
2025-09-07T10:12:09.8713454Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8713654Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8713712Z     return mod(*inputs)
2025-09-07T10:12:09.8713947Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8714048Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8714259Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8714329Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8714551Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8714636Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8714924Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8715029Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8715252Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8715352Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8715607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8715730Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8715977Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8716128Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8716131Z 
2025-09-07T10:12:09.8716230Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8716429Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8716487Z     return mod(*inputs)
2025-09-07T10:12:09.8716721Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8716784Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8716996Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8717063Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8717285Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8717374Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8717610Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8717713Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8717938Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8718045Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8718295Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8718418Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8718664Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8718808Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8718848Z 
2025-09-07T10:12:09.8718950Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8719148Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8719206Z     return mod(*inputs)
2025-09-07T10:12:09.8719448Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8719513Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8719725Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8719794Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8720062Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8720142Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8720371Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8720477Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8720698Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8720863Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8721114Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8721236Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8721479Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8721625Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8721628Z 
2025-09-07T10:12:09.8721727Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8721924Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8721985Z     return mod(*inputs)
2025-09-07T10:12:09.8722216Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8722281Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8722492Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8722560Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8722789Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8722870Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8723100Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8723204Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8723428Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8723531Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8723784Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8723845Z     query, key, value = [
2025-09-07T10:12:09.8724110Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8724211Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8724213Z 
2025-09-07T10:12:09.8724313Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8724508Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8724572Z     return mod(*inputs)
2025-09-07T10:12:09.8724861Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8724924Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8725140Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8725208Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8725434Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8725513Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8725740Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8725879Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8726104Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8726209Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8726458Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8726577Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8727058Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8727140Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8727143Z 
2025-09-07T10:12:09.8727243Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8727442Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8727506Z     return mod(*inputs)
2025-09-07T10:12:09.8727739Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8727803Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8728015Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8728081Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8728307Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8728388Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8728617Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8728720Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8728955Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8729064Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8729317Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8729447Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8729686Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8729762Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8729765Z 
2025-09-07T10:12:09.8729870Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8730065Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8730131Z     return mod(*inputs)
2025-09-07T10:12:09.8730361Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8730428Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8730637Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8730704Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8730974Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8731057Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8731289Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8731399Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8731626Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8731732Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8731980Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8732172Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8732175Z 
2025-09-07T10:12:09.8732274Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8732474Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8732539Z     return mod(*inputs)
2025-09-07T10:12:09.8732773Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8732906Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8733114Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8733184Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8733412Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8733495Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8733734Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8733832Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8734061Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8734161Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8734415Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8734491Z     return self.output_linear(x)
2025-09-07T10:12:09.8734494Z 
2025-09-07T10:12:09.8734593Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8734792Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8734854Z     return mod(*inputs)
2025-09-07T10:12:09.8735086Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8735155Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8735358Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8735434Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8735659Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8735739Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8735983Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8736083Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8736330Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8736441Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8736444Z 
2025-09-07T10:12:09.8736557Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8736754Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8736852Z     return mod(*inputs)
2025-09-07T10:12:09.8737089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8737152Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8737364Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8737433Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8737659Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8737745Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8738013Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8738119Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8738361Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8738475Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8738478Z 
2025-09-07T10:12:09.8738576Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8738829Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8738897Z     return mod(*inputs)
2025-09-07T10:12:09.8739127Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8739196Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8739400Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8739470Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8739698Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8739779Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8740017Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8740116Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8740363Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8740474Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8740477Z 
2025-09-07T10:12:09.8740573Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8740773Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8740831Z     return mod(*inputs)
2025-09-07T10:12:09.8741069Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8741135Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8741341Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8741415Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8741641Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8741727Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8741955Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8742053Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8742056Z 
2025-09-07T10:12:09.8742156Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8742349Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8742410Z     return mod(*inputs)
2025-09-07T10:12:09.8742636Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8742740Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8742951Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8743018Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8743249Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8743329Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8743564Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8743662Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8743920Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8744024Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8744276Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8744343Z     query, key, value = [
2025-09-07T10:12:09.8744600Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8744760Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8744764Z 
2025-09-07T10:12:09.8744864Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8745059Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8745119Z     return mod(*inputs)
2025-09-07T10:12:09.8745352Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8745420Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8745664Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8745734Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8745963Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8746044Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8746283Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8746383Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8746607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8746716Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8746966Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8747033Z     query, key, value = [
2025-09-07T10:12:09.8747293Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8747393Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8747402Z 
2025-09-07T10:12:09.8747498Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8747695Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8747758Z     return mod(*inputs)
2025-09-07T10:12:09.8747986Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8748054Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8748258Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8748325Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8748549Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8748668Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8748903Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8749021Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8749249Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8749357Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8749607Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8749773Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8750013Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8750162Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8750172Z 
2025-09-07T10:12:09.8750268Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8750463Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8750526Z     return mod(*inputs)
2025-09-07T10:12:09.8750820Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8750891Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8751093Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8751160Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8751388Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8751467Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8751703Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8751802Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8752024Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8752129Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8752380Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8752507Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8752745Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8752896Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8752899Z 
2025-09-07T10:12:09.8752994Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8753191Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8753254Z     return mod(*inputs)
2025-09-07T10:12:09.8753482Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8753557Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8753765Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8753833Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8754060Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8754141Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8754377Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8754475Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8754755Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8754856Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8755104Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8755229Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8755467Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8755613Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8755649Z 
2025-09-07T10:12:09.8755744Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8755940Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8756007Z     return mod(*inputs)
2025-09-07T10:12:09.8756237Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8756309Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8756513Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8756645Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8756875Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8756956Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8757194Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8757295Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8757523Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8757626Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8757874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8757943Z     query, key, value = [
2025-09-07T10:12:09.8758202Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8758309Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8758312Z 
2025-09-07T10:12:09.8758409Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8758604Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8758670Z     return mod(*inputs)
2025-09-07T10:12:09.8758900Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8758970Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8759176Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8759247Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8759470Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8759553Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8759785Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8759881Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8760110Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8760210Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8760461Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8760626Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8760866Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8760951Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8760954Z 
2025-09-07T10:12:09.8761050Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8761249Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8761312Z     return mod(*inputs)
2025-09-07T10:12:09.8761542Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8761649Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8761853Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8761925Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8762152Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8762231Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8762471Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8762628Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8762858Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8762960Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8763210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8763337Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8763577Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8763662Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8763666Z 
2025-09-07T10:12:09.8763760Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8763961Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8764023Z     return mod(*inputs)
2025-09-07T10:12:09.8764252Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8764322Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8764527Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8764601Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8764823Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8764903Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8765135Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8765233Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8765465Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8765564Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8765812Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8765943Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8765948Z 
2025-09-07T10:12:09.8766042Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8766241Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8766337Z     return mod(*inputs)
2025-09-07T10:12:09.8766571Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8766634Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8766838Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8766916Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8767134Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8767217Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8767447Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8767585Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8767809Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8767912Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8768166Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8768233Z     return self.output_linear(x)
2025-09-07T10:12:09.8768239Z 
2025-09-07T10:12:09.8768438Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8768640Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8768700Z     return mod(*inputs)
2025-09-07T10:12:09.8768936Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8769003Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8769210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8769275Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8769499Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8769582Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8769811Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8769917Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8770163Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8770275Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8770278Z 
2025-09-07T10:12:09.8770380Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8770579Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8770644Z     return mod(*inputs)
2025-09-07T10:12:09.8770875Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8770944Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8771148Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8771215Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8771447Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8771525Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8771758Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8771855Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8772101Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8772214Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8772251Z 
2025-09-07T10:12:09.8772348Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8772545Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8772604Z     return mod(*inputs)
2025-09-07T10:12:09.8772838Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8772905Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8773107Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8773179Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8773399Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8773518Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8773747Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8773847Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8774099Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8774206Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8774286Z 
2025-09-07T10:12:09.8774390Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8774585Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8774643Z     return mod(*inputs)
2025-09-07T10:12:09.8774878Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8774946Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8775156Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8775224Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8775447Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8775533Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8775767Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8775871Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8776095Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8776202Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8776454Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8776517Z     query, key, value = [
2025-09-07T10:12:09.8776780Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8776885Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8776888Z 
2025-09-07T10:12:09.8776992Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8777188Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8777247Z     return mod(*inputs)
2025-09-07T10:12:09.8777486Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8777547Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8777758Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8777828Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8778049Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8778169Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8778397Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8778499Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8778723Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8778829Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8779076Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8779136Z     query, key, value = [
2025-09-07T10:12:09.8779401Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8779534Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8779537Z 
2025-09-07T10:12:09.8779639Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8779835Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8779892Z     return mod(*inputs)
2025-09-07T10:12:09.8780125Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8780248Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8780463Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8780532Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8780764Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8780858Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8781095Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8781205Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8781425Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8781531Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8781779Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8781901Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8782144Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8782294Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8782299Z 
2025-09-07T10:12:09.8782398Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8782592Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8782656Z     return mod(*inputs)
2025-09-07T10:12:09.8782888Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8782950Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8783160Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8783227Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8783451Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8783529Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8783759Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8783862Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8784085Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8784225Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8784478Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8784599Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8784844Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8784990Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8784993Z 
2025-09-07T10:12:09.8785093Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8785322Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8785383Z     return mod(*inputs)
2025-09-07T10:12:09.8785652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8785720Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8785932Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8785999Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8786290Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8786369Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8786601Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8786705Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8786926Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8787033Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8787282Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8787408Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8787648Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8787793Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8787797Z 
2025-09-07T10:12:09.8787913Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8788106Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8788172Z     return mod(*inputs)
2025-09-07T10:12:09.8788401Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8788464Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8788670Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8788737Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8788962Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8789041Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8789274Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8789376Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8789599Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8789702Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8789948Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8790010Z     query, key, value = [
2025-09-07T10:12:09.8790310Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8790411Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8790414Z 
2025-09-07T10:12:09.8790514Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8790709Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8790769Z     return mod(*inputs)
2025-09-07T10:12:09.8791000Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8791064Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8791311Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8791377Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8791603Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8791684Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8791916Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8792014Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8792299Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8792403Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8792654Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8792782Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8793019Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8793100Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8793103Z 
2025-09-07T10:12:09.8793200Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8793394Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8793458Z     return mod(*inputs)
2025-09-07T10:12:09.8793690Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8793754Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8793963Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8794030Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8794258Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8794337Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8794569Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8794708Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8795079Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8795257Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8795537Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8795686Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8795984Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8796082Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8796086Z 
2025-09-07T10:12:09.8796285Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8803823Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8803903Z     return mod(*inputs)
2025-09-07T10:12:09.8804166Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8804235Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8804519Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8804598Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8804898Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8804995Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8805369Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8805480Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8805716Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8805821Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8806086Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8806328Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8806334Z 
2025-09-07T10:12:09.8806443Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8806646Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8806707Z     return mod(*inputs)
2025-09-07T10:12:09.8806949Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8807014Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8807226Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8807296Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8807523Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8807612Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8807844Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8807954Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8808177Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8808285Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8808536Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8808603Z     return self.output_linear(x)
2025-09-07T10:12:09.8808609Z 
2025-09-07T10:12:09.8808712Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8808908Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8808972Z     return mod(*inputs)
2025-09-07T10:12:09.8809209Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8809273Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8809481Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8809548Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8809776Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8809858Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8810089Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8810244Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8810489Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8810603Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8810610Z 
2025-09-07T10:12:09.8810708Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8810909Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8810967Z     return mod(*inputs)
2025-09-07T10:12:09.8811197Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8811309Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8811513Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8811586Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8811806Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8811885Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8812438Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8812538Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8812782Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8812891Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8812897Z 
2025-09-07T10:12:09.8812995Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8813185Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8813242Z     return mod(*inputs)
2025-09-07T10:12:09.8813481Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8813546Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8813753Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8813822Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8814042Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8814126Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8814355Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8814462Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8814702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8814809Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8814812Z 
2025-09-07T10:12:09.8814914Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8815108Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8815171Z     return mod(*inputs)
2025-09-07T10:12:09.8815404Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8815471Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8815676Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8815743Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8815971Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8816049Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8816324Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8816420Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8816424Z 
2025-09-07T10:12:09.8816517Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8816713Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8816770Z     return mod(*inputs)
2025-09-07T10:12:09.8817006Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8817067Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8817269Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8817374Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8817596Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8817680Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8817908Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8818007Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8818287Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8818393Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8818644Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8818708Z     query, key, value = [
2025-09-07T10:12:09.8818971Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8819074Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8819079Z 
2025-09-07T10:12:09.8819171Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8819369Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8819428Z     return mod(*inputs)
2025-09-07T10:12:09.8819665Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8819729Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8819934Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8820002Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8820224Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8820305Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8820533Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8820634Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8820856Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8820955Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8821211Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8821271Z     query, key, value = [
2025-09-07T10:12:09.8821532Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8821627Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8821631Z 
2025-09-07T10:12:09.8821719Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8821921Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8822039Z     return mod(*inputs)
2025-09-07T10:12:09.8822275Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8822340Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8822550Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8822621Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8822848Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8822931Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8823168Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8823314Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8823537Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8823639Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8823895Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8824023Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8824337Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8824491Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8824495Z 
2025-09-07T10:12:09.8824598Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8824802Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8824860Z     return mod(*inputs)
2025-09-07T10:12:09.8825099Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8825167Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8825376Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8825444Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8825730Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8825818Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8826051Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8826157Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8826384Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8826487Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8826744Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8826866Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8827113Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8827264Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8827268Z 
2025-09-07T10:12:09.8827370Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8827568Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8827626Z     return mod(*inputs)
2025-09-07T10:12:09.8827864Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8827928Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8828140Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8828255Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8828480Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8828565Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8828797Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8828903Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8829125Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8829262Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8829516Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8829636Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8829884Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8830031Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8830034Z 
2025-09-07T10:12:09.8830197Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8830400Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8830459Z     return mod(*inputs)
2025-09-07T10:12:09.8830698Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8830766Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8830975Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8831044Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8831268Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8831354Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8831582Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8831689Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8831912Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8832019Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8832264Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8832329Z     query, key, value = [
2025-09-07T10:12:09.8832595Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8832702Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8832705Z 
2025-09-07T10:12:09.8832808Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8833004Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8833063Z     return mod(*inputs)
2025-09-07T10:12:09.8833298Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8833365Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8833574Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8833644Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8833867Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8833952Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8834234Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8834339Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8834563Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8834671Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8834924Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8835048Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8835291Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8835405Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8835408Z 
2025-09-07T10:12:09.8835511Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8835712Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8835771Z     return mod(*inputs)
2025-09-07T10:12:09.8836006Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8836134Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8836350Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8836419Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8836645Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8836733Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8836962Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8837066Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8837287Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8837392Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8837643Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8837763Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8838003Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8838079Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8838083Z 
2025-09-07T10:12:09.8838185Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8838382Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8838439Z     return mod(*inputs)
2025-09-07T10:12:09.8838674Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8838738Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8838947Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8839017Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8839242Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8839324Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8839563Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8839671Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8839894Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8839997Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8840288Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8840421Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8840426Z 
2025-09-07T10:12:09.8840530Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8840728Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8840788Z     return mod(*inputs)
2025-09-07T10:12:09.8841022Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8841189Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8841400Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8841467Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8841702Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8841784Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8842022Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8842205Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8842430Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8842532Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8842780Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8842855Z     return self.output_linear(x)
2025-09-07T10:12:09.8842859Z 
2025-09-07T10:12:09.8842956Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8843148Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8843214Z     return mod(*inputs)
2025-09-07T10:12:09.8843441Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8843506Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8843713Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8843784Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8844007Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8844084Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8844319Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8844415Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8844664Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8844777Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8844780Z 
2025-09-07T10:12:09.8844878Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8845085Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8845144Z     return mod(*inputs)
2025-09-07T10:12:09.8845379Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8845444Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8845649Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8845724Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8845944Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8846069Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8846294Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8846398Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8846644Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8846751Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8846755Z 
2025-09-07T10:12:09.8846857Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8847050Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8847146Z     return mod(*inputs)
2025-09-07T10:12:09.8847377Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8847444Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8847654Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8847719Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8848004Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8848084Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8848311Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8848413Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8848652Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8848763Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8848766Z 
2025-09-07T10:12:09.8848857Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8849058Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8849114Z     return mod(*inputs)
2025-09-07T10:12:09.8849343Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8849412Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8849629Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8849702Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8849927Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8850005Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8850237Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8850333Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8850561Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8850661Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8850915Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8850980Z     query, key, value = [
2025-09-07T10:12:09.8851241Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8851347Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8851351Z 
2025-09-07T10:12:09.8851445Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8851640Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8851697Z     return mod(*inputs)
2025-09-07T10:12:09.8851962Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8852035Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8852240Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8852312Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8852533Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8852609Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8852840Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8852970Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8853203Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8853304Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8853554Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8853614Z     query, key, value = [
2025-09-07T10:12:09.8853935Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8854035Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8854038Z 
2025-09-07T10:12:09.8854130Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8854325Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8854383Z     return mod(*inputs)
2025-09-07T10:12:09.8854614Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8854681Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8854885Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8854953Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8855175Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8855255Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8855485Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8855579Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8855802Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8855901Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8856152Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8856276Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8856512Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8856665Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8856668Z 
2025-09-07T10:12:09.8856765Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8856962Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8857017Z     return mod(*inputs)
2025-09-07T10:12:09.8857247Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8857319Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8857523Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8857590Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8857856Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8857940Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8858168Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8858272Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8858494Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8858594Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8858841Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8858996Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8859231Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8859381Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8859385Z 
2025-09-07T10:12:09.8859479Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8859736Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8859795Z     return mod(*inputs)
2025-09-07T10:12:09.8860028Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8860089Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8860292Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8860362Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8860582Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8860662Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8860891Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8860987Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8861210Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8861308Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8861555Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8861672Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8861906Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 24, in forward
2025-09-07T10:12:09.8862048Z     scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(query.size(-1))
2025-09-07T10:12:09.8862052Z 
2025-09-07T10:12:09.8862152Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8862350Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8862408Z     return mod(*inputs)
2025-09-07T10:12:09.8862649Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8862713Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8862914Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8862983Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8863204Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8863287Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8863515Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8863651Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8863874Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8863973Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8864224Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 42, in forward
2025-09-07T10:12:09.8864284Z     query, key, value = [
2025-09-07T10:12:09.8864539Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 43, in <listcomp>
2025-09-07T10:12:09.8864677Z     l(x).view(batch_size, -1, self.h, self.d_k).transpose(1, 2)
2025-09-07T10:12:09.8864680Z 
2025-09-07T10:12:09.8864777Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8864979Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8865038Z     return mod(*inputs)
2025-09-07T10:12:09.8865272Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8865336Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8865678Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8865752Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8865976Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8866061Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8866290Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8866393Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8866617Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8866718Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8866968Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8867092Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8867335Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8867415Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8867419Z 
2025-09-07T10:12:09.8867515Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8867712Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8867771Z     return mod(*inputs)
2025-09-07T10:12:09.8868000Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8868064Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8868266Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8868337Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8868561Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8868642Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8868869Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8868966Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8869190Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8869288Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8869538Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 48, in forward
2025-09-07T10:12:09.8869698Z     x, attn = self.attention(query, key, value, self.dropout, mask=mask)
2025-09-07T10:12:09.8869938Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/single.py", line 41, in forward
2025-09-07T10:12:09.8870016Z     return torch.matmul(p_attn, value), p_attn
2025-09-07T10:12:09.8870020Z 
2025-09-07T10:12:09.8870114Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8870311Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8870367Z     return mod(*inputs)
2025-09-07T10:12:09.8870596Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8870693Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8870897Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8870966Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8871185Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8871267Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8871558Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8871658Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8871880Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8871976Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8872228Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 51, in forward
2025-09-07T10:12:09.8872356Z     x = x.transpose(1, 2).contiguous().view(batch_size, -1, self.h * self.d_k)
2025-09-07T10:12:09.8872361Z 
2025-09-07T10:12:09.8872460Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8872655Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8872713Z     return mod(*inputs)
2025-09-07T10:12:09.8872945Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8873008Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8873216Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8873281Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8873501Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 48, in forward
2025-09-07T10:12:09.8873585Z     x = self.input_sublayer(x, self.lambda_module)
2025-09-07T10:12:09.8873813Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8873913Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8874133Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 19, in forward
2025-09-07T10:12:09.8874232Z     return self.attention.forward(x, x, x, mask=self.mask)
2025-09-07T10:12:09.8874480Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/attention/multi_head.py", line 53, in forward
2025-09-07T10:12:09.8874548Z     return self.output_linear(x)
2025-09-07T10:12:09.8874551Z 
2025-09-07T10:12:09.8874648Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8874838Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8874899Z     return mod(*inputs)
2025-09-07T10:12:09.8875128Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8875242Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8875449Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8875515Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8875740Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8875820Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8876048Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8876149Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8876391Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8876536Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8876539Z 
2025-09-07T10:12:09.8876636Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8876827Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8876884Z     return mod(*inputs)
2025-09-07T10:12:09.8877115Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8877246Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8877449Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8877519Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8877739Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8877820Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8878053Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8878149Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8878394Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8878499Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8878502Z 
2025-09-07T10:12:09.8878600Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8878794Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8878850Z     return mod(*inputs)
2025-09-07T10:12:09.8879082Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8879143Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8879348Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8879415Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8879634Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8879714Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8879941Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8880044Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8880285Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/feed_forward.py", line 15, in forward
2025-09-07T10:12:09.8880386Z     return self.w_2(self.dropout(self.activation(self.w_1(x))))
2025-09-07T10:12:09.8880393Z 
2025-09-07T10:12:09.8880487Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8880681Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8880740Z     return mod(*inputs)
2025-09-07T10:12:09.8880966Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 24, in forward
2025-09-07T10:12:09.8881082Z     x = self.bert(x, segment_label)
2025-09-07T10:12:09.8881284Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/bert.py", line 51, in forward
2025-09-07T10:12:09.8881349Z     x = transformer.forward(x, mask)
2025-09-07T10:12:09.8881573Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/transformer.py", line 49, in forward
2025-09-07T10:12:09.8881650Z     x = self.output_sublayer(x, self.feed_forward)
2025-09-07T10:12:09.8881882Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/utils/sublayer.py", line 20, in forward
2025-09-07T10:12:09.8881979Z     return x + self.dropout(sublayer.forward(self.norm(x)))
2025-09-07T10:12:09.8882019Z 
2025-09-07T10:12:09.8882113Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8882310Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8882371Z     return mod(*inputs)
2025-09-07T10:12:09.8882599Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 25, in forward
2025-09-07T10:12:09.8882681Z     return self.next_sentence(x), self.mask_lm(x)
2025-09-07T10:12:09.8882970Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 42, in forward
2025-09-07T10:12:09.8883051Z     return self.softmax(self.linear(x[:, 0]))
2025-09-07T10:12:09.8883054Z 
2025-09-07T10:12:09.8883148Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:09.8883345Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:09.8883406Z     return mod(*inputs)
2025-09-07T10:12:09.8883639Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 25, in forward
2025-09-07T10:12:09.8883720Z     return self.next_sentence(x), self.mask_lm(x)
2025-09-07T10:12:09.8883946Z   File "/torchbench/torchbenchmark/models/BERT_pytorch/bert_pytorch/model/language_model.py", line 61, in forward
2025-09-07T10:12:09.8884020Z     return self.softmax(self.linear(x))
2025-09-07T10:12:09.8884023Z 
2025-09-07T10:12:28.5000979Z 
2025-09-07T10:12:28.6309996Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:12:28.7583907Z running benchmark:   3% 1/30 [00:00<00:03,  7.65it/s]
2025-09-07T10:12:28.8866394Z running benchmark:   7% 2/30 [00:00<00:03,  7.77it/s]
2025-09-07T10:12:29.0147094Z running benchmark:  10% 3/30 [00:00<00:03,  7.78it/s]
2025-09-07T10:12:29.1430409Z running benchmark:  13% 4/30 [00:00<00:03,  7.79it/s]
2025-09-07T10:12:29.3432210Z running benchmark:  17% 5/30 [00:00<00:03,  7.79it/s]
2025-09-07T10:12:29.4736430Z running benchmark:  20% 6/30 [00:00<00:03,  6.55it/s]
2025-09-07T10:12:29.6008816Z running benchmark:  23% 7/30 [00:00<00:03,  6.87it/s]
2025-09-07T10:12:29.7292455Z running benchmark:  27% 8/30 [00:01<00:03,  7.16it/s]
2025-09-07T10:12:29.8571336Z running benchmark:  30% 9/30 [00:01<00:02,  7.35it/s]
2025-09-07T10:12:29.9848429Z running benchmark:  33% 10/30 [00:01<00:02,  7.49it/s]
2025-09-07T10:12:30.1127657Z running benchmark:  37% 11/30 [00:01<00:02,  7.59it/s]
2025-09-07T10:12:30.2396823Z running benchmark:  40% 12/30 [00:01<00:02,  7.66it/s]
2025-09-07T10:12:30.3668532Z running benchmark:  43% 13/30 [00:01<00:02,  7.72it/s]
2025-09-07T10:12:30.4941488Z running benchmark:  47% 14/30 [00:01<00:02,  7.76it/s]
2025-09-07T10:12:30.6223171Z running benchmark:  50% 15/30 [00:01<00:01,  7.79it/s]
2025-09-07T10:12:30.7501829Z running benchmark:  53% 16/30 [00:02<00:01,  7.80it/s]
2025-09-07T10:12:30.8777778Z running benchmark:  57% 17/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:12:31.0057400Z running benchmark:  60% 18/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:12:31.1336055Z running benchmark:  63% 19/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:12:31.2610597Z running benchmark:  67% 20/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:12:31.3894026Z running benchmark:  70% 21/30 [00:02<00:01,  7.82it/s]
2025-09-07T10:12:31.5161100Z running benchmark:  73% 22/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:12:31.6438669Z running benchmark:  77% 23/30 [00:03<00:00,  7.84it/s]
2025-09-07T10:12:31.7714055Z running benchmark:  80% 24/30 [00:03<00:00,  7.84it/s]
2025-09-07T10:12:31.8991476Z running benchmark:  83% 25/30 [00:03<00:00,  7.84it/s]
2025-09-07T10:12:32.0261749Z running benchmark:  87% 26/30 [00:03<00:00,  7.83it/s]
2025-09-07T10:12:32.1532487Z running benchmark:  90% 27/30 [00:03<00:00,  7.85it/s]
2025-09-07T10:12:32.2801013Z running benchmark:  93% 28/30 [00:03<00:00,  7.85it/s]
2025-09-07T10:12:32.4078992Z running benchmark:  97% 29/30 [00:03<00:00,  7.86it/s]
2025-09-07T10:12:32.4079340Z running benchmark: 100% 30/30 [00:03<00:00,  7.85it/s]
2025-09-07T10:12:32.4081620Z running benchmark: 100% 30/30 [00:03<00:00,  7.68it/s]
2025-09-07T10:12:32.4908076Z 1.426x
2025-09-07T10:12:32.4911957Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:12:34.8249071Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:12:34.8250467Z   import pynvml  # type: ignore[import]
2025-09-07T10:12:36.8488899Z 
2025-09-07T10:12:39.0721089Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:12:39.0721406Z loading model: 0it [00:02, ?it/s]
2025-09-07T10:12:39.0818303Z cpu  eval  Background_Matting                 
2025-09-07T10:12:46.2371450Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2371980Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2372364Z     return mod(*inputs)
2025-09-07T10:12:46.2372686Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 236, in forward
2025-09-07T10:12:46.2373054Z     img_feat1 = self.model_enc1(image)
2025-09-07T10:12:46.2373414Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2373786Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2373940Z 
2025-09-07T10:12:46.2374027Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2374242Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2374448Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2374683Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2375054Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2375385Z     return mod(*inputs)
2025-09-07T10:12:46.2375712Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 239, in forward
2025-09-07T10:12:46.2376056Z     back_feat = self.model_enc_back(back)
2025-09-07T10:12:46.2376394Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2376752Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2376903Z 
2025-09-07T10:12:46.2376981Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2377183Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2377417Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2377649Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2378000Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2378332Z     return mod(*inputs)
2025-09-07T10:12:46.2378633Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2378971Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2379295Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2379640Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2380101Z 
2025-09-07T10:12:46.2380180Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2380393Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2380592Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2380782Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2380984Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2381213Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2381408Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2381600Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2381794Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2381992Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2382276Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2382481Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2382681Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2382875Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2383070Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2383256Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2383450Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2383647Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2383841Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2384181Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2384372Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2384566Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2384766Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2384970Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2385166Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2385366Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2385634Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2385851Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2386060Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2386262Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2386464Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2386659Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2386845Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2387104Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2387338Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2387702Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2388040Z     return mod(*inputs)
2025-09-07T10:12:46.2388360Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 236, in forward
2025-09-07T10:12:46.2388707Z     img_feat1 = self.model_enc1(image)
2025-09-07T10:12:46.2388843Z 
2025-09-07T10:12:46.2388949Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2389312Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2389646Z     return mod(*inputs)
2025-09-07T10:12:46.2389945Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 236, in forward
2025-09-07T10:12:46.2390278Z     img_feat1 = self.model_enc1(image)
2025-09-07T10:12:46.2390401Z 
2025-09-07T10:12:46.2390508Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2390849Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2391169Z     return mod(*inputs)
2025-09-07T10:12:46.2391462Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 236, in forward
2025-09-07T10:12:46.2391801Z     img_feat1 = self.model_enc1(image)
2025-09-07T10:12:46.2391923Z 
2025-09-07T10:12:46.2392024Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2392359Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2392690Z     return mod(*inputs)
2025-09-07T10:12:46.2393031Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 237, in forward
2025-09-07T10:12:46.2393364Z     img_feat = self.model_enc2(img_feat1)
2025-09-07T10:12:46.2393494Z 
2025-09-07T10:12:46.2393591Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2393953Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2394274Z     return mod(*inputs)
2025-09-07T10:12:46.2394568Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 237, in forward
2025-09-07T10:12:46.2394908Z     img_feat = self.model_enc2(img_feat1)
2025-09-07T10:12:46.2395051Z 
2025-09-07T10:12:46.2395153Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2395566Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2395898Z     return mod(*inputs)
2025-09-07T10:12:46.2396200Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 239, in forward
2025-09-07T10:12:46.2396536Z     back_feat = self.model_enc_back(back)
2025-09-07T10:12:46.2396674Z 
2025-09-07T10:12:46.2396772Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2397125Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2397516Z     return mod(*inputs)
2025-09-07T10:12:46.2397814Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 239, in forward
2025-09-07T10:12:46.2398142Z     back_feat = self.model_enc_back(back)
2025-09-07T10:12:46.2398279Z 
2025-09-07T10:12:46.2398372Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2398880Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2399216Z     return mod(*inputs)
2025-09-07T10:12:46.2399506Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 239, in forward
2025-09-07T10:12:46.2399848Z     back_feat = self.model_enc_back(back)
2025-09-07T10:12:46.2399986Z 
2025-09-07T10:12:46.2400082Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2400432Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2400756Z     return mod(*inputs)
2025-09-07T10:12:46.2401032Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 239, in forward
2025-09-07T10:12:46.2401364Z     back_feat = self.model_enc_back(back)
2025-09-07T10:12:46.2401491Z 
2025-09-07T10:12:46.2401586Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2401939Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2402265Z     return mod(*inputs)
2025-09-07T10:12:46.2402550Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 239, in forward
2025-09-07T10:12:46.2402873Z     back_feat = self.model_enc_back(back)
2025-09-07T10:12:46.2402998Z 
2025-09-07T10:12:46.2403099Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2403442Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2403749Z     return mod(*inputs)
2025-09-07T10:12:46.2404039Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 245, in forward
2025-09-07T10:12:46.2404407Z     self.comb_back(torch.cat([img_feat, back_feat], dim=1)),
2025-09-07T10:12:46.2404572Z 
2025-09-07T10:12:46.2404653Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2404879Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2405219Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2405541Z     return mod(*inputs)
2025-09-07T10:12:46.2405831Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 245, in forward
2025-09-07T10:12:46.2406264Z     self.comb_back(torch.cat([img_feat, back_feat], dim=1)),
2025-09-07T10:12:46.2406427Z 
2025-09-07T10:12:46.2406522Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2406872Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2407191Z     return mod(*inputs)
2025-09-07T10:12:46.2407485Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2407823Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2407951Z 
2025-09-07T10:12:46.2408048Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2408400Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2408837Z     return mod(*inputs)
2025-09-07T10:12:46.2409132Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2409462Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2409594Z 
2025-09-07T10:12:46.2409695Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2410043Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2410365Z     return mod(*inputs)
2025-09-07T10:12:46.2410777Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2411119Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2411254Z 
2025-09-07T10:12:46.2411355Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2411728Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2412062Z     return mod(*inputs)
2025-09-07T10:12:46.2412357Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2412692Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2412827Z 
2025-09-07T10:12:46.2412924Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2413281Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2413603Z     return mod(*inputs)
2025-09-07T10:12:46.2413886Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2414211Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2414345Z 
2025-09-07T10:12:46.2414444Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2414799Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2415118Z     return mod(*inputs)
2025-09-07T10:12:46.2415419Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 240, in forward
2025-09-07T10:12:46.2415745Z     seg_feat = self.model_enc_seg(seg)
2025-09-07T10:12:46.2415868Z 
2025-09-07T10:12:46.2415970Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2416323Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2416638Z     return mod(*inputs)
2025-09-07T10:12:46.2416928Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 246, in forward
2025-09-07T10:12:46.2417294Z     self.comb_seg(torch.cat([img_feat, seg_feat], dim=1)),
2025-09-07T10:12:46.2417453Z 
2025-09-07T10:12:46.2417535Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2417753Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2418107Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2418429Z     return mod(*inputs)
2025-09-07T10:12:46.2418720Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 246, in forward
2025-09-07T10:12:46.2419084Z     self.comb_seg(torch.cat([img_feat, seg_feat], dim=1)),
2025-09-07T10:12:46.2419284Z 
2025-09-07T10:12:46.2419383Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2419730Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2420051Z     return mod(*inputs)
2025-09-07T10:12:46.2420342Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 247, in forward
2025-09-07T10:12:46.2420707Z     self.comb_multi(torch.cat([img_feat, back_feat], dim=1)),
2025-09-07T10:12:46.2420881Z 
2025-09-07T10:12:46.2420955Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2421182Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2421537Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2421899Z     return mod(*inputs)
2025-09-07T10:12:46.2422182Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 247, in forward
2025-09-07T10:12:46.2422547Z     self.comb_multi(torch.cat([img_feat, back_feat], dim=1)),
2025-09-07T10:12:46.2422724Z 
2025-09-07T10:12:46.2422820Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2423171Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2423494Z     return mod(*inputs)
2025-09-07T10:12:46.2423876Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 245, in forward
2025-09-07T10:12:46.2424250Z     self.comb_back(torch.cat([img_feat, back_feat], dim=1)),
2025-09-07T10:12:46.2424414Z 
2025-09-07T10:12:46.2424519Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2424872Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2425193Z     return mod(*inputs)
2025-09-07T10:12:46.2425486Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 246, in forward
2025-09-07T10:12:46.2425920Z     self.comb_seg(torch.cat([img_feat, seg_feat], dim=1)),
2025-09-07T10:12:46.2426082Z 
2025-09-07T10:12:46.2426189Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2426549Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2426866Z     return mod(*inputs)
2025-09-07T10:12:46.2427161Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 247, in forward
2025-09-07T10:12:46.2427530Z     self.comb_multi(torch.cat([img_feat, back_feat], dim=1)),
2025-09-07T10:12:46.2427692Z 
2025-09-07T10:12:46.2427796Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2428135Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2428464Z     return mod(*inputs)
2025-09-07T10:12:46.2428757Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 243, in forward
2025-09-07T10:12:46.2429087Z     oth_feat = torch.cat(
2025-09-07T10:12:46.2429192Z 
2025-09-07T10:12:46.2429276Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2429501Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2429857Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2430175Z     return mod(*inputs)
2025-09-07T10:12:46.2430472Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2430851Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2431043Z 
2025-09-07T10:12:46.2431118Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2431352Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2431718Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2432043Z     return mod(*inputs)
2025-09-07T10:12:46.2432333Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2432764Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2432955Z 
2025-09-07T10:12:46.2433053Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2433403Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2433726Z     return mod(*inputs)
2025-09-07T10:12:46.2434022Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2434395Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2434573Z 
2025-09-07T10:12:46.2434678Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2435069Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2435388Z     return mod(*inputs)
2025-09-07T10:12:46.2435675Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2436065Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2436444Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2436766Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2437165Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2437530Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2437684Z 
2025-09-07T10:12:46.2437791Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2438150Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2438475Z     return mod(*inputs)
2025-09-07T10:12:46.2438769Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2439157Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2439542Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2439867Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2439985Z 
2025-09-07T10:12:46.2440080Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2440439Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2440772Z     return mod(*inputs)
2025-09-07T10:12:46.2441060Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2441428Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2441810Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2442140Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2442458Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2442808Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2442957Z 
2025-09-07T10:12:46.2443051Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2443408Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2443736Z     return mod(*inputs)
2025-09-07T10:12:46.2444029Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2444404Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2444780Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2445103Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2445412Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2445758Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2445950Z 
2025-09-07T10:12:46.2446045Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2446397Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2446717Z     return mod(*inputs)
2025-09-07T10:12:46.2447007Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2447380Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2447748Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2448064Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2448173Z 
2025-09-07T10:12:46.2448315Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2448670Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2448984Z     return mod(*inputs)
2025-09-07T10:12:46.2449280Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2449660Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2450034Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2450349Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2450540Z 
2025-09-07T10:12:46.2450640Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2450993Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2451314Z     return mod(*inputs)
2025-09-07T10:12:46.2451605Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2451974Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2452347Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2452674Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2452988Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2453338Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2453498Z 
2025-09-07T10:12:46.2453598Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2453955Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2454282Z     return mod(*inputs)
2025-09-07T10:12:46.2454569Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2454937Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2455315Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2455638Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2455750Z 
2025-09-07T10:12:46.2455856Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2456210Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2456524Z     return mod(*inputs)
2025-09-07T10:12:46.2456815Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2457189Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2457565Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2457881Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2458194Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2458546Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2458696Z 
2025-09-07T10:12:46.2458803Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2459201Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2459515Z     return mod(*inputs)
2025-09-07T10:12:46.2459801Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2460177Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2460561Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2460878Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2461186Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2461537Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2461727Z 
2025-09-07T10:12:46.2461832Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2462182Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2462495Z     return mod(*inputs)
2025-09-07T10:12:46.2462787Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2463155Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2463588Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2463909Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2464030Z 
2025-09-07T10:12:46.2464126Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2464481Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2464801Z     return mod(*inputs)
2025-09-07T10:12:46.2465089Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2465460Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2465892Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2466215Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2466330Z 
2025-09-07T10:12:46.2466432Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2466785Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2467117Z     return mod(*inputs)
2025-09-07T10:12:46.2467411Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2467795Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2468176Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2468494Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2468807Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2469165Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2469316Z 
2025-09-07T10:12:46.2469422Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2469779Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2470116Z     return mod(*inputs)
2025-09-07T10:12:46.2470410Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2470789Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2471177Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2471493Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2471617Z 
2025-09-07T10:12:46.2471712Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2472066Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2472388Z     return mod(*inputs)
2025-09-07T10:12:46.2472721Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2473094Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2473467Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2473790Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2474106Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2474454Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2474609Z 
2025-09-07T10:12:46.2474709Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2475117Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2475442Z     return mod(*inputs)
2025-09-07T10:12:46.2475731Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2476106Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2476483Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2476805Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2478231Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2478597Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2478754Z 
2025-09-07T10:12:46.2478851Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2479210Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2479538Z     return mod(*inputs)
2025-09-07T10:12:46.2479828Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2480202Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2480578Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2480959Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2481146Z 
2025-09-07T10:12:46.2481301Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2491542Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2491954Z     return mod(*inputs)
2025-09-07T10:12:46.2492281Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2492681Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2493072Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2493402Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2493523Z 
2025-09-07T10:12:46.2493627Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2493998Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2494331Z     return mod(*inputs)
2025-09-07T10:12:46.2494626Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2495015Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2495393Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2495719Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2496048Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2496409Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2496570Z 
2025-09-07T10:12:46.2496670Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2497030Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2497441Z     return mod(*inputs)
2025-09-07T10:12:46.2497733Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2498119Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2498503Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2499021Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2499139Z 
2025-09-07T10:12:46.2499246Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2499599Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2499921Z     return mod(*inputs)
2025-09-07T10:12:46.2500296Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2500673Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2501052Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2501370Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2501684Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2502037Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2502313Z 
2025-09-07T10:12:46.2502422Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2502772Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2503092Z     return mod(*inputs)
2025-09-07T10:12:46.2503383Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2503782Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2504148Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2504475Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2504783Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2505131Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2505276Z 
2025-09-07T10:12:46.2505377Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2505803Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2506128Z     return mod(*inputs)
2025-09-07T10:12:46.2506414Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2506787Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2507155Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2507473Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2507605Z 
2025-09-07T10:12:46.2507700Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2508072Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2508457Z     return mod(*inputs)
2025-09-07T10:12:46.2508737Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2509111Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2509480Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2509800Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2509908Z 
2025-09-07T10:12:46.2510007Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2510356Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2510671Z     return mod(*inputs)
2025-09-07T10:12:46.2510951Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2511401Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2511771Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2512093Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2512406Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2512767Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2512913Z 
2025-09-07T10:12:46.2513012Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2513355Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2513739Z     return mod(*inputs)
2025-09-07T10:12:46.2514025Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2514393Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2514760Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2515077Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2515195Z 
2025-09-07T10:12:46.2515288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2515711Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2516033Z     return mod(*inputs)
2025-09-07T10:12:46.2516311Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2516688Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2517062Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2517385Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2517688Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2518039Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2518194Z 
2025-09-07T10:12:46.2518293Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2518653Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2518981Z     return mod(*inputs)
2025-09-07T10:12:46.2519266Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2519645Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2520017Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2520339Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2520652Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2520995Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2521151Z 
2025-09-07T10:12:46.2521244Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2521595Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2521914Z     return mod(*inputs)
2025-09-07T10:12:46.2522201Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2522581Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2522955Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2523277Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2523391Z 
2025-09-07T10:12:46.2523494Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2523836Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2524156Z     return mod(*inputs)
2025-09-07T10:12:46.2524495Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2524869Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2525233Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2525557Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2525675Z 
2025-09-07T10:12:46.2525770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2526113Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2526430Z     return mod(*inputs)
2025-09-07T10:12:46.2526711Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2527120Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2527490Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2527809Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2528109Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2528458Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2528610Z 
2025-09-07T10:12:46.2528765Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2529117Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2529430Z     return mod(*inputs)
2025-09-07T10:12:46.2529702Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2530072Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2530441Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2530762Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2530876Z 
2025-09-07T10:12:46.2530975Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2531316Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2531631Z     return mod(*inputs)
2025-09-07T10:12:46.2531920Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2532293Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2532657Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2532978Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2533281Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2533629Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2533775Z 
2025-09-07T10:12:46.2533875Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2534221Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2534535Z     return mod(*inputs)
2025-09-07T10:12:46.2534821Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2535196Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2535555Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2535874Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2536177Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2536524Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2536672Z 
2025-09-07T10:12:46.2536768Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2537109Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2537469Z     return mod(*inputs)
2025-09-07T10:12:46.2537752Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2538136Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2538518Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2538845Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2538968Z 
2025-09-07T10:12:46.2539070Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2539426Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2539747Z     return mod(*inputs)
2025-09-07T10:12:46.2540073Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2540451Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2540824Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2541146Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2541257Z 
2025-09-07T10:12:46.2541352Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2541767Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2542094Z     return mod(*inputs)
2025-09-07T10:12:46.2542384Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2542758Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2543123Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2543442Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2543750Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2544103Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2544253Z 
2025-09-07T10:12:46.2544353Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2544695Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2545014Z     return mod(*inputs)
2025-09-07T10:12:46.2545297Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2545729Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2546089Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2546399Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2546512Z 
2025-09-07T10:12:46.2546605Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2546944Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2547256Z     return mod(*inputs)
2025-09-07T10:12:46.2547532Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2547895Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2548251Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2548561Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2548861Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2549200Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2549347Z 
2025-09-07T10:12:46.2549437Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2549777Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2550087Z     return mod(*inputs)
2025-09-07T10:12:46.2550360Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2550798Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2551156Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2551465Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2551760Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2552096Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2552249Z 
2025-09-07T10:12:46.2552338Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2552677Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2553027Z     return mod(*inputs)
2025-09-07T10:12:46.2553301Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2553667Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2554033Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2554345Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2554455Z 
2025-09-07T10:12:46.2554545Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2554981Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2555299Z     return mod(*inputs)
2025-09-07T10:12:46.2555573Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 252, in forward
2025-09-07T10:12:46.2555939Z     out_dec = self.model_res_dec(torch.cat([img_feat, oth_feat], dim=1))
2025-09-07T10:12:46.2556300Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2556611Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2556723Z 
2025-09-07T10:12:46.2556814Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2557158Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2557464Z     return mod(*inputs)
2025-09-07T10:12:46.2557739Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2558070Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2558391Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2558702Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2558808Z 
2025-09-07T10:12:46.2558902Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2559241Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2559556Z     return mod(*inputs)
2025-09-07T10:12:46.2559830Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2560154Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2560469Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2560776Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2561080Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2561424Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2561569Z 
2025-09-07T10:12:46.2561658Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2561996Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2562302Z     return mod(*inputs)
2025-09-07T10:12:46.2562576Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2562898Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2563214Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2563576Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2563870Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2564199Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2564341Z 
2025-09-07T10:12:46.2564434Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2564764Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2565072Z     return mod(*inputs)
2025-09-07T10:12:46.2565346Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2565707Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2566021Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2566329Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2566438Z 
2025-09-07T10:12:46.2566532Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2566869Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2567174Z     return mod(*inputs)
2025-09-07T10:12:46.2567516Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2567840Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2568154Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2568455Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2568563Z 
2025-09-07T10:12:46.2568651Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2568987Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2569292Z     return mod(*inputs)
2025-09-07T10:12:46.2569563Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2569883Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2570201Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2570508Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2570815Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2571167Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2571314Z 
2025-09-07T10:12:46.2571401Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2571738Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2572046Z     return mod(*inputs)
2025-09-07T10:12:46.2572319Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2572636Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2572955Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2573263Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2573557Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2573886Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2574029Z 
2025-09-07T10:12:46.2574118Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2574451Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2574755Z     return mod(*inputs)
2025-09-07T10:12:46.2575027Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2575349Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2575663Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2576015Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2576121Z 
2025-09-07T10:12:46.2576211Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2576549Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2576853Z     return mod(*inputs)
2025-09-07T10:12:46.2577126Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2577449Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2577763Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2578068Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2578397Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2578729Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2578871Z 
2025-09-07T10:12:46.2578963Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2579302Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2579607Z     return mod(*inputs)
2025-09-07T10:12:46.2579883Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2580279Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2580595Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2580901Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2581013Z 
2025-09-07T10:12:46.2581105Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2581444Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2581749Z     return mod(*inputs)
2025-09-07T10:12:46.2582017Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2582340Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2582658Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2582965Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2583259Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2583596Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2583741Z 
2025-09-07T10:12:46.2583833Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2584172Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2584476Z     return mod(*inputs)
2025-09-07T10:12:46.2584751Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2585070Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2585385Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2585768Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2586079Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2586423Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2586573Z 
2025-09-07T10:12:46.2586676Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2587031Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2587351Z     return mod(*inputs)
2025-09-07T10:12:46.2587639Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2587974Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2588298Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2588611Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2588769Z 
2025-09-07T10:12:46.2588866Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2589207Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2589530Z     return mod(*inputs)
2025-09-07T10:12:46.2589810Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2590133Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2590447Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2590755Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2590864Z 
2025-09-07T10:12:46.2590954Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2591327Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2591636Z     return mod(*inputs)
2025-09-07T10:12:46.2591909Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2592234Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2592553Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2592858Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2593219Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2593562Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2593710Z 
2025-09-07T10:12:46.2593803Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2594139Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2594446Z     return mod(*inputs)
2025-09-07T10:12:46.2594724Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2595046Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2595368Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2595675Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2595783Z 
2025-09-07T10:12:46.2595875Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2596212Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2596522Z     return mod(*inputs)
2025-09-07T10:12:46.2596798Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2597119Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2597435Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2597746Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2598045Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2598386Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2598531Z 
2025-09-07T10:12:46.2598623Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2599134Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2599451Z     return mod(*inputs)
2025-09-07T10:12:46.2599734Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2600061Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2600383Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2600703Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2601014Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2601357Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2601505Z 
2025-09-07T10:12:46.2601703Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2602072Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2602400Z     return mod(*inputs)
2025-09-07T10:12:46.2602694Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 254, in forward
2025-09-07T10:12:46.2603038Z     out_dec_al = self.model_res_dec_al(out_dec)
2025-09-07T10:12:46.2603369Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2603692Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2603809Z 
2025-09-07T10:12:46.2603904Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2604331Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2604650Z     return mod(*inputs)
2025-09-07T10:12:46.2604932Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2605263Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2605397Z 
2025-09-07T10:12:46.2605498Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2605844Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2606158Z     return mod(*inputs)
2025-09-07T10:12:46.2606546Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2606885Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2607017Z 
2025-09-07T10:12:46.2607118Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2607473Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2607786Z     return mod(*inputs)
2025-09-07T10:12:46.2608069Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2608391Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2608519Z 
2025-09-07T10:12:46.2608620Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2608959Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2609277Z     return mod(*inputs)
2025-09-07T10:12:46.2609559Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2609890Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2610019Z 
2025-09-07T10:12:46.2610121Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2610465Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2610781Z     return mod(*inputs)
2025-09-07T10:12:46.2611068Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2611393Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2611524Z 
2025-09-07T10:12:46.2611617Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2611965Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2612279Z     return mod(*inputs)
2025-09-07T10:12:46.2612565Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2612887Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2613012Z 
2025-09-07T10:12:46.2613104Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2613446Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2613760Z     return mod(*inputs)
2025-09-07T10:12:46.2614047Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2614367Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2614691Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2615107Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2615255Z 
2025-09-07T10:12:46.2615358Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2615706Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2616018Z     return mod(*inputs)
2025-09-07T10:12:46.2616310Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2616635Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2616959Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2617341Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2617490Z 
2025-09-07T10:12:46.2617583Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2617927Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2618249Z     return mod(*inputs)
2025-09-07T10:12:46.2618536Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2618852Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2618985Z 
2025-09-07T10:12:46.2619141Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2619484Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2619818Z     return mod(*inputs)
2025-09-07T10:12:46.2620097Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2620444Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2620771Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2621090Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2621402Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2621741Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2621891Z 
2025-09-07T10:12:46.2621984Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2622334Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2622648Z     return mod(*inputs)
2025-09-07T10:12:46.2622932Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2623259Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2623582Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2623906Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2624016Z 
2025-09-07T10:12:46.2624114Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2624456Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2624770Z     return mod(*inputs)
2025-09-07T10:12:46.2625056Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2625381Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2625762Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2626084Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2626393Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2626735Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2626883Z 
2025-09-07T10:12:46.2626982Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2627320Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2627632Z     return mod(*inputs)
2025-09-07T10:12:46.2627968Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2628297Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2628624Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2628952Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2629249Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2629597Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2629742Z 
2025-09-07T10:12:46.2629840Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2630180Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2630549Z     return mod(*inputs)
2025-09-07T10:12:46.2630842Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2631182Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2631526Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2631836Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2631951Z 
2025-09-07T10:12:46.2632047Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2632458Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2632779Z     return mod(*inputs)
2025-09-07T10:12:46.2633056Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2633397Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2633722Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2634037Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2634145Z 
2025-09-07T10:12:46.2634251Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2634589Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2634904Z     return mod(*inputs)
2025-09-07T10:12:46.2635185Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2635537Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2635855Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2636178Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2636489Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2636842Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2636989Z 
2025-09-07T10:12:46.2637089Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2637446Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2637761Z     return mod(*inputs)
2025-09-07T10:12:46.2638043Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2638372Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2638699Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2639004Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2639117Z 
2025-09-07T10:12:46.2639209Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2639565Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2639876Z     return mod(*inputs)
2025-09-07T10:12:46.2640155Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2640484Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2640808Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2641170Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2641472Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2641813Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2641964Z 
2025-09-07T10:12:46.2642065Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2642407Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2642717Z     return mod(*inputs)
2025-09-07T10:12:46.2642996Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2643367Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2643691Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2644006Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2644302Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2644637Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2644789Z 
2025-09-07T10:12:46.2644878Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2645295Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2645631Z     return mod(*inputs)
2025-09-07T10:12:46.2645908Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 257, in forward
2025-09-07T10:12:46.2646234Z     out_dec_fg = self.model_res_dec_fg(out_dec)
2025-09-07T10:12:46.2646577Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 405, in forward
2025-09-07T10:12:46.2646900Z     out = x + self.conv_block(x)
2025-09-07T10:12:46.2647006Z 
2025-09-07T10:12:46.2647099Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2647465Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2647775Z     return mod(*inputs)
2025-09-07T10:12:46.2648055Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 258, in forward
2025-09-07T10:12:46.2648396Z     out_dec_fg1 = self.model_dec_fg1(out_dec_fg)
2025-09-07T10:12:46.2648534Z 
2025-09-07T10:12:46.2648629Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2648981Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2649293Z     return mod(*inputs)
2025-09-07T10:12:46.2649572Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 258, in forward
2025-09-07T10:12:46.2649903Z     out_dec_fg1 = self.model_dec_fg1(out_dec_fg)
2025-09-07T10:12:46.2650042Z 
2025-09-07T10:12:46.2650134Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2650475Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2650786Z     return mod(*inputs)
2025-09-07T10:12:46.2651065Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 258, in forward
2025-09-07T10:12:46.2651388Z     out_dec_fg1 = self.model_dec_fg1(out_dec_fg)
2025-09-07T10:12:46.2651527Z 
2025-09-07T10:12:46.2651620Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2651968Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2652274Z     return mod(*inputs)
2025-09-07T10:12:46.2652544Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 258, in forward
2025-09-07T10:12:46.2652873Z     out_dec_fg1 = self.model_dec_fg1(out_dec_fg)
2025-09-07T10:12:46.2653011Z 
2025-09-07T10:12:46.2653100Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2653450Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2653830Z     return mod(*inputs)
2025-09-07T10:12:46.2654110Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 259, in forward
2025-09-07T10:12:46.2654486Z     fg_out = self.model_fg_out(torch.cat([out_dec_fg1, img_feat1], dim=1))
2025-09-07T10:12:46.2654675Z 
2025-09-07T10:12:46.2654773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2655125Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2655440Z     return mod(*inputs)
2025-09-07T10:12:46.2655723Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 259, in forward
2025-09-07T10:12:46.2656136Z     fg_out = self.model_fg_out(torch.cat([out_dec_fg1, img_feat1], dim=1))
2025-09-07T10:12:46.2656316Z 
2025-09-07T10:12:46.2656421Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2656770Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2657081Z     return mod(*inputs)
2025-09-07T10:12:46.2657366Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 259, in forward
2025-09-07T10:12:46.2657733Z     fg_out = self.model_fg_out(torch.cat([out_dec_fg1, img_feat1], dim=1))
2025-09-07T10:12:46.2657912Z 
2025-09-07T10:12:46.2658300Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2658656Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2658964Z     return mod(*inputs)
2025-09-07T10:12:46.2659244Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 259, in forward
2025-09-07T10:12:46.2659623Z     fg_out = self.model_fg_out(torch.cat([out_dec_fg1, img_feat1], dim=1))
2025-09-07T10:12:46.2660005Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2660354Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2660513Z 
2025-09-07T10:12:46.2660608Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2660957Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2661278Z     return mod(*inputs)
2025-09-07T10:12:46.2661571Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 259, in forward
2025-09-07T10:12:46.2661938Z     fg_out = self.model_fg_out(torch.cat([out_dec_fg1, img_feat1], dim=1))
2025-09-07T10:12:46.2662313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/nn/functional.py", line 5294, in pad
2025-09-07T10:12:46.2662662Z     return torch._C._nn.pad(input, pad, mode, value)
2025-09-07T10:12:46.2662808Z 
2025-09-07T10:12:46.2662892Z cudagraph partition due to non gpu ops
2025-09-07T10:12:46.2663125Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2663472Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2663797Z     return mod(*inputs)
2025-09-07T10:12:46.2664082Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 255, in forward
2025-09-07T10:12:46.2664414Z     al_out = self.model_al_out(out_dec_al)
2025-09-07T10:12:46.2664545Z 
2025-09-07T10:12:46.2664640Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:12:46.2664994Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:12:46.2665311Z     return mod(*inputs)
2025-09-07T10:12:46.2665660Z   File "/torchbench/torchbenchmark/models/Background_Matting/networks.py", line 259, in forward
2025-09-07T10:12:46.2666038Z     fg_out = self.model_fg_out(torch.cat([out_dec_fg1, img_feat1], dim=1))
2025-09-07T10:12:46.2666222Z 
2025-09-07T10:13:11.2346750Z 
2025-09-07T10:13:11.6469790Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:13:12.0530658Z running benchmark:   3% 1/30 [00:00<00:11,  2.43it/s]
2025-09-07T10:13:12.4531046Z running benchmark:   7% 2/30 [00:00<00:11,  2.45it/s]
2025-09-07T10:13:12.8598379Z running benchmark:  10% 3/30 [00:01<00:10,  2.47it/s]
2025-09-07T10:13:13.2660952Z running benchmark:  13% 4/30 [00:01<00:10,  2.47it/s]
2025-09-07T10:13:13.6712759Z running benchmark:  17% 5/30 [00:02<00:10,  2.46it/s]
2025-09-07T10:13:14.0792899Z running benchmark:  20% 6/30 [00:02<00:09,  2.47it/s]
2025-09-07T10:13:14.5551271Z running benchmark:  23% 7/30 [00:02<00:09,  2.46it/s]
2025-09-07T10:13:14.9612524Z running benchmark:  27% 8/30 [00:03<00:09,  2.33it/s]
2025-09-07T10:13:15.3691308Z running benchmark:  30% 9/30 [00:03<00:08,  2.37it/s]
2025-09-07T10:13:15.7739720Z running benchmark:  33% 10/30 [00:04<00:08,  2.40it/s]
2025-09-07T10:13:16.1791538Z running benchmark:  37% 11/30 [00:04<00:07,  2.42it/s]
2025-09-07T10:13:16.5823347Z running benchmark:  40% 12/30 [00:04<00:07,  2.43it/s]
2025-09-07T10:13:16.9888591Z running benchmark:  43% 13/30 [00:05<00:06,  2.45it/s]
2025-09-07T10:13:17.3942038Z running benchmark:  47% 14/30 [00:05<00:06,  2.45it/s]
2025-09-07T10:13:17.7976621Z running benchmark:  50% 15/30 [00:06<00:06,  2.46it/s]
2025-09-07T10:13:18.1980579Z running benchmark:  53% 16/30 [00:06<00:05,  2.46it/s]
2025-09-07T10:13:18.6752675Z running benchmark:  57% 17/30 [00:06<00:05,  2.47it/s]
2025-09-07T10:13:19.0793489Z running benchmark:  60% 18/30 [00:07<00:05,  2.35it/s]
2025-09-07T10:13:19.4830739Z running benchmark:  63% 19/30 [00:07<00:04,  2.38it/s]
2025-09-07T10:13:19.8863235Z running benchmark:  67% 20/30 [00:08<00:04,  2.41it/s]
2025-09-07T10:13:20.2912551Z running benchmark:  70% 21/30 [00:08<00:03,  2.43it/s]
2025-09-07T10:13:20.6950301Z running benchmark:  73% 22/30 [00:09<00:03,  2.44it/s]
2025-09-07T10:13:21.1221275Z running benchmark:  77% 23/30 [00:09<00:02,  2.45it/s]
2025-09-07T10:13:21.5480654Z running benchmark:  80% 24/30 [00:09<00:02,  2.42it/s]
2025-09-07T10:13:21.9738818Z running benchmark:  83% 25/30 [00:10<00:02,  2.40it/s]
2025-09-07T10:13:22.4677589Z running benchmark:  87% 26/30 [00:10<00:01,  2.38it/s]
2025-09-07T10:13:22.8914542Z running benchmark:  90% 27/30 [00:11<00:01,  2.26it/s]
2025-09-07T10:13:23.3179943Z running benchmark:  93% 28/30 [00:11<00:00,  2.29it/s]
2025-09-07T10:13:23.7451961Z running benchmark:  97% 29/30 [00:12<00:00,  2.31it/s]
2025-09-07T10:13:23.7452305Z running benchmark: 100% 30/30 [00:12<00:00,  2.32it/s]
2025-09-07T10:13:23.7452625Z running benchmark: 100% 30/30 [00:12<00:00,  2.40it/s]
2025-09-07T10:13:23.8621362Z 0.876x
2025-09-07T10:13:23.8625343Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:13:26.2980620Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:13:26.2981531Z   import pynvml  # type: ignore[import]
2025-09-07T10:13:28.3161294Z 
2025-09-07T10:13:30.3786320Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:13:30.3786636Z loading model: 0it [00:02, ?it/s]
2025-09-07T10:13:30.3828807Z cpu  eval  LearningToPaint                    
2025-09-07T10:13:33.9346303Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9346615Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9346856Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9347069Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9347274Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9347472Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9347681Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9347884Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9348101Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9348313Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9348516Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9348709Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9349290Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9349507Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9349709Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9349907Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9350096Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9350296Z cudagraph partition due to non gpu ops
2025-09-07T10:13:33.9350536Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9350928Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9351266Z     return mod(*inputs)
2025-09-07T10:13:33.9351616Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 128, in forward
2025-09-07T10:13:33.9352121Z     x = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9352272Z 
2025-09-07T10:13:33.9352390Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9352767Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9353094Z     return mod(*inputs)
2025-09-07T10:13:33.9353428Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 128, in forward
2025-09-07T10:13:33.9353794Z     x = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9354105Z 
2025-09-07T10:13:33.9354216Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9354569Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9354913Z     return mod(*inputs)
2025-09-07T10:13:33.9355241Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9355593Z     x = self.layer1(x)
2025-09-07T10:13:33.9355917Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9356273Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9356418Z 
2025-09-07T10:13:33.9356518Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9356881Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9357206Z     return mod(*inputs)
2025-09-07T10:13:33.9357529Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9357880Z     x = self.layer1(x)
2025-09-07T10:13:33.9358202Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9358564Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9358697Z 
2025-09-07T10:13:33.9358799Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9359148Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9359472Z     return mod(*inputs)
2025-09-07T10:13:33.9359794Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9360161Z     x = self.layer1(x)
2025-09-07T10:13:33.9360467Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9360822Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9360953Z 
2025-09-07T10:13:33.9361056Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9361422Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9361764Z     return mod(*inputs)
2025-09-07T10:13:33.9362077Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9362425Z     x = self.layer1(x)
2025-09-07T10:13:33.9362736Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T10:13:33.9363084Z     out += self.shortcut(x)
2025-09-07T10:13:33.9363238Z 
2025-09-07T10:13:33.9363337Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9363703Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9364026Z     return mod(*inputs)
2025-09-07T10:13:33.9364351Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9364698Z     x = self.layer1(x)
2025-09-07T10:13:33.9365003Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9365369Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9365508Z 
2025-09-07T10:13:33.9365608Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9366010Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9366353Z     return mod(*inputs)
2025-09-07T10:13:33.9366676Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9367029Z     x = self.layer1(x)
2025-09-07T10:13:33.9367339Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9367691Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9367829Z 
2025-09-07T10:13:33.9367990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9368353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9368683Z     return mod(*inputs)
2025-09-07T10:13:33.9368997Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9369349Z     x = self.layer1(x)
2025-09-07T10:13:33.9369663Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9370022Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9370151Z 
2025-09-07T10:13:33.9370257Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9370603Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9370927Z     return mod(*inputs)
2025-09-07T10:13:33.9371243Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 129, in forward
2025-09-07T10:13:33.9371594Z     x = self.layer1(x)
2025-09-07T10:13:33.9371899Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T10:13:33.9372239Z     out = F.relu(out)
2025-09-07T10:13:33.9372335Z 
2025-09-07T10:13:33.9372433Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9372795Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9373109Z     return mod(*inputs)
2025-09-07T10:13:33.9381014Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9381504Z     x = self.layer2(x)
2025-09-07T10:13:33.9381889Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9382262Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9382399Z 
2025-09-07T10:13:33.9382536Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9382922Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9383248Z     return mod(*inputs)
2025-09-07T10:13:33.9383577Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9383927Z     x = self.layer2(x)
2025-09-07T10:13:33.9384252Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9384610Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9384742Z 
2025-09-07T10:13:33.9384841Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9385273Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9385665Z     return mod(*inputs)
2025-09-07T10:13:33.9385994Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9386346Z     x = self.layer2(x)
2025-09-07T10:13:33.9386679Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9387044Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9387178Z 
2025-09-07T10:13:33.9387288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9387662Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9388050Z     return mod(*inputs)
2025-09-07T10:13:33.9388381Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9388740Z     x = self.layer2(x)
2025-09-07T10:13:33.9389064Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T10:13:33.9389412Z     out += self.shortcut(x)
2025-09-07T10:13:33.9389528Z 
2025-09-07T10:13:33.9389629Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9390066Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9390402Z     return mod(*inputs)
2025-09-07T10:13:33.9390729Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9391071Z     x = self.layer2(x)
2025-09-07T10:13:33.9391388Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9391754Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9391887Z 
2025-09-07T10:13:33.9391992Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9392349Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9392675Z     return mod(*inputs)
2025-09-07T10:13:33.9392993Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9393341Z     x = self.layer2(x)
2025-09-07T10:13:33.9393657Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9394011Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9394148Z 
2025-09-07T10:13:33.9394245Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9394602Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9394930Z     return mod(*inputs)
2025-09-07T10:13:33.9395245Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9395613Z     x = self.layer2(x)
2025-09-07T10:13:33.9395936Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9396296Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9396422Z 
2025-09-07T10:13:33.9396529Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9396893Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9397218Z     return mod(*inputs)
2025-09-07T10:13:33.9397545Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 130, in forward
2025-09-07T10:13:33.9397894Z     x = self.layer2(x)
2025-09-07T10:13:33.9398201Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T10:13:33.9398550Z     out = F.relu(out)
2025-09-07T10:13:33.9398650Z 
2025-09-07T10:13:33.9398956Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9399322Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9399757Z     return mod(*inputs)
2025-09-07T10:13:33.9400077Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9400429Z     x = self.layer3(x)
2025-09-07T10:13:33.9400750Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9401117Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9401254Z 
2025-09-07T10:13:33.9401355Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9401717Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9404114Z     return mod(*inputs)
2025-09-07T10:13:33.9404446Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9404800Z     x = self.layer3(x)
2025-09-07T10:13:33.9405118Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9405478Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9405613Z 
2025-09-07T10:13:33.9405720Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9406270Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9406603Z     return mod(*inputs)
2025-09-07T10:13:33.9406930Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9407280Z     x = self.layer3(x)
2025-09-07T10:13:33.9407595Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9407955Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9408081Z 
2025-09-07T10:13:33.9408177Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9408533Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9408861Z     return mod(*inputs)
2025-09-07T10:13:33.9409183Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9409524Z     x = self.layer3(x)
2025-09-07T10:13:33.9409843Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T10:13:33.9410190Z     out += self.shortcut(x)
2025-09-07T10:13:33.9410301Z 
2025-09-07T10:13:33.9410404Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9410758Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9411076Z     return mod(*inputs)
2025-09-07T10:13:33.9411396Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9411755Z     x = self.layer3(x)
2025-09-07T10:13:33.9412071Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9412427Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9412566Z 
2025-09-07T10:13:33.9412661Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9413011Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9413339Z     return mod(*inputs)
2025-09-07T10:13:33.9413656Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9413998Z     x = self.layer3(x)
2025-09-07T10:13:33.9414302Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9414661Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9414790Z 
2025-09-07T10:13:33.9414891Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9415234Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9415601Z     return mod(*inputs)
2025-09-07T10:13:33.9415918Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9416261Z     x = self.layer3(x)
2025-09-07T10:13:33.9416567Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9416920Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9417052Z 
2025-09-07T10:13:33.9417147Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9417499Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9417824Z     return mod(*inputs)
2025-09-07T10:13:33.9418174Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 131, in forward
2025-09-07T10:13:33.9418517Z     x = self.layer3(x)
2025-09-07T10:13:33.9418824Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T10:13:33.9419167Z     out = F.relu(out)
2025-09-07T10:13:33.9419259Z 
2025-09-07T10:13:33.9419359Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9419707Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9420023Z     return mod(*inputs)
2025-09-07T10:13:33.9420403Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9420756Z     x = self.layer4(x)
2025-09-07T10:13:33.9421062Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9421434Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9421572Z 
2025-09-07T10:13:33.9421667Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9422016Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9422333Z     return mod(*inputs)
2025-09-07T10:13:33.9422652Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9422995Z     x = self.layer4(x)
2025-09-07T10:13:33.9423314Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9423671Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9423803Z 
2025-09-07T10:13:33.9423898Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9424252Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9424569Z     return mod(*inputs)
2025-09-07T10:13:33.9424887Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9425229Z     x = self.layer4(x)
2025-09-07T10:13:33.9425605Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9425963Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9426085Z 
2025-09-07T10:13:33.9426190Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9426545Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9426861Z     return mod(*inputs)
2025-09-07T10:13:33.9427179Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9427528Z     x = self.layer4(x)
2025-09-07T10:13:33.9427842Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 56, in forward
2025-09-07T10:13:33.9428186Z     out += self.shortcut(x)
2025-09-07T10:13:33.9428306Z 
2025-09-07T10:13:33.9428405Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9428771Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9429100Z     return mod(*inputs)
2025-09-07T10:13:33.9429471Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9429812Z     x = self.layer4(x)
2025-09-07T10:13:33.9430129Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9430482Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9430617Z 
2025-09-07T10:13:33.9430722Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9431071Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9431400Z     return mod(*inputs)
2025-09-07T10:13:33.9431719Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9432107Z     x = self.layer4(x)
2025-09-07T10:13:33.9432424Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 54, in forward
2025-09-07T10:13:33.9432776Z     out = F.relu(self.bn1(self.conv1(x)))
2025-09-07T10:13:33.9432911Z 
2025-09-07T10:13:33.9433007Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9433369Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9433693Z     return mod(*inputs)
2025-09-07T10:13:33.9434065Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9434418Z     x = self.layer4(x)
2025-09-07T10:13:33.9434738Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 55, in forward
2025-09-07T10:13:33.9435094Z     out = self.bn2(self.conv2(out))
2025-09-07T10:13:33.9435216Z 
2025-09-07T10:13:33.9435327Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9435678Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9435999Z     return mod(*inputs)
2025-09-07T10:13:33.9436320Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 132, in forward
2025-09-07T10:13:33.9436669Z     x = self.layer4(x)
2025-09-07T10:13:33.9436977Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 57, in forward
2025-09-07T10:13:33.9437324Z     out = F.relu(out)
2025-09-07T10:13:33.9437420Z 
2025-09-07T10:13:33.9437517Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9437872Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9438204Z     return mod(*inputs)
2025-09-07T10:13:33.9438521Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 133, in forward
2025-09-07T10:13:33.9438875Z     x = F.avg_pool2d(x, 4)
2025-09-07T10:13:33.9438992Z 
2025-09-07T10:13:33.9439094Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9439460Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9439779Z     return mod(*inputs)
2025-09-07T10:13:33.9440116Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 135, in forward
2025-09-07T10:13:33.9440458Z     x = self.fc(x)
2025-09-07T10:13:33.9440552Z 
2025-09-07T10:13:33.9440647Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:13:33.9441008Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:13:33.9441336Z     return mod(*inputs)
2025-09-07T10:13:33.9441656Z   File "/torchbench/torchbenchmark/models/LearningToPaint/baseline/DRL/actor.py", line 136, in forward
2025-09-07T10:13:33.9442001Z     x = torch.sigmoid(x)
2025-09-07T10:13:33.9442114Z 
2025-09-07T10:13:48.6427913Z 
2025-09-07T10:13:48.7660063Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:13:48.9131290Z running benchmark:   7% 2/30 [00:00<00:01, 16.30it/s]
2025-09-07T10:13:49.0571630Z running benchmark:  17% 5/30 [00:00<00:01, 18.88it/s]
2025-09-07T10:13:49.2017701Z running benchmark:  27% 8/30 [00:00<00:01, 19.79it/s]
2025-09-07T10:13:49.3487080Z running benchmark:  37% 11/30 [00:00<00:00, 20.18it/s]
2025-09-07T10:13:49.4950020Z running benchmark:  47% 14/30 [00:00<00:00, 20.26it/s]
2025-09-07T10:13:49.6392386Z running benchmark:  57% 17/30 [00:00<00:00, 20.35it/s]
2025-09-07T10:13:49.7827893Z running benchmark:  67% 20/30 [00:00<00:00, 20.50it/s]
2025-09-07T10:13:49.9299119Z running benchmark:  77% 23/30 [00:01<00:00, 20.62it/s]
2025-09-07T10:13:50.0739107Z running benchmark:  87% 26/30 [00:01<00:00, 20.55it/s]
2025-09-07T10:13:50.1217290Z running benchmark:  97% 29/30 [00:01<00:00, 20.64it/s]
2025-09-07T10:13:50.1217628Z running benchmark: 100% 30/30 [00:01<00:00, 20.29it/s]
2025-09-07T10:13:50.2101745Z 1.170x
2025-09-07T10:13:50.2104232Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:13:52.4723517Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:13:52.4724542Z   import pynvml  # type: ignore[import]
2025-09-07T10:13:54.4964903Z 
2025-09-07T10:13:55.9709985Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T10:13:56.5201323Z 
2025-09-07T10:13:56.5201706Z loading model: 0it [00:02, ?it/s]
2025-09-07T10:13:56.5202124Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T10:13:56.5202475Z cpu  eval  Super_SloMo                        
2025-09-07T10:13:56.5202853Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T10:14:10.3444481Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3444778Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3445048Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3445438Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3445777Z     return mod(*inputs)
2025-09-07T10:14:10.3446083Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3446448Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3446800Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3447185Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3447342Z 
2025-09-07T10:14:10.3447455Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3447830Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3448159Z     return mod(*inputs)
2025-09-07T10:14:10.3448455Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3448813Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3449163Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3449505Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3449663Z 
2025-09-07T10:14:10.3449768Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3450132Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3450472Z     return mod(*inputs)
2025-09-07T10:14:10.3450757Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3451094Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3451434Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3451779Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3452237Z 
2025-09-07T10:14:10.3452343Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3452697Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3453020Z     return mod(*inputs)
2025-09-07T10:14:10.3453310Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3453660Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3453991Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3454330Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3454588Z 
2025-09-07T10:14:10.3454685Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3455041Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3455366Z     return mod(*inputs)
2025-09-07T10:14:10.3455650Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3455997Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3456325Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3456635Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3457059Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3457391Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3457542Z 
2025-09-07T10:14:10.3457640Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3457996Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3458322Z     return mod(*inputs)
2025-09-07T10:14:10.3458600Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3458940Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3459264Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3459568Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3459837Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3460163Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3460315Z 
2025-09-07T10:14:10.3460411Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3460762Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3461081Z     return mod(*inputs)
2025-09-07T10:14:10.3461362Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3461692Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3462023Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3462339Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3462667Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3463013Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3463174Z 
2025-09-07T10:14:10.3463276Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3463631Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3463959Z     return mod(*inputs)
2025-09-07T10:14:10.3464242Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3464690Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3465024Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3465339Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3465668Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3466063Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3466229Z 
2025-09-07T10:14:10.3466331Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3466703Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3467057Z     return mod(*inputs)
2025-09-07T10:14:10.3467355Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3467698Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3468034Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3468436Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3468709Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3469046Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3469203Z 
2025-09-07T10:14:10.3469304Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3469663Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3469991Z     return mod(*inputs)
2025-09-07T10:14:10.3470395Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3470738Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3471071Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3471383Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3471655Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3471983Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3472134Z 
2025-09-07T10:14:10.3472232Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3472598Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3472932Z     return mod(*inputs)
2025-09-07T10:14:10.3473224Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3473561Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3473897Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3474218Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3474500Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3474826Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3474979Z 
2025-09-07T10:14:10.3475078Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3475441Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3475770Z     return mod(*inputs)
2025-09-07T10:14:10.3476053Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3476385Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3476719Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3477024Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3477303Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3477633Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3477786Z 
2025-09-07T10:14:10.3477880Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3478239Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3478567Z     return mod(*inputs)
2025-09-07T10:14:10.3478845Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3479240Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3479584Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3479885Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3480154Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3480496Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3480651Z 
2025-09-07T10:14:10.3480749Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3481100Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3481442Z     return mod(*inputs)
2025-09-07T10:14:10.3481724Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3482127Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3482448Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3482766Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3483042Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3483367Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3483514Z 
2025-09-07T10:14:10.3483689Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3484051Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3484370Z     return mod(*inputs)
2025-09-07T10:14:10.3484654Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3484993Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3485321Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3485632Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3485906Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3486237Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3486380Z 
2025-09-07T10:14:10.3486478Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3486877Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3487209Z     return mod(*inputs)
2025-09-07T10:14:10.3487489Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3487825Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3488146Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3488451Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3488731Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3489061Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3489210Z 
2025-09-07T10:14:10.3489305Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3489650Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3489975Z     return mod(*inputs)
2025-09-07T10:14:10.3490259Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3490595Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3490913Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3491214Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3491479Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3491810Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3491954Z 
2025-09-07T10:14:10.3492050Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3492414Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3492789Z     return mod(*inputs)
2025-09-07T10:14:10.3493066Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3493404Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3493725Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3494029Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3494301Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3494630Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3494776Z 
2025-09-07T10:14:10.3494913Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3495274Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3495598Z     return mod(*inputs)
2025-09-07T10:14:10.3495878Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3496231Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3496558Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3496863Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3497235Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3497575Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3497722Z 
2025-09-07T10:14:10.3497819Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3498169Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3498492Z     return mod(*inputs)
2025-09-07T10:14:10.3498954Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3499294Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3499617Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3499921Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3500193Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3500523Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3500669Z 
2025-09-07T10:14:10.3500767Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3501124Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3501444Z     return mod(*inputs)
2025-09-07T10:14:10.3501717Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3502049Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3502368Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3502670Z     x = self.down5(s5)
2025-09-07T10:14:10.3502944Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3503272Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3503417Z 
2025-09-07T10:14:10.3503516Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3503871Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3504186Z     return mod(*inputs)
2025-09-07T10:14:10.3504464Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3504796Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3505120Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3505426Z     x = self.down5(s5)
2025-09-07T10:14:10.3505770Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3506190Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3506337Z 
2025-09-07T10:14:10.3506436Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3506792Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3507121Z     return mod(*inputs)
2025-09-07T10:14:10.3507402Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3507740Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3508066Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3508432Z     x = self.down5(s5)
2025-09-07T10:14:10.3508715Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3509054Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3509203Z 
2025-09-07T10:14:10.3509299Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3509664Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3509989Z     return mod(*inputs)
2025-09-07T10:14:10.3510376Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3510720Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3511041Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3511349Z     x = self.down5(s5)
2025-09-07T10:14:10.3511629Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3511964Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3512107Z 
2025-09-07T10:14:10.3512202Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3512563Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3512889Z     return mod(*inputs)
2025-09-07T10:14:10.3513168Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3513504Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3513830Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3514135Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3514413Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3514744Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3514887Z 
2025-09-07T10:14:10.3514987Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3515335Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3515660Z     return mod(*inputs)
2025-09-07T10:14:10.3515940Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3516277Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3516596Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3516900Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3517175Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3517504Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3517647Z 
2025-09-07T10:14:10.3517743Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3518097Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3518423Z     return mod(*inputs)
2025-09-07T10:14:10.3518701Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3519041Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3519413Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3519716Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3519988Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3520372Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3520570Z 
2025-09-07T10:14:10.3520666Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3521020Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3521343Z     return mod(*inputs)
2025-09-07T10:14:10.3521692Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3522034Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3522364Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3522668Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3522944Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3523319Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3523513Z 
2025-09-07T10:14:10.3523681Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3524036Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3524360Z     return mod(*inputs)
2025-09-07T10:14:10.3524641Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3524980Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3525304Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3525609Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3525883Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3526218Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3526367Z 
2025-09-07T10:14:10.3526465Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3526826Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3527150Z     return mod(*inputs)
2025-09-07T10:14:10.3527425Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3527762Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3528079Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3528385Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3528658Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3528982Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3529127Z 
2025-09-07T10:14:10.3529226Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3529593Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3529924Z     return mod(*inputs)
2025-09-07T10:14:10.3530218Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3530565Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3530899Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3531209Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3531490Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3531870Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3532067Z 
2025-09-07T10:14:10.3532172Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3532604Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3532931Z     return mod(*inputs)
2025-09-07T10:14:10.3533214Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3533558Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3533886Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3534193Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3534470Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3534849Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3535085Z 
2025-09-07T10:14:10.3535185Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3535547Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3535875Z     return mod(*inputs)
2025-09-07T10:14:10.3536157Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3536495Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3536900Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3537211Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3537484Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3537816Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3537963Z 
2025-09-07T10:14:10.3538067Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3538424Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3538747Z     return mod(*inputs)
2025-09-07T10:14:10.3539031Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3539367Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3539689Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3539992Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3540265Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3540601Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3540749Z 
2025-09-07T10:14:10.3540846Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3541193Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3541521Z     return mod(*inputs)
2025-09-07T10:14:10.3541801Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3542134Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3542468Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3542776Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3543048Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3543423Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3543617Z 
2025-09-07T10:14:10.3543715Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3544072Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3544399Z     return mod(*inputs)
2025-09-07T10:14:10.3544680Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3545022Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3545347Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3545770Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3546048Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3546431Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3546622Z 
2025-09-07T10:14:10.3546721Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3547074Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3547398Z     return mod(*inputs)
2025-09-07T10:14:10.3547680Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3548021Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3548413Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3548720Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3548993Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3549325Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3549472Z 
2025-09-07T10:14:10.3549572Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3549927Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3550328Z     return mod(*inputs)
2025-09-07T10:14:10.3550614Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3550951Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3551275Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3551582Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3551858Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3552187Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3552334Z 
2025-09-07T10:14:10.3552432Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3552787Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3553113Z     return mod(*inputs)
2025-09-07T10:14:10.3553395Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3553738Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3554065Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3554368Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3554640Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3555019Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3555212Z 
2025-09-07T10:14:10.3555309Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3555667Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3555992Z     return mod(*inputs)
2025-09-07T10:14:10.3556276Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3556622Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3556946Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3557249Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3557523Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3557901Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3558096Z 
2025-09-07T10:14:10.3558194Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3558545Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3558916Z     return mod(*inputs)
2025-09-07T10:14:10.3559199Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3559533Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3559861Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3560170Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3560444Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3560775Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3560924Z 
2025-09-07T10:14:10.3561022Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3561382Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3561753Z     return mod(*inputs)
2025-09-07T10:14:10.3562033Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3562378Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3562701Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3563006Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3563278Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3563680Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3563829Z 
2025-09-07T10:14:10.3563928Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3564297Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3564620Z     return mod(*inputs)
2025-09-07T10:14:10.3564903Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3565238Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3565566Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3565876Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3566149Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3566520Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3566710Z 
2025-09-07T10:14:10.3566814Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3567168Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3567494Z     return mod(*inputs)
2025-09-07T10:14:10.3567773Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3568110Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3568432Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3568737Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3569018Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3569394Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3569582Z 
2025-09-07T10:14:10.3569685Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3570037Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3570357Z     return mod(*inputs)
2025-09-07T10:14:10.3570642Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3570980Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3571302Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T10:14:10.3571629Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T10:14:10.3571780Z 
2025-09-07T10:14:10.3571879Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3572279Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3572599Z     return mod(*inputs)
2025-09-07T10:14:10.3572875Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3573213Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3573548Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T10:14:10.3573877Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T10:14:10.3574018Z 
2025-09-07T10:14:10.3574103Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3574321Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3574595Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3574961Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3575280Z     return mod(*inputs)
2025-09-07T10:14:10.3575569Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3575902Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3576218Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3576622Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3576773Z 
2025-09-07T10:14:10.3576872Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3577230Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3577552Z     return mod(*inputs)
2025-09-07T10:14:10.3577837Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3578158Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3578472Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3578799Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3578945Z 
2025-09-07T10:14:10.3579054Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3579408Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3579721Z     return mod(*inputs)
2025-09-07T10:14:10.3580004Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3580325Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3580636Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3580974Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3581135Z 
2025-09-07T10:14:10.3581235Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3581592Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3581918Z     return mod(*inputs)
2025-09-07T10:14:10.3582205Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3582523Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3582829Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3583162Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3583309Z 
2025-09-07T10:14:10.3583412Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3583768Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3584087Z     return mod(*inputs)
2025-09-07T10:14:10.3584370Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3584698Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3585001Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3585351Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3585717Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3586049Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3586196Z 
2025-09-07T10:14:10.3586300Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3586655Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3586980Z     return mod(*inputs)
2025-09-07T10:14:10.3587263Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3587592Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3587945Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3588248Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3588518Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3588850Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3588997Z 
2025-09-07T10:14:10.3589107Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3589461Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3589787Z     return mod(*inputs)
2025-09-07T10:14:10.3590192Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3590525Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3590834Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3591135Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3591418Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3591753Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3591902Z 
2025-09-07T10:14:10.3592010Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3592356Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3592682Z     return mod(*inputs)
2025-09-07T10:14:10.3592965Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3593293Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3593608Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3593912Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3594185Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3594518Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3594667Z 
2025-09-07T10:14:10.3594773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3595127Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3595453Z     return mod(*inputs)
2025-09-07T10:14:10.3595738Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3596063Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3596385Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3596689Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3596965Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3597296Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3597441Z 
2025-09-07T10:14:10.3597546Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3597895Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3598222Z     return mod(*inputs)
2025-09-07T10:14:10.3598503Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3599002Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3599307Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3611204Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3611533Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3611903Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3612069Z 
2025-09-07T10:14:10.3612181Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3612550Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3612888Z     return mod(*inputs)
2025-09-07T10:14:10.3613304Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3613642Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3613969Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3614287Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3614569Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3614897Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3615058Z 
2025-09-07T10:14:10.3615160Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3615630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3615973Z     return mod(*inputs)
2025-09-07T10:14:10.3616266Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3616600Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3616924Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3617234Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3617511Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3617841Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3617997Z 
2025-09-07T10:14:10.3618098Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3618460Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3618788Z     return mod(*inputs)
2025-09-07T10:14:10.3619063Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3619388Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3619700Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3620008Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3620284Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3620606Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3620757Z 
2025-09-07T10:14:10.3620853Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3621209Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3621533Z     return mod(*inputs)
2025-09-07T10:14:10.3621807Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3622134Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3622445Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3622754Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3623029Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3623352Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3623505Z 
2025-09-07T10:14:10.3623601Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3623953Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3624347Z     return mod(*inputs)
2025-09-07T10:14:10.3624621Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3624945Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3625248Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3625641Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3625917Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3626235Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3626385Z 
2025-09-07T10:14:10.3626486Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3626881Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3627202Z     return mod(*inputs)
2025-09-07T10:14:10.3627472Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3627793Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3628099Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3628395Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3628658Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3629039Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3629191Z 
2025-09-07T10:14:10.3629288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3629635Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3629954Z     return mod(*inputs)
2025-09-07T10:14:10.3630226Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3630545Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3630852Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3631157Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3631423Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3631748Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3631899Z 
2025-09-07T10:14:10.3631998Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3632353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3632679Z     return mod(*inputs)
2025-09-07T10:14:10.3632946Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3633268Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3633573Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3633877Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3634141Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3634478Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3634630Z 
2025-09-07T10:14:10.3634723Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3635073Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3635395Z     return mod(*inputs)
2025-09-07T10:14:10.3635669Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3635988Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3636290Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3636598Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3636859Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3637183Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3637375Z 
2025-09-07T10:14:10.3637471Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3637819Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3638139Z     return mod(*inputs)
2025-09-07T10:14:10.3638402Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3638721Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3639024Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3639328Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3639588Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3639951Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3640104Z 
2025-09-07T10:14:10.3640201Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3640554Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3640876Z     return mod(*inputs)
2025-09-07T10:14:10.3641140Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3641460Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3641817Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3642126Z     x = self.down5(s5)
2025-09-07T10:14:10.3642396Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3642719Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3642868Z 
2025-09-07T10:14:10.3642965Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3643318Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3643637Z     return mod(*inputs)
2025-09-07T10:14:10.3643904Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3644225Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3644531Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3644832Z     x = self.down5(s5)
2025-09-07T10:14:10.3645103Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3645431Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3645583Z 
2025-09-07T10:14:10.3645677Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3646026Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3646350Z     return mod(*inputs)
2025-09-07T10:14:10.3646619Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3646933Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3647234Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3647540Z     x = self.down5(s5)
2025-09-07T10:14:10.3647804Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3648135Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3648288Z 
2025-09-07T10:14:10.3648385Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3648732Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3649051Z     return mod(*inputs)
2025-09-07T10:14:10.3649316Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3649632Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3649938Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3650238Z     x = self.down5(s5)
2025-09-07T10:14:10.3650545Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3650866Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3651016Z 
2025-09-07T10:14:10.3651112Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3651467Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3651782Z     return mod(*inputs)
2025-09-07T10:14:10.3652059Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3652379Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3652683Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3653028Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3653291Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3653617Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3653767Z 
2025-09-07T10:14:10.3653860Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3654216Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3654530Z     return mod(*inputs)
2025-09-07T10:14:10.3654884Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3655203Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3655509Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3655811Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3656070Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3656398Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3656551Z 
2025-09-07T10:14:10.3656644Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3656992Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3657309Z     return mod(*inputs)
2025-09-07T10:14:10.3657589Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3657907Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3658210Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3658513Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3658780Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3659158Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3659358Z 
2025-09-07T10:14:10.3659455Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3659808Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3660124Z     return mod(*inputs)
2025-09-07T10:14:10.3660405Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3660729Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3661023Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3661312Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3661573Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3661936Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3662128Z 
2025-09-07T10:14:10.3662224Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3662560Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3662872Z     return mod(*inputs)
2025-09-07T10:14:10.3663143Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3663505Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3663802Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3664092Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3664355Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3664676Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3664819Z 
2025-09-07T10:14:10.3664912Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3665251Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3665626Z     return mod(*inputs)
2025-09-07T10:14:10.3665896Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3666250Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3666543Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3666833Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3667093Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3667414Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3667559Z 
2025-09-07T10:14:10.3667656Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3668067Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3668388Z     return mod(*inputs)
2025-09-07T10:14:10.3668664Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3668983Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3669284Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3669576Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3669839Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3670212Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3670399Z 
2025-09-07T10:14:10.3670498Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3670839Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3671153Z     return mod(*inputs)
2025-09-07T10:14:10.3671427Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3671737Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3672032Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3672328Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3672593Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3672950Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3673140Z 
2025-09-07T10:14:10.3673238Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3673578Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3673890Z     return mod(*inputs)
2025-09-07T10:14:10.3674161Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3674476Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3674767Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3675057Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3675316Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3675636Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3675777Z 
2025-09-07T10:14:10.3675873Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3676218Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3676579Z     return mod(*inputs)
2025-09-07T10:14:10.3676847Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3677156Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3677454Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3677747Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3678009Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3678330Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3678473Z 
2025-09-07T10:14:10.3678571Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3678951Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3679266Z     return mod(*inputs)
2025-09-07T10:14:10.3679539Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3679854Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3680143Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3680438Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3680756Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3681123Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3681312Z 
2025-09-07T10:14:10.3681411Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3681752Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3682066Z     return mod(*inputs)
2025-09-07T10:14:10.3682335Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3682648Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3682940Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3683235Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3683491Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3683855Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3684037Z 
2025-09-07T10:14:10.3684137Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3684477Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3684787Z     return mod(*inputs)
2025-09-07T10:14:10.3685056Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3685368Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3685662Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3685958Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3686219Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3686536Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3686678Z 
2025-09-07T10:14:10.3686770Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3687114Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3687423Z     return mod(*inputs)
2025-09-07T10:14:10.3687686Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3687998Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3688286Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3688580Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3688859Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3689223Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3689366Z 
2025-09-07T10:14:10.3689464Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3689807Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3690121Z     return mod(*inputs)
2025-09-07T10:14:10.3690394Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3690706Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3690999Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3691292Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3691554Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3691959Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3692150Z 
2025-09-07T10:14:10.3692247Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3692589Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3692903Z     return mod(*inputs)
2025-09-07T10:14:10.3693173Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3693544Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3693833Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3694130Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3694390Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3694749Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3694937Z 
2025-09-07T10:14:10.3695031Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3695360Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3695669Z     return mod(*inputs)
2025-09-07T10:14:10.3695934Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3696244Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3696533Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3696828Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3697082Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3697404Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3697559Z 
2025-09-07T10:14:10.3697660Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3698016Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3698333Z     return mod(*inputs)
2025-09-07T10:14:10.3698609Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3699094Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3699397Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3699701Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3699972Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3700300Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3700445Z 
2025-09-07T10:14:10.3700542Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3700890Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3701202Z     return mod(*inputs)
2025-09-07T10:14:10.3701480Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3701792Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3702084Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3702456Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3702727Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3703101Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3703296Z 
2025-09-07T10:14:10.3703401Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3703748Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3704065Z     return mod(*inputs)
2025-09-07T10:14:10.3704343Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3704719Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3705015Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3705315Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3705621Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3705987Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3706177Z 
2025-09-07T10:14:10.3706278Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3706732Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3707062Z     return mod(*inputs)
2025-09-07T10:14:10.3707347Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3707666Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3707969Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T10:14:10.3708306Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T10:14:10.3708460Z 
2025-09-07T10:14:10.3708558Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3708904Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3709221Z     return mod(*inputs)
2025-09-07T10:14:10.3709492Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3709812Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3710121Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T10:14:10.3710444Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T10:14:10.3710588Z 
2025-09-07T10:14:10.3710681Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3711032Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3711349Z     return mod(*inputs)
2025-09-07T10:14:10.3711620Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3711951Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3712099Z 
2025-09-07T10:14:10.3712192Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3712531Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3712839Z     return mod(*inputs)
2025-09-07T10:14:10.3713110Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3713432Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3713750Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3714073Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3714215Z 
2025-09-07T10:14:10.3714314Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3714657Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3714968Z     return mod(*inputs)
2025-09-07T10:14:10.3715290Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3715618Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3715937Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3716269Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3716422Z 
2025-09-07T10:14:10.3716515Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3716853Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3717187Z     return mod(*inputs)
2025-09-07T10:14:10.3717453Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3718098Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3718423Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3718770Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3718915Z 
2025-09-07T10:14:10.3719021Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3719369Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3719678Z     return mod(*inputs)
2025-09-07T10:14:10.3720025Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3720367Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3720691Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3721037Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3721195Z 
2025-09-07T10:14:10.3721416Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3721781Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3722096Z     return mod(*inputs)
2025-09-07T10:14:10.3722365Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3722688Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3723032Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3723343Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3723624Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3723947Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3724055Z 
2025-09-07T10:14:10.3724154Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3724513Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3724830Z     return mod(*inputs)
2025-09-07T10:14:10.3725117Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3725453Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3725793Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3726092Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3726384Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3726706Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3726855Z 
2025-09-07T10:14:10.3726949Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3727297Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3727618Z     return mod(*inputs)
2025-09-07T10:14:10.3727892Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3728217Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3728541Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3728886Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3729170Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3729484Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3729628Z 
2025-09-07T10:14:10.3729722Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3730067Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3730385Z     return mod(*inputs)
2025-09-07T10:14:10.3730676Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3731037Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3731361Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3731656Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3731921Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3732253Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3732402Z 
2025-09-07T10:14:10.3732495Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3732905Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3733235Z     return mod(*inputs)
2025-09-07T10:14:10.3733502Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3733825Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3734149Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3734455Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3734727Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3735028Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3735137Z 
2025-09-07T10:14:10.3735237Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3735590Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3735907Z     return mod(*inputs)
2025-09-07T10:14:10.3736189Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3736519Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3736843Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3737141Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3737405Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3737727Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3737873Z 
2025-09-07T10:14:10.3737970Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3738319Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3738633Z     return mod(*inputs)
2025-09-07T10:14:10.3738903Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3739235Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3739558Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3739847Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3740115Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3740436Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3740583Z 
2025-09-07T10:14:10.3740675Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3741023Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3741332Z     return mod(*inputs)
2025-09-07T10:14:10.3741642Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3741971Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3742291Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3742592Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3742858Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3743175Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3743324Z 
2025-09-07T10:14:10.3743419Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3743757Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3744135Z     return mod(*inputs)
2025-09-07T10:14:10.3744406Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3744744Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3745071Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3745385Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3745695Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3746056Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3746166Z 
2025-09-07T10:14:10.3746259Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3746611Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3746922Z     return mod(*inputs)
2025-09-07T10:14:10.3747195Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3747533Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3747859Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3748159Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3748432Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3748758Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3748907Z 
2025-09-07T10:14:10.3749001Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3749353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3749674Z     return mod(*inputs)
2025-09-07T10:14:10.3749946Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3750277Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3750603Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3750911Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3751177Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3751496Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3751642Z 
2025-09-07T10:14:10.3751738Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3752086Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3752404Z     return mod(*inputs)
2025-09-07T10:14:10.3752670Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3753000Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3753321Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3753624Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3753888Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3754202Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3754351Z 
2025-09-07T10:14:10.3754484Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3754830Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3755142Z     return mod(*inputs)
2025-09-07T10:14:10.3755407Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3755735Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3756056Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3756354Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3756617Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3756976Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3757082Z 
2025-09-07T10:14:10.3757178Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3757525Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3757845Z     return mod(*inputs)
2025-09-07T10:14:10.3758111Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3758442Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3758824Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3759127Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3759392Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3759710Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3759855Z 
2025-09-07T10:14:10.3759953Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3760301Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3760613Z     return mod(*inputs)
2025-09-07T10:14:10.3760879Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3761209Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3761530Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3761830Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3762098Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3762415Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3762560Z 
2025-09-07T10:14:10.3762654Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3762998Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3763317Z     return mod(*inputs)
2025-09-07T10:14:10.3763589Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3763915Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3764245Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3764539Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3764806Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3765132Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3765286Z 
2025-09-07T10:14:10.3765385Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3765739Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3766059Z     return mod(*inputs)
2025-09-07T10:14:10.3766336Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3766672Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3767000Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3767298Z     x = self.down5(s5)
2025-09-07T10:14:10.3767614Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3767913Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3768020Z 
2025-09-07T10:14:10.3768115Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3768468Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3768780Z     return mod(*inputs)
2025-09-07T10:14:10.3769050Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3769378Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3769701Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3770042Z     x = self.down5(s5)
2025-09-07T10:14:10.3770304Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3770627Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3770779Z 
2025-09-07T10:14:10.3770871Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3771216Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3771531Z     return mod(*inputs)
2025-09-07T10:14:10.3771861Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3772192Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3772515Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3772813Z     x = self.down5(s5)
2025-09-07T10:14:10.3773076Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3773414Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3773566Z 
2025-09-07T10:14:10.3773661Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3774017Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3774340Z     return mod(*inputs)
2025-09-07T10:14:10.3774611Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3774950Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3775278Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3775575Z     x = self.down5(s5)
2025-09-07T10:14:10.3775838Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3776166Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3776321Z 
2025-09-07T10:14:10.3776416Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3776769Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3777095Z     return mod(*inputs)
2025-09-07T10:14:10.3777364Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3777461Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3777641Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3777709Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3777887Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3777972Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3777975Z 
2025-09-07T10:14:10.3778078Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3778276Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3778341Z     return mod(*inputs)
2025-09-07T10:14:10.3778522Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3778651Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3778834Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3778894Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3779081Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3779166Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3779169Z 
2025-09-07T10:14:10.3779273Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3779470Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3779529Z     return mod(*inputs)
2025-09-07T10:14:10.3779752Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3779838Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3780019Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3780081Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3780255Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3780347Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3780351Z 
2025-09-07T10:14:10.3780507Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3780712Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3780773Z     return mod(*inputs)
2025-09-07T10:14:10.3780955Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3781052Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3781224Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3781291Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3781464Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3781598Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3781609Z 
2025-09-07T10:14:10.3781689Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3781783Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3781989Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3782051Z     return mod(*inputs)
2025-09-07T10:14:10.3782241Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3782326Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3782503Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3782577Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3782750Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3782894Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3782897Z 
2025-09-07T10:14:10.3782993Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3783188Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3783256Z     return mod(*inputs)
2025-09-07T10:14:10.3783437Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3783528Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3783704Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3783763Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3783944Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3784031Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3784071Z 
2025-09-07T10:14:10.3784173Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3784364Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3784424Z     return mod(*inputs)
2025-09-07T10:14:10.3784618Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3784706Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3784887Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3784947Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3785131Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3785251Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3785254Z 
2025-09-07T10:14:10.3785349Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3785617Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3785680Z     return mod(*inputs)
2025-09-07T10:14:10.3785865Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3785952Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3786195Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3786268Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3786449Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3786544Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3786549Z 
2025-09-07T10:14:10.3786642Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3786844Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3786911Z     return mod(*inputs)
2025-09-07T10:14:10.3787092Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3787190Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3787365Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3787422Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3787600Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3787727Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3787730Z 
2025-09-07T10:14:10.3787811Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3787906Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3788101Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3788161Z     return mod(*inputs)
2025-09-07T10:14:10.3788339Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3788432Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3788604Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3788678Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3788854Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3788982Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3788985Z 
2025-09-07T10:14:10.3789080Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3789268Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3789333Z     return mod(*inputs)
2025-09-07T10:14:10.3789508Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3789594Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3789837Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3789895Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3790071Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3790159Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3790162Z 
2025-09-07T10:14:10.3790256Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3790439Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3790499Z     return mod(*inputs)
2025-09-07T10:14:10.3790678Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3790800Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3790975Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3791034Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3791206Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3791318Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3791322Z 
2025-09-07T10:14:10.3791416Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3791692Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3791751Z     return mod(*inputs)
2025-09-07T10:14:10.3791929Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3792017Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3792190Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3792259Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3792433Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3792520Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3792523Z 
2025-09-07T10:14:10.3792617Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3792806Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3792871Z     return mod(*inputs)
2025-09-07T10:14:10.3793047Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3793131Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3793306Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3793364Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3793544Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3793672Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3793677Z 
2025-09-07T10:14:10.3793753Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3793848Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3794035Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3794096Z     return mod(*inputs)
2025-09-07T10:14:10.3794279Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3794367Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3794543Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3794601Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3794779Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3794906Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3794909Z 
2025-09-07T10:14:10.3795041Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3795233Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3795295Z     return mod(*inputs)
2025-09-07T10:14:10.3795480Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3795565Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3795744Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3795803Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3795975Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3796098Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3796101Z 
2025-09-07T10:14:10.3796194Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3796393Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3796458Z     return mod(*inputs)
2025-09-07T10:14:10.3796641Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3796724Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3796957Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3797025Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3797196Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3797285Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3797288Z 
2025-09-07T10:14:10.3797382Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3797573Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3797639Z     return mod(*inputs)
2025-09-07T10:14:10.3797815Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3797914Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3798090Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3798146Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3798327Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3798409Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3798412Z 
2025-09-07T10:14:10.3798504Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3798697Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3798884Z     return mod(*inputs)
2025-09-07T10:14:10.3799064Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3799148Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3799324Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3799383Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3799564Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3799697Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3799701Z 
2025-09-07T10:14:10.3799773Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3799871Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3800064Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3800125Z     return mod(*inputs)
2025-09-07T10:14:10.3800303Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3800386Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3800563Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3800712Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3800888Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3801014Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3801018Z 
2025-09-07T10:14:10.3801115Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3801308Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3801366Z     return mod(*inputs)
2025-09-07T10:14:10.3801547Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3801678Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3801853Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3801913Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3802088Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3802175Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3802179Z 
2025-09-07T10:14:10.3802277Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3802567Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3802626Z     return mod(*inputs)
2025-09-07T10:14:10.3802804Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3802892Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3803066Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3803129Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3803296Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3803381Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3803385Z 
2025-09-07T10:14:10.3803486Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3803678Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3803745Z     return mod(*inputs)
2025-09-07T10:14:10.3803928Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3804019Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3804213Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3804312Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3804317Z 
2025-09-07T10:14:10.3804431Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3804634Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3804710Z     return mod(*inputs)
2025-09-07T10:14:10.3804890Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3804974Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3805153Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3805213Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3805389Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3805518Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3805521Z 
2025-09-07T10:14:10.3805594Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3805696Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3805887Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3805951Z     return mod(*inputs)
2025-09-07T10:14:10.3806166Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3806253Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3806429Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3806488Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3806678Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3806807Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3806810Z 
2025-09-07T10:14:10.3806921Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3807116Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3807209Z     return mod(*inputs)
2025-09-07T10:14:10.3807393Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3807478Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3807654Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3807713Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3807886Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3808099Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3808102Z 
2025-09-07T10:14:10.3808214Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3808414Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3808471Z     return mod(*inputs)
2025-09-07T10:14:10.3808653Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 31, in forward
2025-09-07T10:14:10.3808740Z     flowOut = self.flowComp(torch.cat((I0, I1), dim=1))
2025-09-07T10:14:10.3808910Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T10:14:10.3809000Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T10:14:10.3809003Z 
2025-09-07T10:14:10.3809096Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3809282Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3809361Z     return mod(*inputs)
2025-09-07T10:14:10.3809559Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 45, in forward
2025-09-07T10:14:10.3809657Z     g_I1_F_t_1 = self.trainFlowBackWarp(I1, F_t_1)
2025-09-07T10:14:10.3809829Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T10:14:10.3809903Z     grid = torch.stack((x, y), dim=3)
2025-09-07T10:14:10.3809907Z 
2025-09-07T10:14:10.3810001Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3810210Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3810277Z     return mod(*inputs)
2025-09-07T10:14:10.3810454Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 44, in forward
2025-09-07T10:14:10.3810542Z     g_I0_F_t_0 = self.trainFlowBackWarp(I0, F_t_0)
2025-09-07T10:14:10.3810726Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T10:14:10.3810798Z     grid = torch.stack((x, y), dim=3)
2025-09-07T10:14:10.3810801Z 
2025-09-07T10:14:10.3810898Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3811088Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3811153Z     return mod(*inputs)
2025-09-07T10:14:10.3811333Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 49, in forward
2025-09-07T10:14:10.3811391Z     torch.cat(
2025-09-07T10:14:10.3811394Z 
2025-09-07T10:14:10.3811502Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3811744Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3811808Z     return mod(*inputs)
2025-09-07T10:14:10.3811985Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 49, in forward
2025-09-07T10:14:10.3812040Z     torch.cat(
2025-09-07T10:14:10.3812062Z 
2025-09-07T10:14:10.3812145Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3812216Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3812315Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3812508Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3812607Z     return mod(*inputs)
2025-09-07T10:14:10.3812787Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 49, in forward
2025-09-07T10:14:10.3812843Z     torch.cat(
2025-09-07T10:14:10.3812846Z 
2025-09-07T10:14:10.3812944Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3813135Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3813209Z     return mod(*inputs)
2025-09-07T10:14:10.3813383Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3813523Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3813705Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3813791Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3813794Z 
2025-09-07T10:14:10.3813895Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3814088Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3814148Z     return mod(*inputs)
2025-09-07T10:14:10.3814328Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3814402Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3814592Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3814679Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3814682Z 
2025-09-07T10:14:10.3814773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3814980Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3815039Z     return mod(*inputs)
2025-09-07T10:14:10.3815221Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3815292Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3815471Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 197, in forward
2025-09-07T10:14:10.3815559Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3815562Z 
2025-09-07T10:14:10.3815656Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3815858Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3815921Z     return mod(*inputs)
2025-09-07T10:14:10.3816104Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3816180Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3816354Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3816450Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3816453Z 
2025-09-07T10:14:10.3816545Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3816741Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3816809Z     return mod(*inputs)
2025-09-07T10:14:10.3816988Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3817109Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3817285Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3817349Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3817526Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3817592Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3817601Z 
2025-09-07T10:14:10.3817695Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3817889Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3817955Z     return mod(*inputs)
2025-09-07T10:14:10.3818175Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3818251Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3818425Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3818494Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3818678Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3818763Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3818767Z 
2025-09-07T10:14:10.3818865Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3819117Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3819179Z     return mod(*inputs)
2025-09-07T10:14:10.3819367Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3819437Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3819628Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3819688Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3819861Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3819951Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3819955Z 
2025-09-07T10:14:10.3820046Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3820258Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3820322Z     return mod(*inputs)
2025-09-07T10:14:10.3820498Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3820572Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3820745Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3820809Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3820984Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3821067Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3821085Z 
2025-09-07T10:14:10.3821391Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3821673Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3821760Z     return mod(*inputs)
2025-09-07T10:14:10.3821997Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3822099Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3822286Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3822460Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3822679Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3822800Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3822804Z 
2025-09-07T10:14:10.3822926Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3823161Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3823342Z     return mod(*inputs)
2025-09-07T10:14:10.3823577Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3823706Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3823910Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3824032Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3824222Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3824377Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3824380Z 
2025-09-07T10:14:10.3824564Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3824838Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3824959Z     return mod(*inputs)
2025-09-07T10:14:10.3825172Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3825353Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3825626Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3825714Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3825947Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3826132Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3826136Z 
2025-09-07T10:14:10.3826295Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3826561Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3826662Z     return mod(*inputs)
2025-09-07T10:14:10.3826902Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3827006Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3827252Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3827328Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3827573Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3827734Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3827737Z 
2025-09-07T10:14:10.3827860Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3828126Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3828213Z     return mod(*inputs)
2025-09-07T10:14:10.3828481Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3828590Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3828797Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3828927Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3829173Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3829282Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3829286Z 
2025-09-07T10:14:10.3836711Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3836963Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3837030Z     return mod(*inputs)
2025-09-07T10:14:10.3837238Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3837319Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3837508Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3837572Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3837753Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3837852Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3837856Z 
2025-09-07T10:14:10.3837964Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3838254Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3838316Z     return mod(*inputs)
2025-09-07T10:14:10.3838507Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3838589Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3838775Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3838840Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3839019Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3839111Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3839154Z 
2025-09-07T10:14:10.3839261Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3839461Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3839527Z     return mod(*inputs)
2025-09-07T10:14:10.3839711Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3839788Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3839974Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3840097Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3840282Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3840372Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3840376Z 
2025-09-07T10:14:10.3840476Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3840682Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3840741Z     return mod(*inputs)
2025-09-07T10:14:10.3840924Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3840998Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3841173Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3841236Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3841411Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3841485Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3841488Z 
2025-09-07T10:14:10.3841584Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3841786Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3841847Z     return mod(*inputs)
2025-09-07T10:14:10.3842028Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3842105Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3842277Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3842341Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3842517Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3842606Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3842609Z 
2025-09-07T10:14:10.3842709Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3842903Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3842964Z     return mod(*inputs)
2025-09-07T10:14:10.3843145Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3843214Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3843395Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3843453Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3843633Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3843755Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3843758Z 
2025-09-07T10:14:10.3843852Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3844051Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3844109Z     return mod(*inputs)
2025-09-07T10:14:10.3844294Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3844366Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3844545Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3844602Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3844809Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3844898Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3844902Z 
2025-09-07T10:14:10.3844993Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3845189Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3845245Z     return mod(*inputs)
2025-09-07T10:14:10.3845424Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3845556Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3845734Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3845799Z     x = self.down5(s5)
2025-09-07T10:14:10.3845971Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 72, in forward
2025-09-07T10:14:10.3846033Z     x = F.avg_pool2d(x, 2)
2025-09-07T10:14:10.3846038Z 
2025-09-07T10:14:10.3846135Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3846328Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3846392Z     return mod(*inputs)
2025-09-07T10:14:10.3846568Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3846636Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3846815Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3846871Z     x = self.down5(s5)
2025-09-07T10:14:10.3847049Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3847134Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3847137Z 
2025-09-07T10:14:10.3847231Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3847425Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3847484Z     return mod(*inputs)
2025-09-07T10:14:10.3847666Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3847736Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3847913Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3847971Z     x = self.down5(s5)
2025-09-07T10:14:10.3848145Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 74, in forward
2025-09-07T10:14:10.3848240Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3848244Z 
2025-09-07T10:14:10.3848340Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3848534Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3848594Z     return mod(*inputs)
2025-09-07T10:14:10.3848771Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3848848Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3849028Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 203, in forward
2025-09-07T10:14:10.3849128Z     x = self.down5(s5)
2025-09-07T10:14:10.3849302Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3849390Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3849393Z 
2025-09-07T10:14:10.3849492Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3849688Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3849752Z     return mod(*inputs)
2025-09-07T10:14:10.3849930Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3850002Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3850235Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3850295Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3850472Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3850557Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3850561Z 
2025-09-07T10:14:10.3850658Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3850852Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3850908Z     return mod(*inputs)
2025-09-07T10:14:10.3851149Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3851222Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3851399Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3851456Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3851633Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3851722Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3851725Z 
2025-09-07T10:14:10.3851816Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3852010Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3852069Z     return mod(*inputs)
2025-09-07T10:14:10.3852246Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3852321Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3852493Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 202, in forward
2025-09-07T10:14:10.3852555Z     s5 = self.down4(s4)
2025-09-07T10:14:10.3852726Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3852810Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3852815Z 
2025-09-07T10:14:10.3852910Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3853099Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3853163Z     return mod(*inputs)
2025-09-07T10:14:10.3853339Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3853409Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3853586Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3853647Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3853820Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3853956Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3853959Z 
2025-09-07T10:14:10.3854040Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3854132Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3854325Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3854385Z     return mod(*inputs)
2025-09-07T10:14:10.3854598Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3854672Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3854847Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 204, in forward
2025-09-07T10:14:10.3854902Z     x = self.up1(x, s5)
2025-09-07T10:14:10.3855081Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3855210Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3855214Z 
2025-09-07T10:14:10.3855310Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3855497Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3855588Z     return mod(*inputs)
2025-09-07T10:14:10.3855772Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3855843Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3856019Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3856078Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3856247Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3856397Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3856400Z 
2025-09-07T10:14:10.3856493Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3856690Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3856748Z     return mod(*inputs)
2025-09-07T10:14:10.3856926Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3856997Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3857170Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3857233Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3857401Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3857489Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3857492Z 
2025-09-07T10:14:10.3857584Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3857779Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3857841Z     return mod(*inputs)
2025-09-07T10:14:10.3858018Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3858090Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3858263Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 201, in forward
2025-09-07T10:14:10.3858320Z     s4 = self.down3(s3)
2025-09-07T10:14:10.3858496Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3858581Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3858583Z 
2025-09-07T10:14:10.3858680Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3858866Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3858925Z     return mod(*inputs)
2025-09-07T10:14:10.3859107Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3859175Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3859351Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3859408Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3859584Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3859712Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3859715Z 
2025-09-07T10:14:10.3859826Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3859926Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3860117Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3860176Z     return mod(*inputs)
2025-09-07T10:14:10.3860358Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3860431Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3860628Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 205, in forward
2025-09-07T10:14:10.3860684Z     x = self.up2(x, s4)
2025-09-07T10:14:10.3860862Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3861046Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3861049Z 
2025-09-07T10:14:10.3861146Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3861344Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3861403Z     return mod(*inputs)
2025-09-07T10:14:10.3861586Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3861657Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3861890Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3861952Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3862122Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3862208Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3862213Z 
2025-09-07T10:14:10.3862304Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3862499Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3862558Z     return mod(*inputs)
2025-09-07T10:14:10.3862736Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3862807Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3862975Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3863035Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3863208Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3863291Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3863294Z 
2025-09-07T10:14:10.3863388Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3863576Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3863636Z     return mod(*inputs)
2025-09-07T10:14:10.3863813Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3863883Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3864060Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 200, in forward
2025-09-07T10:14:10.3864115Z     s3 = self.down2(s2)
2025-09-07T10:14:10.3864292Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3864374Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3864377Z 
2025-09-07T10:14:10.3864467Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3864656Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3864712Z     return mod(*inputs)
2025-09-07T10:14:10.3864889Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3864959Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3865128Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3865225Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3865398Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3865525Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3865528Z 
2025-09-07T10:14:10.3865673Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3865772Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3865963Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3866020Z     return mod(*inputs)
2025-09-07T10:14:10.3866200Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3866309Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3866481Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 206, in forward
2025-09-07T10:14:10.3866538Z     x = self.up3(x, s3)
2025-09-07T10:14:10.3866707Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3866842Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3866845Z 
2025-09-07T10:14:10.3866936Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3867197Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3867256Z     return mod(*inputs)
2025-09-07T10:14:10.3867431Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3867504Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3867674Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3867738Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3867906Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3867990Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3868000Z 
2025-09-07T10:14:10.3868093Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3868279Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3868340Z     return mod(*inputs)
2025-09-07T10:14:10.3868521Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3868596Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3868769Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3868828Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3869004Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3869088Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3869091Z 
2025-09-07T10:14:10.3869185Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3869375Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3869431Z     return mod(*inputs)
2025-09-07T10:14:10.3869613Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3869683Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3869863Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 199, in forward
2025-09-07T10:14:10.3869921Z     s2 = self.down1(s1)
2025-09-07T10:14:10.3870092Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 76, in forward
2025-09-07T10:14:10.3870179Z     x = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3870182Z 
2025-09-07T10:14:10.3870275Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3870467Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3870525Z     return mod(*inputs)
2025-09-07T10:14:10.3870757Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3870828Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3871001Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3871063Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3871232Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3871358Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3871365Z 
2025-09-07T10:14:10.3871436Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3871529Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3871754Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3871812Z     return mod(*inputs)
2025-09-07T10:14:10.3871994Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3872067Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3872237Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 207, in forward
2025-09-07T10:14:10.3872299Z     x = self.up4(x, s2)
2025-09-07T10:14:10.3872529Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3872659Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3872662Z 
2025-09-07T10:14:10.3872751Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3872939Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3873005Z     return mod(*inputs)
2025-09-07T10:14:10.3873183Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3873255Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3873425Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3873485Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3873663Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3873746Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3873749Z 
2025-09-07T10:14:10.3873846Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3874037Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3874095Z     return mod(*inputs)
2025-09-07T10:14:10.3874277Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3874347Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3874521Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3874578Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3874756Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 136, in forward
2025-09-07T10:14:10.3874838Z     x = F.leaky_relu(self.conv1(x), negative_slope=0.1)
2025-09-07T10:14:10.3874841Z 
2025-09-07T10:14:10.3874931Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3875127Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3875183Z     return mod(*inputs)
2025-09-07T10:14:10.3875363Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3875428Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3875600Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 198, in forward
2025-09-07T10:14:10.3875697Z     s1 = F.leaky_relu(self.conv2(x), negative_slope=0.1)
2025-09-07T10:14:10.3875700Z 
2025-09-07T10:14:10.3875791Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3875982Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3876073Z     return mod(*inputs)
2025-09-07T10:14:10.3876249Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3876318Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3876493Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3876555Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3876727Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3876858Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3876893Z 
2025-09-07T10:14:10.3876964Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3877057Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3877245Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3877305Z     return mod(*inputs)
2025-09-07T10:14:10.3877486Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3877556Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3877728Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3877851Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3878022Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3878152Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3878156Z 
2025-09-07T10:14:10.3878245Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3878436Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3878491Z     return mod(*inputs)
2025-09-07T10:14:10.3878668Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3878740Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3878907Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 208, in forward
2025-09-07T10:14:10.3878965Z     x = self.up5(x, s1)
2025-09-07T10:14:10.3879138Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 138, in forward
2025-09-07T10:14:10.3879262Z     x = F.leaky_relu(self.conv2(torch.cat((x, skpCn), 1)), negative_slope=0.1)
2025-09-07T10:14:10.3879268Z 
2025-09-07T10:14:10.3879359Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3879547Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3879608Z     return mod(*inputs)
2025-09-07T10:14:10.3879785Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 48, in forward
2025-09-07T10:14:10.3879855Z     intrpOut = self.ArbTimeFlowIntrp(
2025-09-07T10:14:10.3880032Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 209, in forward
2025-09-07T10:14:10.3880116Z     x = F.leaky_relu(self.conv3(x), negative_slope=0.1)
2025-09-07T10:14:10.3880119Z 
2025-09-07T10:14:10.3880212Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3880400Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3880460Z     return mod(*inputs)
2025-09-07T10:14:10.3880634Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 57, in forward
2025-09-07T10:14:10.3880710Z     V_t_0 = F.sigmoid(intrpOut[:, 4:5, :, :])
2025-09-07T10:14:10.3880713Z 
2025-09-07T10:14:10.3880808Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3880997Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3881057Z     return mod(*inputs)
2025-09-07T10:14:10.3881232Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 61, in forward
2025-09-07T10:14:10.3881362Z     g_I0_F_t_0_f = self.trainFlowBackWarp(I0, F_t_0_f)
2025-09-07T10:14:10.3881538Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T10:14:10.3881603Z     grid = torch.stack((x, y), dim=3)
2025-09-07T10:14:10.3881606Z 
2025-09-07T10:14:10.3881703Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3881889Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3881947Z     return mod(*inputs)
2025-09-07T10:14:10.3882123Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 62, in forward
2025-09-07T10:14:10.3882244Z     g_I1_F_t_1_f = self.trainFlowBackWarp(I1, F_t_1_f)
2025-09-07T10:14:10.3882416Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T10:14:10.3882480Z     grid = torch.stack((x, y), dim=3)
2025-09-07T10:14:10.3882485Z 
2025-09-07T10:14:10.3882579Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3882762Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3882819Z     return mod(*inputs)
2025-09-07T10:14:10.3883057Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3883199Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3883202Z 
2025-09-07T10:14:10.3883296Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3883486Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3883544Z     return mod(*inputs)
2025-09-07T10:14:10.3883720Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3883853Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3883858Z 
2025-09-07T10:14:10.3883952Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3884135Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3884193Z     return mod(*inputs)
2025-09-07T10:14:10.3884369Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3884503Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3884507Z 
2025-09-07T10:14:10.3884603Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3884792Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3884855Z     return mod(*inputs)
2025-09-07T10:14:10.3885039Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3885169Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3885177Z 
2025-09-07T10:14:10.3885266Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3885451Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3885512Z     return mod(*inputs)
2025-09-07T10:14:10.3885691Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3885824Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3885827Z 
2025-09-07T10:14:10.3885918Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3886109Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3886172Z     return mod(*inputs)
2025-09-07T10:14:10.3886355Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3886493Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3886530Z 
2025-09-07T10:14:10.3886618Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3886806Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3886864Z     return mod(*inputs)
2025-09-07T10:14:10.3887043Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3887176Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3887180Z 
2025-09-07T10:14:10.3887269Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3887460Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3887548Z     return mod(*inputs)
2025-09-07T10:14:10.3887725Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3887867Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3887870Z 
2025-09-07T10:14:10.3887959Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3888148Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3888204Z     return mod(*inputs)
2025-09-07T10:14:10.3888454Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3888593Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3888596Z 
2025-09-07T10:14:10.3888692Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3888880Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3888940Z     return mod(*inputs)
2025-09-07T10:14:10.3889120Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3889253Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3889256Z 
2025-09-07T10:14:10.3889346Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3889541Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3889601Z     return mod(*inputs)
2025-09-07T10:14:10.3889783Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3889913Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3889916Z 
2025-09-07T10:14:10.3890008Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3890198Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3890254Z     return mod(*inputs)
2025-09-07T10:14:10.3890434Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3890564Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3890567Z 
2025-09-07T10:14:10.3890658Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3890841Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3890901Z     return mod(*inputs)
2025-09-07T10:14:10.3891077Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3891206Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3891209Z 
2025-09-07T10:14:10.3891296Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3891478Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3891533Z     return mod(*inputs)
2025-09-07T10:14:10.3891709Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3891870Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3891873Z 
2025-09-07T10:14:10.3891965Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3892150Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3892209Z     return mod(*inputs)
2025-09-07T10:14:10.3892385Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3892511Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3892514Z 
2025-09-07T10:14:10.3892602Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3892816Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3892878Z     return mod(*inputs)
2025-09-07T10:14:10.3893056Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3893187Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3893190Z 
2025-09-07T10:14:10.3893288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3893541Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3893606Z     return mod(*inputs)
2025-09-07T10:14:10.3893783Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3893916Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3893922Z 
2025-09-07T10:14:10.3894015Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3894205Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3894268Z     return mod(*inputs)
2025-09-07T10:14:10.3894444Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3894578Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3894581Z 
2025-09-07T10:14:10.3894674Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3894858Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3894919Z     return mod(*inputs)
2025-09-07T10:14:10.3895094Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3895228Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3895231Z 
2025-09-07T10:14:10.3895322Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3895503Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3895562Z     return mod(*inputs)
2025-09-07T10:14:10.3895738Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3895873Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3895875Z 
2025-09-07T10:14:10.3895963Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3896154Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3896212Z     return mod(*inputs)
2025-09-07T10:14:10.3896387Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3896517Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3896522Z 
2025-09-07T10:14:10.3896610Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3896801Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3896860Z     return mod(*inputs)
2025-09-07T10:14:10.3897075Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3897217Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3897220Z 
2025-09-07T10:14:10.3897308Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3897496Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3897552Z     return mod(*inputs)
2025-09-07T10:14:10.3897733Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3897862Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3897896Z 
2025-09-07T10:14:10.3897987Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3898180Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3898240Z     return mod(*inputs)
2025-09-07T10:14:10.3898419Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3898550Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3898554Z 
2025-09-07T10:14:10.3898644Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3899336Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3899399Z     return mod(*inputs)
2025-09-07T10:14:10.3899579Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3899707Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3899713Z 
2025-09-07T10:14:10.3899807Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3899992Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3900049Z     return mod(*inputs)
2025-09-07T10:14:10.3900228Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3900356Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3900359Z 
2025-09-07T10:14:10.3900435Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3900525Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3900715Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3900778Z     return mod(*inputs)
2025-09-07T10:14:10.3900952Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 79, in forward
2025-09-07T10:14:10.3901048Z     + L1_lossFn(self.trainFlowBackWarp(I0, F_1_0), I1)
2025-09-07T10:14:10.3901222Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T10:14:10.3901287Z     grid = torch.stack((x, y), dim=3)
2025-09-07T10:14:10.3901292Z 
2025-09-07T10:14:10.3901368Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3901459Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3901651Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3901709Z     return mod(*inputs)
2025-09-07T10:14:10.3901892Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 80, in forward
2025-09-07T10:14:10.3901981Z     + L1_lossFn(self.trainFlowBackWarp(I1, F_0_1), I0)
2025-09-07T10:14:10.3902155Z   File "/torchbench/torchbenchmark/models/Super_SloMo/slomo_model.py", line 286, in forward
2025-09-07T10:14:10.3902221Z     grid = torch.stack((x, y), dim=3)
2025-09-07T10:14:10.3902226Z 
2025-09-07T10:14:10.3902294Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3902388Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3902574Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3902691Z     return mod(*inputs)
2025-09-07T10:14:10.3902878Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3903010Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3903013Z 
2025-09-07T10:14:10.3903112Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3903299Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3903355Z     return mod(*inputs)
2025-09-07T10:14:10.3903533Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3903718Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3903721Z 
2025-09-07T10:14:10.3903814Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3903997Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3904058Z     return mod(*inputs)
2025-09-07T10:14:10.3904235Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3904368Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3904434Z 
2025-09-07T10:14:10.3904531Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3904743Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3904801Z     return mod(*inputs)
2025-09-07T10:14:10.3904975Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3905106Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3905109Z 
2025-09-07T10:14:10.3905201Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3905391Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3905451Z     return mod(*inputs)
2025-09-07T10:14:10.3905696Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3905827Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3905837Z 
2025-09-07T10:14:10.3905929Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3906117Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3906182Z     return mod(*inputs)
2025-09-07T10:14:10.3906359Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3906490Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3906493Z 
2025-09-07T10:14:10.3906583Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3906770Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3906830Z     return mod(*inputs)
2025-09-07T10:14:10.3907006Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3907142Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3907144Z 
2025-09-07T10:14:10.3907235Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3907419Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3907480Z     return mod(*inputs)
2025-09-07T10:14:10.3907655Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3907786Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3907788Z 
2025-09-07T10:14:10.3907877Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3908105Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3908162Z     return mod(*inputs)
2025-09-07T10:14:10.3908334Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3908467Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3908470Z 
2025-09-07T10:14:10.3908559Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3908747Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3908802Z     return mod(*inputs)
2025-09-07T10:14:10.3909011Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3909142Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3909145Z 
2025-09-07T10:14:10.3909241Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3909439Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3909496Z     return mod(*inputs)
2025-09-07T10:14:10.3909676Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3909881Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3909884Z 
2025-09-07T10:14:10.3909973Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3910163Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3910219Z     return mod(*inputs)
2025-09-07T10:14:10.3910398Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 74, in forward
2025-09-07T10:14:10.3910524Z     prcpLoss = MSE_LossFn(self.vgg16_conv_4_3(Ft_p), self.vgg16_conv_4_3(IFrame))
2025-09-07T10:14:10.3910527Z 
2025-09-07T10:14:10.3910599Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3910672Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3910740Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3910810Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3910878Z cudagraph partition due to non gpu ops
2025-09-07T10:14:10.3910971Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:14:10.3911165Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:14:10.3911220Z     return mod(*inputs)
2025-09-07T10:14:10.3911398Z   File "/torchbench/torchbenchmark/models/Super_SloMo/model_wrapper.py", line 94, in forward
2025-09-07T10:14:10.3911516Z     loss = 204 * recnLoss + 102 * warpLoss + 0.005 * prcpLoss + loss_smooth
2025-09-07T10:14:10.3911521Z 
2025-09-07T10:14:57.1523999Z 
2025-09-07T10:14:57.9192268Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:14:58.6845472Z running benchmark:   3% 1/30 [00:00<00:22,  1.30it/s]
2025-09-07T10:14:59.4367271Z running benchmark:   7% 2/30 [00:01<00:21,  1.31it/s]
2025-09-07T10:15:00.1863743Z running benchmark:  10% 3/30 [00:02<00:20,  1.32it/s]
2025-09-07T10:15:01.0103350Z running benchmark:  13% 4/30 [00:03<00:19,  1.32it/s]
2025-09-07T10:15:01.7693387Z running benchmark:  17% 5/30 [00:03<00:19,  1.28it/s]
2025-09-07T10:15:02.5200675Z running benchmark:  20% 6/30 [00:04<00:18,  1.29it/s]
2025-09-07T10:15:03.2811237Z running benchmark:  23% 7/30 [00:05<00:17,  1.31it/s]
2025-09-07T10:15:04.0374600Z running benchmark:  27% 8/30 [00:06<00:16,  1.31it/s]
2025-09-07T10:15:04.8645293Z running benchmark:  30% 9/30 [00:06<00:15,  1.31it/s]
2025-09-07T10:15:05.6263519Z running benchmark:  33% 10/30 [00:07<00:15,  1.28it/s]
2025-09-07T10:15:06.3774485Z running benchmark:  37% 11/30 [00:08<00:14,  1.29it/s]
2025-09-07T10:15:07.1375102Z running benchmark:  40% 12/30 [00:09<00:13,  1.30it/s]
2025-09-07T10:15:07.8912399Z running benchmark:  43% 13/30 [00:09<00:13,  1.31it/s]
2025-09-07T10:15:08.7172774Z running benchmark:  47% 14/30 [00:10<00:12,  1.31it/s]
2025-09-07T10:15:09.4760937Z running benchmark:  50% 15/30 [00:11<00:11,  1.28it/s]
2025-09-07T10:15:10.2406775Z running benchmark:  53% 16/30 [00:12<00:10,  1.29it/s]
2025-09-07T10:15:10.9904305Z running benchmark:  57% 17/30 [00:13<00:10,  1.30it/s]
2025-09-07T10:15:11.7496901Z running benchmark:  60% 18/30 [00:13<00:09,  1.31it/s]
2025-09-07T10:15:12.5047082Z running benchmark:  63% 19/30 [00:14<00:08,  1.31it/s]
2025-09-07T10:15:13.3276548Z running benchmark:  67% 20/30 [00:15<00:07,  1.31it/s]
2025-09-07T10:15:14.0875242Z running benchmark:  70% 21/30 [00:16<00:07,  1.28it/s]
2025-09-07T10:15:14.8462172Z running benchmark:  73% 22/30 [00:16<00:06,  1.29it/s]
2025-09-07T10:15:15.6094635Z running benchmark:  77% 23/30 [00:17<00:05,  1.30it/s]
2025-09-07T10:15:16.3665803Z running benchmark:  80% 24/30 [00:18<00:04,  1.30it/s]
2025-09-07T10:15:17.1915793Z running benchmark:  83% 25/30 [00:19<00:03,  1.31it/s]
2025-09-07T10:15:17.9424115Z running benchmark:  87% 26/30 [00:20<00:03,  1.28it/s]
2025-09-07T10:15:18.6946270Z running benchmark:  90% 27/30 [00:20<00:02,  1.29it/s]
2025-09-07T10:15:19.4497616Z running benchmark:  93% 28/30 [00:21<00:01,  1.30it/s]
2025-09-07T10:15:20.2015804Z running benchmark:  97% 29/30 [00:22<00:00,  1.31it/s]
2025-09-07T10:15:20.2016663Z running benchmark: 100% 30/30 [00:23<00:00,  1.32it/s]
2025-09-07T10:15:20.2016939Z running benchmark: 100% 30/30 [00:23<00:00,  1.30it/s]
2025-09-07T10:15:20.3460730Z 1.119x
2025-09-07T10:15:20.3463223Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:15:22.9597186Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:15:22.9598119Z   import pynvml  # type: ignore[import]
2025-09-07T10:15:24.9802590Z 
2025-09-07T10:15:25.8407707Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:15:25.8408023Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:15:25.8489364Z cpu  eval  alexnet                            
2025-09-07T10:15:28.5920924Z cudagraph partition due to non gpu ops
2025-09-07T10:15:28.5921240Z cudagraph partition due to non gpu ops
2025-09-07T10:15:28.5921487Z cudagraph partition due to non gpu ops
2025-09-07T10:15:28.5921697Z cudagraph partition due to non gpu ops
2025-09-07T10:15:28.5921897Z cudagraph partition due to non gpu ops
2025-09-07T10:15:28.5922100Z cudagraph partition due to non gpu ops
2025-09-07T10:15:28.5922336Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5922734Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5923074Z     return mod(*inputs)
2025-09-07T10:15:28.5923439Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5923835Z     x = self.features(x)
2025-09-07T10:15:28.5923947Z 
2025-09-07T10:15:28.5924064Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5924450Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5924779Z     return mod(*inputs)
2025-09-07T10:15:28.5925117Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5925475Z     x = self.features(x)
2025-09-07T10:15:28.5925576Z 
2025-09-07T10:15:28.5925683Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5926047Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5926370Z     return mod(*inputs)
2025-09-07T10:15:28.5926694Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5927361Z     x = self.features(x)
2025-09-07T10:15:28.5927462Z 
2025-09-07T10:15:28.5927567Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5927915Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5928247Z     return mod(*inputs)
2025-09-07T10:15:28.5928576Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5928932Z     x = self.features(x)
2025-09-07T10:15:28.5929029Z 
2025-09-07T10:15:28.5929130Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5929481Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5929904Z     return mod(*inputs)
2025-09-07T10:15:28.5930220Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5930566Z     x = self.features(x)
2025-09-07T10:15:28.5930670Z 
2025-09-07T10:15:28.5930769Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5931122Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5931441Z     return mod(*inputs)
2025-09-07T10:15:28.5931904Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5932258Z     x = self.features(x)
2025-09-07T10:15:28.5932362Z 
2025-09-07T10:15:28.5932489Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5932845Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5933168Z     return mod(*inputs)
2025-09-07T10:15:28.5933493Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5933835Z     x = self.features(x)
2025-09-07T10:15:28.5933936Z 
2025-09-07T10:15:28.5934035Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5934391Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5934713Z     return mod(*inputs)
2025-09-07T10:15:28.5935029Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5935377Z     x = self.features(x)
2025-09-07T10:15:28.5935474Z 
2025-09-07T10:15:28.5935570Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5935915Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5936237Z     return mod(*inputs)
2025-09-07T10:15:28.5936546Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5936892Z     x = self.features(x)
2025-09-07T10:15:28.5936995Z 
2025-09-07T10:15:28.5937088Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5937440Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5937760Z     return mod(*inputs)
2025-09-07T10:15:28.5938068Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 48, in forward
2025-09-07T10:15:28.5938406Z     x = self.features(x)
2025-09-07T10:15:28.5938507Z 
2025-09-07T10:15:28.5938606Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5938955Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5939276Z     return mod(*inputs)
2025-09-07T10:15:28.5939584Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 49, in forward
2025-09-07T10:15:28.5939930Z     x = self.avgpool(x)
2025-09-07T10:15:28.5940030Z 
2025-09-07T10:15:28.5940125Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5940473Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5940851Z     return mod(*inputs)
2025-09-07T10:15:28.5941156Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T10:15:28.5941506Z     x = self.classifier(x)
2025-09-07T10:15:28.5941614Z 
2025-09-07T10:15:28.5941722Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5942070Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5942382Z     return mod(*inputs)
2025-09-07T10:15:28.5942691Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T10:15:28.5943081Z     x = self.classifier(x)
2025-09-07T10:15:28.5943183Z 
2025-09-07T10:15:28.5943286Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5943635Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5943952Z     return mod(*inputs)
2025-09-07T10:15:28.5944264Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T10:15:28.5944602Z     x = self.classifier(x)
2025-09-07T10:15:28.5944705Z 
2025-09-07T10:15:28.5944807Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5946018Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5946352Z     return mod(*inputs)
2025-09-07T10:15:28.5946666Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T10:15:28.5947010Z     x = self.classifier(x)
2025-09-07T10:15:28.5947113Z 
2025-09-07T10:15:28.5947213Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:28.5947555Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:28.5947875Z     return mod(*inputs)
2025-09-07T10:15:28.5948190Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/alexnet.py", line 51, in forward
2025-09-07T10:15:28.5948537Z     x = self.classifier(x)
2025-09-07T10:15:28.5948637Z 
2025-09-07T10:15:38.5562787Z 
2025-09-07T10:15:38.6997179Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:15:38.8290179Z running benchmark:   7% 2/30 [00:00<00:02, 14.00it/s]
2025-09-07T10:15:38.9605038Z running benchmark:  13% 4/30 [00:00<00:01, 14.83it/s]
2025-09-07T10:15:39.0917609Z running benchmark:  20% 6/30 [00:00<00:01, 15.00it/s]
2025-09-07T10:15:39.2217049Z running benchmark:  27% 8/30 [00:00<00:01, 15.09it/s]
2025-09-07T10:15:39.3517452Z running benchmark:  33% 10/30 [00:00<00:01, 15.20it/s]
2025-09-07T10:15:39.4816652Z running benchmark:  40% 12/30 [00:00<00:01, 15.26it/s]
2025-09-07T10:15:39.6118157Z running benchmark:  47% 14/30 [00:00<00:01, 15.30it/s]
2025-09-07T10:15:39.7416545Z running benchmark:  53% 16/30 [00:01<00:00, 15.32it/s]
2025-09-07T10:15:39.8719074Z running benchmark:  60% 18/30 [00:01<00:00, 15.35it/s]
2025-09-07T10:15:40.0018489Z running benchmark:  67% 20/30 [00:01<00:00, 15.35it/s]
2025-09-07T10:15:40.1306578Z running benchmark:  73% 22/30 [00:01<00:00, 15.36it/s]
2025-09-07T10:15:40.2606930Z running benchmark:  80% 24/30 [00:01<00:00, 15.41it/s]
2025-09-07T10:15:40.3908375Z running benchmark:  87% 26/30 [00:01<00:00, 15.40it/s]
2025-09-07T10:15:40.5207786Z running benchmark:  93% 28/30 [00:01<00:00, 15.39it/s]
2025-09-07T10:15:40.5208140Z running benchmark: 100% 30/30 [00:01<00:00, 15.39it/s]
2025-09-07T10:15:40.5208439Z running benchmark: 100% 30/30 [00:01<00:00, 15.27it/s]
2025-09-07T10:15:40.5907581Z 1.431x
2025-09-07T10:15:40.5909854Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:15:42.6300210Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:15:42.6301354Z   import pynvml  # type: ignore[import]
2025-09-07T10:15:44.6530016Z 
2025-09-07T10:15:46.1420750Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:15:46.1421064Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:15:46.1426426Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T10:15:47.7350590Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7351044Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7351391Z     return mod(*inputs)
2025-09-07T10:15:47.7351779Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7352441Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7352689Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 233, in forward
2025-09-07T10:15:47.7352974Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7353281Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 192, in propagate
2025-09-07T10:15:47.7353652Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T10:15:47.7354309Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:15:47.7354779Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:15:47.7355203Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:15:47.7355619Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:15:47.7356028Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward
2025-09-07T10:15:47.7356434Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='max')
2025-09-07T10:15:47.7356840Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:15:47.7357221Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:15:47.7357601Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter
2025-09-07T10:15:47.7357976Z     return src.new_zeros(size).scatter_reduce_(
2025-09-07T10:15:47.7358121Z 
2025-09-07T10:15:47.7358228Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7358614Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7358959Z     return mod(*inputs)
2025-09-07T10:15:47.7359313Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7359696Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7359935Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 233, in forward
2025-09-07T10:15:47.7360209Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7360483Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 192, in propagate
2025-09-07T10:15:47.7360828Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T10:15:47.7361325Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:15:47.7361785Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:15:47.7362204Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:15:47.7362628Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:15:47.7363031Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward
2025-09-07T10:15:47.7363427Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='max')
2025-09-07T10:15:47.7363907Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:15:47.7364286Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:15:47.7364672Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter
2025-09-07T10:15:47.7365062Z     return src.new_zeros(size).scatter_reduce_(
2025-09-07T10:15:47.7365210Z 
2025-09-07T10:15:47.7365315Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7365689Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7366024Z     return mod(*inputs)
2025-09-07T10:15:47.7366388Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7366822Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7367061Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 233, in forward
2025-09-07T10:15:47.7367335Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7367609Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 192, in propagate
2025-09-07T10:15:47.7367959Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T10:15:47.7368522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:15:47.7368988Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:15:47.7369407Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:15:47.7369821Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:15:47.7370258Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 48, in forward
2025-09-07T10:15:47.7370682Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='max')
2025-09-07T10:15:47.7371101Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:15:47.7371465Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:15:47.7371835Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 98, in scatter
2025-09-07T10:15:47.7372210Z     return src.new_zeros(size).scatter_reduce_(
2025-09-07T10:15:47.7372353Z 
2025-09-07T10:15:47.7372461Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7372829Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7373155Z     return mod(*inputs)
2025-09-07T10:15:47.7373502Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7373874Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7374114Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 233, in forward
2025-09-07T10:15:47.7374373Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7374646Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 191, in propagate
2025-09-07T10:15:47.7374910Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7375302Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7375710Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7375882Z 
2025-09-07T10:15:47.7375993Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7376366Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7376700Z     return mod(*inputs)
2025-09-07T10:15:47.7377055Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7377435Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7378219Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 233, in forward
2025-09-07T10:15:47.7378488Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7378759Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 191, in propagate
2025-09-07T10:15:47.7379031Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7379421Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7379818Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7380209Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T10:15:47.7380606Z     x = lin(x)
2025-09-07T10:15:47.7380919Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:15:47.7381302Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:15:47.7381453Z 
2025-09-07T10:15:47.7381555Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7381928Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7382256Z     return mod(*inputs)
2025-09-07T10:15:47.7382658Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7383043Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7383279Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 233, in forward
2025-09-07T10:15:47.7383543Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7383807Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 191, in propagate
2025-09-07T10:15:47.7384077Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7384464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7384854Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7385234Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T10:15:47.7385659Z     x = self.act(x)
2025-09-07T10:15:47.7385759Z 
2025-09-07T10:15:47.7385859Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7386224Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7386553Z     return mod(*inputs)
2025-09-07T10:15:47.7386887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7387264Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7387499Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 233, in forward
2025-09-07T10:15:47.7387758Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7388022Z   File "/tmp/jenkins_pyg/tmpt08xfz5u.py", line 191, in propagate
2025-09-07T10:15:47.7388281Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7388666Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7389054Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7389439Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T10:15:47.7389786Z     x = self.lins[-1](x)
2025-09-07T10:15:47.7390117Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:15:47.7390494Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:15:47.7390636Z 
2025-09-07T10:15:47.7390720Z cudagraph partition due to non gpu ops
2025-09-07T10:15:47.7390951Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7391303Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7391672Z     return mod(*inputs)
2025-09-07T10:15:47.7392006Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7392383Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7392609Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 233, in forward
2025-09-07T10:15:47.7392875Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7393141Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 191, in propagate
2025-09-07T10:15:47.7393401Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7393787Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7394204Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7394362Z 
2025-09-07T10:15:47.7394460Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7394820Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7395151Z     return mod(*inputs)
2025-09-07T10:15:47.7395490Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7395862Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7396220Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 233, in forward
2025-09-07T10:15:47.7396486Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7396753Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 191, in propagate
2025-09-07T10:15:47.7397015Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7397402Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7397795Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7398180Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T10:15:47.7398521Z     x = lin(x)
2025-09-07T10:15:47.7399025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:15:47.7399407Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:15:47.7399552Z 
2025-09-07T10:15:47.7399661Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7400029Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7400350Z     return mod(*inputs)
2025-09-07T10:15:47.7400691Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7401070Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7401308Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 233, in forward
2025-09-07T10:15:47.7401565Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7401837Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 191, in propagate
2025-09-07T10:15:47.7402100Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7402485Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7402870Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7403246Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T10:15:47.7403594Z     x = self.act(x)
2025-09-07T10:15:47.7403691Z 
2025-09-07T10:15:47.7403790Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7404151Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7404475Z     return mod(*inputs)
2025-09-07T10:15:47.7404816Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7405256Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7405494Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 233, in forward
2025-09-07T10:15:47.7405753Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7406012Z   File "/tmp/jenkins_pyg/tmp8rp32np3.py", line 191, in propagate
2025-09-07T10:15:47.7406279Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7406673Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7407060Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7407430Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T10:15:47.7407838Z     x = self.lins[-1](x)
2025-09-07T10:15:47.7408178Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:15:47.7408562Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:15:47.7408698Z 
2025-09-07T10:15:47.7408780Z cudagraph partition due to non gpu ops
2025-09-07T10:15:47.7409008Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7409376Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7409792Z     return mod(*inputs)
2025-09-07T10:15:47.7410139Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7410509Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7410745Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 233, in forward
2025-09-07T10:15:47.7411006Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7411279Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 191, in propagate
2025-09-07T10:15:47.7411545Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7411926Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7412320Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7412475Z 
2025-09-07T10:15:47.7412572Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7412960Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7413279Z     return mod(*inputs)
2025-09-07T10:15:47.7413622Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7413993Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7414224Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 233, in forward
2025-09-07T10:15:47.7414483Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7414742Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 191, in propagate
2025-09-07T10:15:47.7415004Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7415391Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7415785Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7416159Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T10:15:47.7416508Z     x = lin(x)
2025-09-07T10:15:47.7416824Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:15:47.7417204Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:15:47.7417343Z 
2025-09-07T10:15:47.7417447Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7417807Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7418128Z     return mod(*inputs)
2025-09-07T10:15:47.7418463Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7418884Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7419115Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 233, in forward
2025-09-07T10:15:47.7419378Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7419651Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 191, in propagate
2025-09-07T10:15:47.7419929Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7420320Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7421015Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7429351Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T10:15:47.7429779Z     x = self.act(x)
2025-09-07T10:15:47.7429879Z 
2025-09-07T10:15:47.7429992Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:15:47.7430386Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:15:47.7430725Z     return mod(*inputs)
2025-09-07T10:15:47.7431096Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:15:47.7431565Z     x = self.convs[i](x, edge_index)
2025-09-07T10:15:47.7431815Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 233, in forward
2025-09-07T10:15:47.7432087Z     return self.propagate(edge_index, x=x, size=None)
2025-09-07T10:15:47.7432362Z   File "/tmp/jenkins_pyg/tmpeyaj5cgk.py", line 191, in propagate
2025-09-07T10:15:47.7432640Z     out = self.message(x_j=kwargs.x_j, x_i=kwargs.x_i)
2025-09-07T10:15:47.7433031Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/edge_conv.py", line 63, in message
2025-09-07T10:15:47.7433437Z     return self.nn(torch.cat([x_i, x_j - x_i], dim=-1))
2025-09-07T10:15:47.7433831Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T10:15:47.7434194Z     x = self.lins[-1](x)
2025-09-07T10:15:47.7434527Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:15:47.7434905Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:15:47.7435059Z 
2025-09-07T10:15:47.7435138Z cudagraph partition due to non gpu ops
2025-09-07T10:15:53.8461642Z 
2025-09-07T10:15:53.9761508Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:15:54.1069296Z running benchmark:  10% 3/30 [00:00<00:01, 23.15it/s]
2025-09-07T10:15:54.2421353Z running benchmark:  20% 6/30 [00:00<00:01, 23.01it/s]
2025-09-07T10:15:54.3778225Z running benchmark:  30% 9/30 [00:00<00:00, 22.63it/s]
2025-09-07T10:15:54.5107794Z running benchmark:  40% 12/30 [00:00<00:00, 22.42it/s]
2025-09-07T10:15:54.6473623Z running benchmark:  50% 15/30 [00:00<00:00, 22.47it/s]
2025-09-07T10:15:54.7775320Z running benchmark:  60% 18/30 [00:00<00:00, 22.30it/s]
2025-09-07T10:15:54.9076488Z running benchmark:  70% 21/30 [00:00<00:00, 22.54it/s]
2025-09-07T10:15:55.0439211Z running benchmark:  80% 24/30 [00:01<00:00, 22.71it/s]
2025-09-07T10:15:55.1737243Z running benchmark:  90% 27/30 [00:01<00:00, 22.48it/s]
2025-09-07T10:15:55.1737586Z running benchmark: 100% 30/30 [00:01<00:00, 22.67it/s]
2025-09-07T10:15:55.1737851Z running benchmark: 100% 30/30 [00:01<00:00, 22.60it/s]
2025-09-07T10:15:55.2326351Z 1.067x
2025-09-07T10:15:55.2330112Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:15:57.2839440Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:15:57.2840350Z   import pynvml  # type: ignore[import]
2025-09-07T10:15:59.3061184Z 
2025-09-07T10:16:00.8132092Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:16:00.8132400Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:16:00.8137032Z cpu  eval  basic_gnn_gcn                      
2025-09-07T10:16:02.2374584Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:02.2375154Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/loop.py", line 340, in add_remaining_self_loops
2025-09-07T10:16:02.2375573Z     mask = edge_index[0] != edge_index[1]
2025-09-07T10:16:02.2375725Z 
2025-09-07T10:16:02.2375832Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:02.2376287Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/loop.py", line 343, in add_remaining_self_loops
2025-09-07T10:16:02.2376998Z     loop_index = loop_index.unsqueeze(0).repeat(2, 1)
2025-09-07T10:16:02.2377146Z 
2025-09-07T10:16:07.0607945Z cudagraph partition due to non gpu ops
2025-09-07T10:16:07.0608266Z cudagraph partition due to non gpu ops
2025-09-07T10:16:07.0608515Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:07.0609066Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/loop.py", line 370, in torch_dynamo_resume_in_add_remaining_self_loops_at_370
2025-09-07T10:16:07.0610001Z     edge_index = torch.cat([edge_index[:, mask], loop_index], dim=1)
2025-09-07T10:16:07.0610187Z 
2025-09-07T10:16:07.7081438Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:07.7082007Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 100, in torch_dynamo_resume_in_gcn_norm_at_91
2025-09-07T10:16:07.7082539Z     deg = scatter(edge_weight, idx, dim=0, dim_size=num_nodes, reduce='sum')
2025-09-07T10:16:07.7083013Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T10:16:07.7083425Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:07.7083604Z 
2025-09-07T10:16:07.7083711Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:07.7084184Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 95, in torch_dynamo_resume_in_gcn_norm_at_91
2025-09-07T10:16:07.7084677Z     edge_weight = torch.ones((edge_index.size(1), ), dtype=dtype,
2025-09-07T10:16:07.7084858Z 
2025-09-07T10:16:07.7084943Z cudagraph partition due to non gpu ops
2025-09-07T10:16:07.7085183Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:07.7085640Z    File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 103, in torch_dynamo_resume_in_gcn_norm_at_91
2025-09-07T10:16:07.7086129Z     edge_weight = deg_inv_sqrt[row] * edge_weight * deg_inv_sqrt[col]
2025-09-07T10:16:07.7086315Z 
2025-09-07T10:16:09.0631791Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:09.0632198Z    File "/tmp/jenkins_pyg/tmpof6qi_hj.py", line 240, in torch_dynamo_resume_in_forward_at_221
2025-09-07T10:16:09.0632539Z     x = self.lin(x)
2025-09-07T10:16:09.0632887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:09.0633284Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:09.0633443Z 
2025-09-07T10:16:09.0633563Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:09.0633910Z    File "/tmp/jenkins_pyg/tmpof6qi_hj.py", line 243, in torch_dynamo_resume_in_forward_at_221
2025-09-07T10:16:09.0634260Z     out = self.propagate(edge_index, x=x, edge_weight=edge_weight,
2025-09-07T10:16:09.0634560Z   File "/tmp/jenkins_pyg/tmpof6qi_hj.py", line 188, in propagate
2025-09-07T10:16:09.0634921Z     out = self.aggregate(out, dim_size=kwargs.dim_size, index=kwargs.index, ptr=kwargs.ptr)
2025-09-07T10:16:09.0635434Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:09.0636213Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:09.0636629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:09.0637040Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:09.0637444Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T10:16:09.0637853Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T10:16:09.0638252Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:09.0638708Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:09.0639085Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T10:16:09.0639479Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:09.0639647Z 
2025-09-07T10:16:09.0639761Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:09.0640091Z    File "/tmp/jenkins_pyg/tmpof6qi_hj.py", line 243, in torch_dynamo_resume_in_forward_at_221
2025-09-07T10:16:09.0640438Z     out = self.propagate(edge_index, x=x, edge_weight=edge_weight,
2025-09-07T10:16:09.0640877Z   File "/tmp/jenkins_pyg/tmpof6qi_hj.py", line 187, in propagate
2025-09-07T10:16:09.0641187Z     out = self.message(edge_weight=kwargs.edge_weight, x_j=kwargs.x_j)
2025-09-07T10:16:09.0641608Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/gcn_conv.py", line 241, in message
2025-09-07T10:16:09.0642028Z     return x_j if edge_weight is None else edge_weight.view(-1, 1) * x_j
2025-09-07T10:16:09.0642224Z 
2025-09-07T10:16:09.0642302Z cudagraph partition due to non gpu ops
2025-09-07T10:16:09.0642538Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:09.0642867Z    File "/tmp/jenkins_pyg/tmpof6qi_hj.py", line 247, in torch_dynamo_resume_in_forward_at_221
2025-09-07T10:16:09.0643165Z     out = out + self.bias
2025-09-07T10:16:09.0643270Z 
2025-09-07T10:16:10.4798147Z 
2025-09-07T10:16:10.5930815Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:16:10.7057961Z running benchmark:   7% 2/30 [00:00<00:01, 17.74it/s]
2025-09-07T10:16:10.8130201Z running benchmark:  13% 4/30 [00:00<00:01, 17.74it/s]
2025-09-07T10:16:10.9224866Z running benchmark:  20% 6/30 [00:00<00:01, 18.14it/s]
2025-09-07T10:16:11.0299274Z running benchmark:  27% 8/30 [00:00<00:01, 18.19it/s]
2025-09-07T10:16:11.1400510Z running benchmark:  33% 10/30 [00:00<00:01, 18.34it/s]
2025-09-07T10:16:11.2477171Z running benchmark:  40% 12/30 [00:00<00:00, 18.28it/s]
2025-09-07T10:16:11.3570158Z running benchmark:  47% 14/30 [00:00<00:00, 18.37it/s]
2025-09-07T10:16:11.4647378Z running benchmark:  53% 16/30 [00:00<00:00, 18.35it/s]
2025-09-07T10:16:11.5730055Z running benchmark:  60% 18/30 [00:00<00:00, 18.42it/s]
2025-09-07T10:16:11.6785037Z running benchmark:  67% 20/30 [00:01<00:00, 18.44it/s]
2025-09-07T10:16:11.7874984Z running benchmark:  73% 22/30 [00:01<00:00, 18.59it/s]
2025-09-07T10:16:11.8960361Z running benchmark:  80% 24/30 [00:01<00:00, 18.52it/s]
2025-09-07T10:16:12.0087819Z running benchmark:  87% 26/30 [00:01<00:00, 18.49it/s]
2025-09-07T10:16:12.1182507Z running benchmark:  93% 28/30 [00:01<00:00, 18.26it/s]
2025-09-07T10:16:12.1182830Z running benchmark: 100% 30/30 [00:01<00:00, 18.27it/s]
2025-09-07T10:16:12.1183102Z running benchmark: 100% 30/30 [00:01<00:00, 18.32it/s]
2025-09-07T10:16:12.1668469Z 1.113x
2025-09-07T10:16:12.1671856Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:16:14.1924624Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:16:14.1927319Z   import pynvml  # type: ignore[import]
2025-09-07T10:16:16.2107604Z 
2025-09-07T10:16:17.6900288Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:16:17.6900702Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:16:17.6907577Z cpu  eval  basic_gnn_gin                      
2025-09-07T10:16:19.2536080Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2536567Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2536910Z     return mod(*inputs)
2025-09-07T10:16:19.2540166Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2540917Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2541184Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 225, in forward
2025-09-07T10:16:19.2541457Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:19.2541751Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 182, in propagate
2025-09-07T10:16:19.2542115Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T10:16:19.2542639Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:19.2543270Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:19.2543729Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:19.2544162Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:19.2544572Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T10:16:19.2544987Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T10:16:19.2545397Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:19.2545831Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:19.2546216Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T10:16:19.2546625Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:19.2546803Z 
2025-09-07T10:16:19.2546911Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2547286Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2547620Z     return mod(*inputs)
2025-09-07T10:16:19.2547967Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2548348Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2548580Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 225, in forward
2025-09-07T10:16:19.2548845Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:19.2549117Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 180, in propagate
2025-09-07T10:16:19.2549392Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T10:16:19.2549659Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 127, in _collect
2025-09-07T10:16:19.2549909Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T10:16:19.2550144Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 87, in _lift
2025-09-07T10:16:19.2550389Z     return src.index_select(self.node_dim, index)
2025-09-07T10:16:19.2550544Z 
2025-09-07T10:16:19.2550648Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2551007Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2551342Z     return mod(*inputs)
2025-09-07T10:16:19.2551689Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2552057Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2552389Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 225, in forward
2025-09-07T10:16:19.2552647Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:19.2552910Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 182, in propagate
2025-09-07T10:16:19.2553245Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T10:16:19.2553739Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:19.2554192Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:19.2554607Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:19.2555059Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:19.2555475Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T10:16:19.2555915Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T10:16:19.2556328Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:19.2556706Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:19.2557201Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T10:16:19.2557595Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:19.2557779Z 
2025-09-07T10:16:19.2557882Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2558253Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2558586Z     return mod(*inputs)
2025-09-07T10:16:19.2558931Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2559301Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2559536Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 225, in forward
2025-09-07T10:16:19.2559797Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:19.2560059Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 182, in propagate
2025-09-07T10:16:19.2560397Z     out = self.aggregate(out, index=kwargs.index, ptr=kwargs.ptr, dim_size=kwargs.dim_size)
2025-09-07T10:16:19.2560893Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:19.2561347Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:19.2561761Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:19.2562171Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:19.2562560Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 21, in forward
2025-09-07T10:16:19.2562966Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='sum')
2025-09-07T10:16:19.2563357Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:19.2563731Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:19.2564103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 74, in scatter
2025-09-07T10:16:19.2564492Z     return src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:19.2564665Z 
2025-09-07T10:16:19.2564745Z cudagraph partition due to non gpu ops
2025-09-07T10:16:19.2564977Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2565342Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2565667Z     return mod(*inputs)
2025-09-07T10:16:19.2566014Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2566433Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2566662Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 229, in forward
2025-09-07T10:16:19.2566899Z     out = out + (1 + self.eps) * x_r
2025-09-07T10:16:19.2567020Z 
2025-09-07T10:16:19.2567118Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2567477Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2567802Z     return mod(*inputs)
2025-09-07T10:16:19.2568136Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2568538Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2568769Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 231, in forward
2025-09-07T10:16:19.2568999Z     return self.nn(out)
2025-09-07T10:16:19.2569324Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T10:16:19.2569674Z     x = lin(x)
2025-09-07T10:16:19.2569983Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:19.2570363Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:19.2570572Z 
2025-09-07T10:16:19.2570677Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2571033Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2571352Z     return mod(*inputs)
2025-09-07T10:16:19.2571691Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2572061Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2572286Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 231, in forward
2025-09-07T10:16:19.2572510Z     return self.nn(out)
2025-09-07T10:16:19.2572834Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T10:16:19.2573178Z     x = self.act(x)
2025-09-07T10:16:19.2573267Z 
2025-09-07T10:16:19.2573368Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2573728Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2574048Z     return mod(*inputs)
2025-09-07T10:16:19.2574384Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2574754Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2574975Z   File "/tmp/jenkins_pyg/tmp5z5y10t_.py", line 231, in forward
2025-09-07T10:16:19.2575195Z     return self.nn(out)
2025-09-07T10:16:19.2575512Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T10:16:19.2575864Z     x = self.lins[-1](x)
2025-09-07T10:16:19.2576199Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:19.2576574Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:19.2576715Z 
2025-09-07T10:16:19.2576813Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2577170Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2577494Z     return mod(*inputs)
2025-09-07T10:16:19.2577830Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2578191Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2578420Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 225, in forward
2025-09-07T10:16:19.2578675Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:19.2578941Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 180, in propagate
2025-09-07T10:16:19.2579272Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T10:16:19.2579538Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 127, in _collect
2025-09-07T10:16:19.2579774Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T10:16:19.2580006Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 87, in _lift
2025-09-07T10:16:19.2580263Z     return src.index_select(self.node_dim, index)
2025-09-07T10:16:19.2580407Z 
2025-09-07T10:16:19.2580483Z cudagraph partition due to non gpu ops
2025-09-07T10:16:19.2580709Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2581064Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2581387Z     return mod(*inputs)
2025-09-07T10:16:19.2581770Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2582138Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2582359Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 229, in forward
2025-09-07T10:16:19.2582595Z     out = out + (1 + self.eps) * x_r
2025-09-07T10:16:19.2582712Z 
2025-09-07T10:16:19.2582817Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2583158Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2583551Z     return mod(*inputs)
2025-09-07T10:16:19.2583888Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2584258Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2584474Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 231, in forward
2025-09-07T10:16:19.2584703Z     return self.nn(out)
2025-09-07T10:16:19.2585025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T10:16:19.2585371Z     x = lin(x)
2025-09-07T10:16:19.2585722Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:19.2586090Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:19.2586238Z 
2025-09-07T10:16:19.2586337Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2586697Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2587018Z     return mod(*inputs)
2025-09-07T10:16:19.2587351Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2587721Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2587949Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 231, in forward
2025-09-07T10:16:19.2588179Z     return self.nn(out)
2025-09-07T10:16:19.2588498Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T10:16:19.2588836Z     x = self.act(x)
2025-09-07T10:16:19.2588933Z 
2025-09-07T10:16:19.2589027Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2589381Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2589702Z     return mod(*inputs)
2025-09-07T10:16:19.2590031Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2590400Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2590630Z   File "/tmp/jenkins_pyg/tmpd5f2wkyi.py", line 231, in forward
2025-09-07T10:16:19.2590861Z     return self.nn(out)
2025-09-07T10:16:19.2591184Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T10:16:19.2591533Z     x = self.lins[-1](x)
2025-09-07T10:16:19.2591868Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:19.2592241Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:19.2592445Z 
2025-09-07T10:16:19.2592550Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2592899Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2593219Z     return mod(*inputs)
2025-09-07T10:16:19.2593554Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2593928Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2594158Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 225, in forward
2025-09-07T10:16:19.2594412Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:19.2594675Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 180, in propagate
2025-09-07T10:16:19.2594992Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T10:16:19.2595264Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 127, in _collect
2025-09-07T10:16:19.2595493Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T10:16:19.2595721Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 87, in _lift
2025-09-07T10:16:19.2595968Z     return src.index_select(self.node_dim, index)
2025-09-07T10:16:19.2596115Z 
2025-09-07T10:16:19.2596197Z cudagraph partition due to non gpu ops
2025-09-07T10:16:19.2596418Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2596841Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2597173Z     return mod(*inputs)
2025-09-07T10:16:19.2597517Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2597891Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2598120Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 229, in forward
2025-09-07T10:16:19.2598357Z     out = out + (1 + self.eps) * x_r
2025-09-07T10:16:19.2598477Z 
2025-09-07T10:16:19.2598599Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2599150Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2599470Z     return mod(*inputs)
2025-09-07T10:16:19.2599813Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2600188Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2600419Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 231, in forward
2025-09-07T10:16:19.2600650Z     return self.nn(out)
2025-09-07T10:16:19.2600965Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 206, in forward
2025-09-07T10:16:19.2601312Z     x = lin(x)
2025-09-07T10:16:19.2601629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:19.2601997Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:19.2602135Z 
2025-09-07T10:16:19.2602237Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2602600Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2602921Z     return mod(*inputs)
2025-09-07T10:16:19.2603267Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2603642Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2603870Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 231, in forward
2025-09-07T10:16:19.2604113Z     return self.nn(out)
2025-09-07T10:16:19.2604439Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 211, in forward
2025-09-07T10:16:19.2604786Z     x = self.act(x)
2025-09-07T10:16:19.2604873Z 
2025-09-07T10:16:19.2604972Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:19.2605331Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:19.2605750Z     return mod(*inputs)
2025-09-07T10:16:19.2606083Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:19.2606452Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:19.2606677Z   File "/tmp/jenkins_pyg/tmpz_vexuxr.py", line 231, in forward
2025-09-07T10:16:19.2606907Z     return self.nn(out)
2025-09-07T10:16:19.2607233Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/mlp.py", line 217, in forward
2025-09-07T10:16:19.2607583Z     x = self.lins[-1](x)
2025-09-07T10:16:19.2607908Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:19.2608352Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:19.2608506Z 
2025-09-07T10:16:26.1690231Z 
2025-09-07T10:16:26.3009979Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:16:26.4306811Z running benchmark:  10% 3/30 [00:00<00:01, 22.80it/s]
2025-09-07T10:16:26.5590967Z running benchmark:  20% 6/30 [00:00<00:01, 23.02it/s]
2025-09-07T10:16:26.6884374Z running benchmark:  30% 9/30 [00:00<00:00, 23.16it/s]
2025-09-07T10:16:26.8182337Z running benchmark:  40% 12/30 [00:00<00:00, 23.18it/s]
2025-09-07T10:16:26.9469498Z running benchmark:  50% 15/30 [00:00<00:00, 23.15it/s]
2025-09-07T10:16:27.0754259Z running benchmark:  60% 18/30 [00:00<00:00, 23.20it/s]
2025-09-07T10:16:27.2045040Z running benchmark:  70% 21/30 [00:00<00:00, 23.25it/s]
2025-09-07T10:16:27.3354083Z running benchmark:  80% 24/30 [00:01<00:00, 23.25it/s]
2025-09-07T10:16:27.4638849Z running benchmark:  90% 27/30 [00:01<00:00, 23.14it/s]
2025-09-07T10:16:27.4639161Z running benchmark: 100% 30/30 [00:01<00:00, 23.21it/s]
2025-09-07T10:16:27.4639450Z running benchmark: 100% 30/30 [00:01<00:00, 23.17it/s]
2025-09-07T10:16:27.5116477Z 1.035x
2025-09-07T10:16:27.5119577Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:16:29.5022278Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:16:29.5023164Z   import pynvml  # type: ignore[import]
2025-09-07T10:16:31.5128218Z 
2025-09-07T10:16:32.9971387Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:16:32.9971689Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:16:32.9975092Z cpu  eval  basic_gnn_sage                     
2025-09-07T10:16:34.5622286Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5622733Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5623098Z     return mod(*inputs)
2025-09-07T10:16:34.5623474Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5623912Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5624164Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 228, in forward
2025-09-07T10:16:34.5624434Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5624706Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 182, in propagate
2025-09-07T10:16:34.5625120Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5625669Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5626199Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5626624Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5627037Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5627434Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5628152Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5628558Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5628940Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5629316Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter
2025-09-07T10:16:34.5629698Z     out = src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:34.5629867Z 
2025-09-07T10:16:34.5629976Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5630437Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5630772Z     return mod(*inputs)
2025-09-07T10:16:34.5631138Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5631519Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5631756Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 228, in forward
2025-09-07T10:16:34.5632023Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5632288Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 180, in propagate
2025-09-07T10:16:34.5632698Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T10:16:34.5632979Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 127, in _collect
2025-09-07T10:16:34.5633222Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T10:16:34.5633451Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 87, in _lift
2025-09-07T10:16:34.5633699Z     return src.index_select(self.node_dim, index)
2025-09-07T10:16:34.5633843Z 
2025-09-07T10:16:34.5633945Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5634311Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5634641Z     return mod(*inputs)
2025-09-07T10:16:34.5634990Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5635367Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5635600Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 228, in forward
2025-09-07T10:16:34.5635860Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5636120Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 182, in propagate
2025-09-07T10:16:34.5636448Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5636943Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5637396Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5637808Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5638221Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5638616Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5639014Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5639414Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5639788Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5640161Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T10:16:34.5640552Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T10:16:34.5640728Z 
2025-09-07T10:16:34.5640826Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5641190Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5641650Z     return mod(*inputs)
2025-09-07T10:16:34.5641986Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5642354Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5642590Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 228, in forward
2025-09-07T10:16:34.5642842Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5643100Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 182, in propagate
2025-09-07T10:16:34.5643422Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5643905Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5644400Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5644818Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5645219Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5645606Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5646108Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5646504Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5646878Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5647245Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T10:16:34.5647641Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T10:16:34.5647817Z 
2025-09-07T10:16:34.5647918Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5648294Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5648628Z     return mod(*inputs)
2025-09-07T10:16:34.5648963Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5649331Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5649568Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 228, in forward
2025-09-07T10:16:34.5649827Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5650090Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 182, in propagate
2025-09-07T10:16:34.5650420Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5650915Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5651358Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5651773Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5652177Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5652568Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5652971Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5653367Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5653735Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5654099Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter
2025-09-07T10:16:34.5654488Z     out = src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:34.5654654Z 
2025-09-07T10:16:34.5654752Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5655151Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5655479Z     return mod(*inputs)
2025-09-07T10:16:34.5655815Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5656189Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5656423Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 228, in forward
2025-09-07T10:16:34.5656681Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5656932Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 182, in propagate
2025-09-07T10:16:34.5657265Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5657783Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5658232Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5658641Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5659030Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5659482Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5659884Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5660279Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5660648Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5661015Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T10:16:34.5661416Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T10:16:34.5661591Z 
2025-09-07T10:16:34.5661693Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5662056Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5662378Z     return mod(*inputs)
2025-09-07T10:16:34.5662711Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5663094Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5663329Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 228, in forward
2025-09-07T10:16:34.5663587Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5663843Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 182, in propagate
2025-09-07T10:16:34.5664177Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5664662Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5665114Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5665526Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5665972Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5666370Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5666770Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5667167Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5667539Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5667906Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T10:16:34.5668300Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T10:16:34.5668517Z 
2025-09-07T10:16:34.5668616Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5668979Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5669301Z     return mod(*inputs)
2025-09-07T10:16:34.5669644Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5670013Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5670250Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 228, in forward
2025-09-07T10:16:34.5670510Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5670768Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 182, in propagate
2025-09-07T10:16:34.5671144Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5671629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5672073Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5672475Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5672870Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5673358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5673767Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5674165Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5674527Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5674901Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 82, in scatter
2025-09-07T10:16:34.5675289Z     out = src.new_zeros(size).scatter_add_(dim, index, src)
2025-09-07T10:16:34.5675450Z 
2025-09-07T10:16:34.5675557Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5675935Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5676262Z     return mod(*inputs)
2025-09-07T10:16:34.5676601Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5676984Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5677228Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 228, in forward
2025-09-07T10:16:34.5677488Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5677757Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 182, in propagate
2025-09-07T10:16:34.5678092Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5678586Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5679042Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5679457Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5679865Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5680258Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5680660Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5681062Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5681441Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5681817Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T10:16:34.5682255Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T10:16:34.5682430Z 
2025-09-07T10:16:34.5682533Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5682899Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5683226Z     return mod(*inputs)
2025-09-07T10:16:34.5683581Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5683953Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5684194Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 228, in forward
2025-09-07T10:16:34.5684457Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5684756Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 182, in propagate
2025-09-07T10:16:34.5685090Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5685580Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5686036Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5686453Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5686922Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5687317Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5687718Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5688120Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5688498Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5688868Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 78, in scatter
2025-09-07T10:16:34.5689260Z     count.scatter_add_(0, index, src.new_ones(src.size(dim)))
2025-09-07T10:16:34.5689432Z 
2025-09-07T10:16:34.5689555Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5689753Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5689987Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5690351Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5690681Z     return mod(*inputs)
2025-09-07T10:16:34.5691017Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5691393Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5691627Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 228, in forward
2025-09-07T10:16:34.5691888Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5692153Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 182, in propagate
2025-09-07T10:16:34.5692487Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5692979Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5693425Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5693839Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5694234Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5694624Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5695027Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5695423Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5695836Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5696199Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 84, in scatter
2025-09-07T10:16:34.5696560Z     return out / broadcast(count, out, dim)
2025-09-07T10:16:34.5696699Z 
2025-09-07T10:16:34.5696799Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5697159Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5697485Z     return mod(*inputs)
2025-09-07T10:16:34.5697820Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5698187Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5698457Z   File "/tmp/jenkins_pyg/tmp0c8ir_w3.py", line 229, in forward
2025-09-07T10:16:34.5698693Z     out = self.lin_l(out)
2025-09-07T10:16:34.5699175Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:34.5699558Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:34.5699711Z 
2025-09-07T10:16:34.5699788Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5700023Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5700497Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5700827Z     return mod(*inputs)
2025-09-07T10:16:34.5701172Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5701549Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5701784Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 228, in forward
2025-09-07T10:16:34.5702045Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5702308Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 180, in propagate
2025-09-07T10:16:34.5702587Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T10:16:34.5702861Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 127, in _collect
2025-09-07T10:16:34.5703100Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T10:16:34.5703325Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 87, in _lift
2025-09-07T10:16:34.5703574Z     return src.index_select(self.node_dim, index)
2025-09-07T10:16:34.5703719Z 
2025-09-07T10:16:34.5703800Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5704006Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5704229Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5704593Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5704922Z     return mod(*inputs)
2025-09-07T10:16:34.5705264Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5705698Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5705934Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 228, in forward
2025-09-07T10:16:34.5706186Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5706447Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 182, in propagate
2025-09-07T10:16:34.5706784Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5707271Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5707716Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5708126Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5708533Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5708928Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5709394Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5709794Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5710167Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5710544Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 84, in scatter
2025-09-07T10:16:34.5710899Z     return out / broadcast(count, out, dim)
2025-09-07T10:16:34.5711043Z 
2025-09-07T10:16:34.5711146Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5711503Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5712937Z     return mod(*inputs)
2025-09-07T10:16:34.5713283Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5713652Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5713890Z   File "/tmp/jenkins_pyg/tmpyj3_5x7o.py", line 229, in forward
2025-09-07T10:16:34.5714122Z     out = self.lin_l(out)
2025-09-07T10:16:34.5714461Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:34.5714829Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:34.5715047Z 
2025-09-07T10:16:34.5715146Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5715506Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5715832Z     return mod(*inputs)
2025-09-07T10:16:34.5716171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 234, in forward
2025-09-07T10:16:34.5716528Z     x = self.act(x)
2025-09-07T10:16:34.5716622Z 
2025-09-07T10:16:34.5716695Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5716922Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5717280Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5717599Z     return mod(*inputs)
2025-09-07T10:16:34.5717930Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5718302Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5718540Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 228, in forward
2025-09-07T10:16:34.5718801Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5719058Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 180, in propagate
2025-09-07T10:16:34.5719333Z     kwargs = self._collect(edge_index, the_size, in_kwargs)
2025-09-07T10:16:34.5719610Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 127, in _collect
2025-09-07T10:16:34.5719847Z     x_j = self._lift(x_j, edge_def, j)
2025-09-07T10:16:34.5720068Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 87, in _lift
2025-09-07T10:16:34.5720322Z     return src.index_select(self.node_dim, index)
2025-09-07T10:16:34.5720470Z 
2025-09-07T10:16:34.5720541Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5720744Z cudagraph partition due to non gpu ops
2025-09-07T10:16:34.5720961Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5721321Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5721648Z     return mod(*inputs)
2025-09-07T10:16:34.5721992Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5722360Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5722592Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 228, in forward
2025-09-07T10:16:34.5722852Z     out = self.propagate(edge_index, x=x, size=size)
2025-09-07T10:16:34.5723112Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 182, in propagate
2025-09-07T10:16:34.5723442Z     out = self.aggregate(out, ptr=kwargs.ptr, dim_size=kwargs.dim_size, index=kwargs.index)
2025-09-07T10:16:34.5723974Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/conv/message_passing.py", line 604, in aggregate
2025-09-07T10:16:34.5724418Z     return self.aggr_module(inputs, index, ptr=ptr, dim_size=dim_size,
2025-09-07T10:16:34.5724832Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 109, in __call__
2025-09-07T10:16:34.5725238Z     return super().__call__(x, index, ptr, dim_size, dim, **kwargs)
2025-09-07T10:16:34.5725636Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/basic.py", line 34, in forward
2025-09-07T10:16:34.5726084Z     return self.reduce(x, index, ptr, dim_size, dim, reduce='mean')
2025-09-07T10:16:34.5726481Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/aggr/base.py", line 155, in reduce
2025-09-07T10:16:34.5726855Z     return scatter(x, index, dim, dim_size, reduce)
2025-09-07T10:16:34.5727235Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/utils/scatter.py", line 84, in scatter
2025-09-07T10:16:34.5727604Z     return out / broadcast(count, out, dim)
2025-09-07T10:16:34.5727739Z 
2025-09-07T10:16:34.5727840Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5728274Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5728606Z     return mod(*inputs)
2025-09-07T10:16:34.5728956Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 226, in forward
2025-09-07T10:16:34.5729328Z     x = self.convs[i](x, edge_index)
2025-09-07T10:16:34.5729564Z   File "/tmp/jenkins_pyg/tmpqvibumku.py", line 229, in forward
2025-09-07T10:16:34.5729807Z     out = self.lin_l(out)
2025-09-07T10:16:34.5730152Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/dense/linear.py", line 132, in forward
2025-09-07T10:16:34.5730529Z     return F.linear(x, self.weight, self.bias)
2025-09-07T10:16:34.5730668Z 
2025-09-07T10:16:34.5730766Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:34.5731121Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:34.5731444Z     return mod(*inputs)
2025-09-07T10:16:34.5731791Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch_geometric/nn/models/basic_gnn.py", line 234, in forward
2025-09-07T10:16:34.5732151Z     x = self.act(x)
2025-09-07T10:16:34.5732245Z 
2025-09-07T10:16:34.5732319Z cudagraph partition due to non gpu ops
2025-09-07T10:16:40.0193623Z 
2025-09-07T10:16:40.1564498Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:16:40.2866241Z running benchmark:  10% 3/30 [00:00<00:01, 21.95it/s]
2025-09-07T10:16:40.4210375Z running benchmark:  20% 6/30 [00:00<00:01, 22.58it/s]
2025-09-07T10:16:40.5513986Z running benchmark:  30% 9/30 [00:00<00:00, 22.46it/s]
2025-09-07T10:16:40.6846538Z running benchmark:  40% 12/30 [00:00<00:00, 22.67it/s]
2025-09-07T10:16:40.8197013Z running benchmark:  50% 15/30 [00:00<00:00, 22.62it/s]
2025-09-07T10:16:40.9500321Z running benchmark:  60% 18/30 [00:00<00:00, 22.48it/s]
2025-09-07T10:16:41.0880825Z running benchmark:  70% 21/30 [00:00<00:00, 22.65it/s]
2025-09-07T10:16:41.2170814Z running benchmark:  80% 24/30 [00:01<00:00, 22.35it/s]
2025-09-07T10:16:41.3490388Z running benchmark:  90% 27/30 [00:01<00:00, 22.63it/s]
2025-09-07T10:16:41.3490734Z running benchmark: 100% 30/30 [00:01<00:00, 22.67it/s]
2025-09-07T10:16:41.3491011Z running benchmark: 100% 30/30 [00:01<00:00, 22.57it/s]
2025-09-07T10:16:41.3961148Z 0.999x
2025-09-07T10:16:41.3964519Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:16:43.4052363Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:16:43.4053592Z   import pynvml  # type: ignore[import]
2025-09-07T10:16:45.4239519Z 
2025-09-07T10:16:45.6723600Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:16:45.6723970Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:16:45.6735977Z cpu  eval  dcgan                              
2025-09-07T10:16:48.1241243Z cudagraph partition due to non gpu ops
2025-09-07T10:16:48.1241550Z cudagraph partition due to non gpu ops
2025-09-07T10:16:48.1241753Z cudagraph partition due to non gpu ops
2025-09-07T10:16:48.1241963Z cudagraph partition due to non gpu ops
2025-09-07T10:16:48.1242171Z cudagraph partition due to non gpu ops
2025-09-07T10:16:48.1242783Z cudagraph partition due to non gpu ops
2025-09-07T10:16:48.1243020Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1243419Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1243776Z     return mod(*inputs)
2025-09-07T10:16:48.1244063Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1244369Z     return self.main(input)
2025-09-07T10:16:48.1244493Z 
2025-09-07T10:16:48.1244602Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1245156Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1245499Z     return mod(*inputs)
2025-09-07T10:16:48.1245768Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1246066Z     return self.main(input)
2025-09-07T10:16:48.1246191Z 
2025-09-07T10:16:48.1246298Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1246669Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1246997Z     return mod(*inputs)
2025-09-07T10:16:48.1247262Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1247585Z     return self.main(input)
2025-09-07T10:16:48.1247701Z 
2025-09-07T10:16:48.1247798Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1248171Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1248503Z     return mod(*inputs)
2025-09-07T10:16:48.1248762Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1249059Z     return self.main(input)
2025-09-07T10:16:48.1249172Z 
2025-09-07T10:16:48.1249288Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1249643Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1249971Z     return mod(*inputs)
2025-09-07T10:16:48.1250228Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1250523Z     return self.main(input)
2025-09-07T10:16:48.1250629Z 
2025-09-07T10:16:48.1250735Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1251081Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1251396Z     return mod(*inputs)
2025-09-07T10:16:48.1251651Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1251938Z     return self.main(input)
2025-09-07T10:16:48.1252042Z 
2025-09-07T10:16:48.1252143Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:16:48.1252493Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:16:48.1252808Z     return mod(*inputs)
2025-09-07T10:16:48.1253060Z   File "/torchbench/torchbenchmark/models/dcgan/__init__.py", line 128, in forward
2025-09-07T10:16:48.1253350Z     return self.main(input)
2025-09-07T10:16:48.1253451Z 
2025-09-07T10:16:56.1229381Z 
2025-09-07T10:16:56.2292245Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:16:56.3431382Z running benchmark:  17% 5/30 [00:00<00:00, 47.18it/s]
2025-09-07T10:16:56.4562449Z running benchmark:  37% 11/30 [00:00<00:00, 50.48it/s]
2025-09-07T10:16:56.5691101Z running benchmark:  57% 17/30 [00:00<00:00, 51.68it/s]
2025-09-07T10:16:56.6831821Z running benchmark:  77% 23/30 [00:00<00:00, 52.29it/s]
2025-09-07T10:16:56.7019349Z running benchmark:  97% 29/30 [00:00<00:00, 52.40it/s]
2025-09-07T10:16:56.7019687Z running benchmark: 100% 30/30 [00:00<00:00, 51.82it/s]
2025-09-07T10:16:56.7549511Z 1.090x
2025-09-07T10:16:56.7552581Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:16:58.7130258Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:16:58.7131228Z   import pynvml  # type: ignore[import]
2025-09-07T10:17:00.7334306Z 
2025-09-07T10:17:02.4133790Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:17:02.4134081Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:17:02.4323026Z cpu  eval  demucs                             
2025-09-07T10:17:05.1302505Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:05.1302909Z    File "/torchbench/torchbenchmark/models/demucs/__init__.py", line 32, in forward
2025-09-07T10:17:05.1303243Z     mix = sources.sum(dim=1)
2025-09-07T10:17:05.1303367Z 
2025-09-07T10:17:10.6341557Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6341988Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6342358Z     x = encode(x)
2025-09-07T10:17:10.6342456Z 
2025-09-07T10:17:10.6342574Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6342950Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6343269Z     x = encode(x)
2025-09-07T10:17:10.6343365Z 
2025-09-07T10:17:10.6343471Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6343815Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6344134Z     x = encode(x)
2025-09-07T10:17:10.6344226Z 
2025-09-07T10:17:10.6344329Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6344685Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6344992Z     x = encode(x)
2025-09-07T10:17:10.6345080Z 
2025-09-07T10:17:10.6345188Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6345528Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6345865Z     x = encode(x)
2025-09-07T10:17:10.6345958Z 
2025-09-07T10:17:10.6346056Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6346397Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6346698Z     x = encode(x)
2025-09-07T10:17:10.6346784Z 
2025-09-07T10:17:10.6346884Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6347224Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6347523Z     x = encode(x)
2025-09-07T10:17:10.6347612Z 
2025-09-07T10:17:10.6347717Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6348053Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6348346Z     x = encode(x)
2025-09-07T10:17:10.6348440Z 
2025-09-07T10:17:10.6348537Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6348956Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6349571Z     x = encode(x)
2025-09-07T10:17:10.6349658Z 
2025-09-07T10:17:10.6349756Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6350091Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6350386Z     x = encode(x)
2025-09-07T10:17:10.6350471Z 
2025-09-07T10:17:10.6350582Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6350913Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6351204Z     x = encode(x)
2025-09-07T10:17:10.6351294Z 
2025-09-07T10:17:10.6351412Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6351739Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6352130Z     x = encode(x)
2025-09-07T10:17:10.6352216Z 
2025-09-07T10:17:10.6352319Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6352638Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6352943Z     x = encode(x)
2025-09-07T10:17:10.6353030Z 
2025-09-07T10:17:10.6353122Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6353452Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6353743Z     x = encode(x)
2025-09-07T10:17:10.6353978Z 
2025-09-07T10:17:10.6354075Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6354404Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6354695Z     x = encode(x)
2025-09-07T10:17:10.6354780Z 
2025-09-07T10:17:10.6354883Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6355206Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6355504Z     x = encode(x)
2025-09-07T10:17:10.6355596Z 
2025-09-07T10:17:10.6355691Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6356016Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6356314Z     x = encode(x)
2025-09-07T10:17:10.6356397Z 
2025-09-07T10:17:10.6356489Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6356817Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6357107Z     x = encode(x)
2025-09-07T10:17:10.6357189Z 
2025-09-07T10:17:10.6357294Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6357611Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6357904Z     x = encode(x)
2025-09-07T10:17:10.6357996Z 
2025-09-07T10:17:10.6358091Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6358420Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6358720Z     x = encode(x)
2025-09-07T10:17:10.6358802Z 
2025-09-07T10:17:10.6358893Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6359217Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6359509Z     x = encode(x)
2025-09-07T10:17:10.6359594Z 
2025-09-07T10:17:10.6359702Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6360022Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6360314Z     x = encode(x)
2025-09-07T10:17:10.6360408Z 
2025-09-07T10:17:10.6360500Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6360822Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6361118Z     x = encode(x)
2025-09-07T10:17:10.6361204Z 
2025-09-07T10:17:10.6361300Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:10.6361632Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 215, in forward
2025-09-07T10:17:10.6362045Z     x = encode(x)
2025-09-07T10:17:10.6362131Z 
2025-09-07T10:17:18.7210224Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7210733Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7211185Z     x = x + skip
2025-09-07T10:17:18.7211290Z 
2025-09-07T10:17:18.7211413Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7211847Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7212219Z     x = decode(x)
2025-09-07T10:17:18.7212314Z 
2025-09-07T10:17:18.7212744Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7213159Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7213535Z     x = decode(x)
2025-09-07T10:17:18.7213631Z 
2025-09-07T10:17:18.7213730Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7214140Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7214507Z     x = decode(x)
2025-09-07T10:17:18.7214589Z 
2025-09-07T10:17:18.7214843Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7215243Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7215637Z     x = x + skip
2025-09-07T10:17:18.7215749Z 
2025-09-07T10:17:18.7215848Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7216262Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7216633Z     x = decode(x)
2025-09-07T10:17:18.7216725Z 
2025-09-07T10:17:18.7216819Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7217228Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7217601Z     x = decode(x)
2025-09-07T10:17:18.7217686Z 
2025-09-07T10:17:18.7217787Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7218173Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7218541Z     x = decode(x)
2025-09-07T10:17:18.7218632Z 
2025-09-07T10:17:18.7218725Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7219129Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7219500Z     x = x + skip
2025-09-07T10:17:18.7219586Z 
2025-09-07T10:17:18.7219681Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7220081Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7220450Z     x = decode(x)
2025-09-07T10:17:18.7220532Z 
2025-09-07T10:17:18.7220632Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7221027Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7221397Z     x = decode(x)
2025-09-07T10:17:18.7221494Z 
2025-09-07T10:17:18.7221612Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7222009Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7222370Z     x = decode(x)
2025-09-07T10:17:18.7222452Z 
2025-09-07T10:17:18.7222554Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7222943Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7223302Z     x = x + skip
2025-09-07T10:17:18.7223480Z 
2025-09-07T10:17:18.7223573Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7223968Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7224327Z     x = decode(x)
2025-09-07T10:17:18.7224423Z 
2025-09-07T10:17:18.7224535Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7224928Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7225297Z     x = decode(x)
2025-09-07T10:17:18.7225380Z 
2025-09-07T10:17:18.7225480Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7225969Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7226338Z     x = decode(x)
2025-09-07T10:17:18.7226436Z 
2025-09-07T10:17:18.7226526Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7226927Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7227288Z     x = x + skip
2025-09-07T10:17:18.7227369Z 
2025-09-07T10:17:18.7227460Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7228154Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7228546Z     x = decode(x)
2025-09-07T10:17:18.7228632Z 
2025-09-07T10:17:18.7228739Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7229131Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7229489Z     x = decode(x)
2025-09-07T10:17:18.7229574Z 
2025-09-07T10:17:18.7229663Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7230054Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7230416Z     x = decode(x)
2025-09-07T10:17:18.7230496Z 
2025-09-07T10:17:18.7230589Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7230981Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 225, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7231338Z     x = x + skip
2025-09-07T10:17:18.7231423Z 
2025-09-07T10:17:18.7231528Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7231921Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7232272Z     x = decode(x)
2025-09-07T10:17:18.7232361Z 
2025-09-07T10:17:18.7232450Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7232842Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7233206Z     x = decode(x)
2025-09-07T10:17:18.7233289Z 
2025-09-07T10:17:18.7233398Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:18.7233803Z    File "/torchbench/torchbenchmark/models/demucs/demucs/model.py", line 226, in torch_dynamo_resume_in_forward_at_220
2025-09-07T10:17:18.7234169Z     x = decode(x)
2025-09-07T10:17:18.7234253Z 
2025-09-07T10:17:27.1118555Z 
2025-09-07T10:17:27.2430320Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:17:27.3699656Z running benchmark:   3% 1/30 [00:00<00:03,  7.64it/s]
2025-09-07T10:17:27.4965006Z running benchmark:   7% 2/30 [00:00<00:03,  7.78it/s]
2025-09-07T10:17:27.6225339Z running benchmark:  10% 3/30 [00:00<00:03,  7.83it/s]
2025-09-07T10:17:27.7499763Z running benchmark:  13% 4/30 [00:00<00:03,  7.87it/s]
2025-09-07T10:17:27.8778856Z running benchmark:  17% 5/30 [00:00<00:03,  7.86it/s]
2025-09-07T10:17:28.0049030Z running benchmark:  20% 6/30 [00:00<00:03,  7.85it/s]
2025-09-07T10:17:28.1320834Z running benchmark:  23% 7/30 [00:00<00:02,  7.86it/s]
2025-09-07T10:17:28.2590230Z running benchmark:  27% 8/30 [00:01<00:02,  7.86it/s]
2025-09-07T10:17:28.3848905Z running benchmark:  30% 9/30 [00:01<00:02,  7.86it/s]
2025-09-07T10:17:28.5112127Z running benchmark:  33% 10/30 [00:01<00:02,  7.89it/s]
2025-09-07T10:17:28.6396825Z running benchmark:  37% 11/30 [00:01<00:02,  7.90it/s]
2025-09-07T10:17:28.7681596Z running benchmark:  40% 12/30 [00:01<00:02,  7.86it/s]
2025-09-07T10:17:28.8964379Z running benchmark:  43% 13/30 [00:01<00:02,  7.84it/s]
2025-09-07T10:17:29.0229255Z running benchmark:  47% 14/30 [00:01<00:02,  7.83it/s]
2025-09-07T10:17:29.1512461Z running benchmark:  50% 15/30 [00:01<00:01,  7.85it/s]
2025-09-07T10:17:29.2805007Z running benchmark:  53% 16/30 [00:02<00:01,  7.83it/s]
2025-09-07T10:17:29.4070037Z running benchmark:  57% 17/30 [00:02<00:01,  7.80it/s]
2025-09-07T10:17:29.5361665Z running benchmark:  60% 18/30 [00:02<00:01,  7.83it/s]
2025-09-07T10:17:29.6652895Z running benchmark:  63% 19/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:17:29.7933536Z running benchmark:  67% 20/30 [00:02<00:01,  7.79it/s]
2025-09-07T10:17:29.9212676Z running benchmark:  70% 21/30 [00:02<00:01,  7.79it/s]
2025-09-07T10:17:30.0483299Z running benchmark:  73% 22/30 [00:02<00:01,  7.80it/s]
2025-09-07T10:17:30.1768187Z running benchmark:  77% 23/30 [00:02<00:00,  7.82it/s]
2025-09-07T10:17:30.3043216Z running benchmark:  80% 24/30 [00:03<00:00,  7.81it/s]
2025-09-07T10:17:30.4336187Z running benchmark:  83% 25/30 [00:03<00:00,  7.82it/s]
2025-09-07T10:17:30.5633715Z running benchmark:  87% 26/30 [00:03<00:00,  7.80it/s]
2025-09-07T10:17:30.6932700Z running benchmark:  90% 27/30 [00:03<00:00,  7.77it/s]
2025-09-07T10:17:30.8198462Z running benchmark:  93% 28/30 [00:03<00:00,  7.75it/s]
2025-09-07T10:17:30.9472916Z running benchmark:  97% 29/30 [00:03<00:00,  7.79it/s]
2025-09-07T10:17:30.9473288Z running benchmark: 100% 30/30 [00:03<00:00,  7.81it/s]
2025-09-07T10:17:30.9473582Z running benchmark: 100% 30/30 [00:03<00:00,  7.82it/s]
2025-09-07T10:17:31.0511135Z 1.044x
2025-09-07T10:17:31.0513969Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:17:33.1556735Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:17:33.1557644Z   import pynvml  # type: ignore[import]
2025-09-07T10:17:35.1763099Z 
2025-09-07T10:17:36.1794711Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:17:36.1794991Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:17:36.1950957Z cpu  eval  densenet121                        
2025-09-07T10:17:49.2182703Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2182990Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2183197Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2183396Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2183637Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2183836Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2184039Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2184242Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2184447Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2184665Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2184863Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2185053Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2185248Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2185444Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2185682Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2185884Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2186089Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2186291Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2186482Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2187010Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2187217Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2187411Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2187606Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2187792Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2187998Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2188201Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2188403Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2188589Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2188788Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2188982Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2189270Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2189458Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2189663Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2189864Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2190064Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2190255Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2190447Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2190641Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2190839Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2191184Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2191376Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2191574Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2191768Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2191979Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2192176Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2192366Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2192561Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2192756Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2192949Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2193144Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2193343Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2193536Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2193730Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2193917Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2194113Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2194309Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2194501Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2194691Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2194880Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2195098Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2195336Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2195730Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2196074Z     return mod(*inputs)
2025-09-07T10:17:49.2196451Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2196839Z     features = self.features(x)
2025-09-07T10:17:49.2196984Z 
2025-09-07T10:17:49.2197093Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2197474Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2197808Z     return mod(*inputs)
2025-09-07T10:17:49.2198136Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2198511Z     features = self.features(x)
2025-09-07T10:17:49.2198630Z 
2025-09-07T10:17:49.2198872Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2199254Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2199587Z     return mod(*inputs)
2025-09-07T10:17:49.2199914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2200353Z     features = self.features(x)
2025-09-07T10:17:49.2200468Z 
2025-09-07T10:17:49.2200579Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2200943Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2201266Z     return mod(*inputs)
2025-09-07T10:17:49.2201589Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2201957Z     features = self.features(x)
2025-09-07T10:17:49.2202318Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2202739Z     new_features = layer(features)
2025-09-07T10:17:49.2203092Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2203491Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2203900Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2204377Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2204610Z 
2025-09-07T10:17:49.2204826Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2205195Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2205525Z     return mod(*inputs)
2025-09-07T10:17:49.2205860Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2206223Z     features = self.features(x)
2025-09-07T10:17:49.2206555Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2206917Z     new_features = layer(features)
2025-09-07T10:17:49.2207270Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2207694Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2207885Z 
2025-09-07T10:17:49.2207993Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2208353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2208680Z     return mod(*inputs)
2025-09-07T10:17:49.2209006Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2209359Z     features = self.features(x)
2025-09-07T10:17:49.2209692Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2210051Z     new_features = layer(features)
2025-09-07T10:17:49.2210399Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2210815Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2211007Z 
2025-09-07T10:17:49.2211111Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2211467Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2211822Z     return mod(*inputs)
2025-09-07T10:17:49.2212152Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2212512Z     features = self.features(x)
2025-09-07T10:17:49.2212858Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2213224Z     new_features = layer(features)
2025-09-07T10:17:49.2213578Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2213967Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2214411Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2214788Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2214934Z 
2025-09-07T10:17:49.2215126Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2215490Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2215832Z     return mod(*inputs)
2025-09-07T10:17:49.2216156Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2216516Z     features = self.features(x)
2025-09-07T10:17:49.2216896Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2217260Z     new_features = layer(features)
2025-09-07T10:17:49.2217605Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2217987Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2218377Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2218909Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2219170Z 
2025-09-07T10:17:49.2219271Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2219644Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2219970Z     return mod(*inputs)
2025-09-07T10:17:49.2220307Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2220665Z     features = self.features(x)
2025-09-07T10:17:49.2221006Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2221361Z     new_features = layer(features)
2025-09-07T10:17:49.2221701Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2222090Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2222485Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2222949Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2223177Z 
2025-09-07T10:17:49.2223279Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2223630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2223958Z     return mod(*inputs)
2025-09-07T10:17:49.2224276Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2224632Z     features = self.features(x)
2025-09-07T10:17:49.2224962Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2225326Z     new_features = layer(features)
2025-09-07T10:17:49.2225751Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2226173Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2226369Z 
2025-09-07T10:17:49.2226472Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2226822Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2227155Z     return mod(*inputs)
2025-09-07T10:17:49.2227472Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2227829Z     features = self.features(x)
2025-09-07T10:17:49.2228236Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2228594Z     new_features = layer(features)
2025-09-07T10:17:49.2228941Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2229368Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2229563Z 
2025-09-07T10:17:49.2229673Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2230029Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2230362Z     return mod(*inputs)
2025-09-07T10:17:49.2230740Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2231101Z     features = self.features(x)
2025-09-07T10:17:49.2231435Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2231791Z     new_features = layer(features)
2025-09-07T10:17:49.2232135Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2232521Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2233038Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2233429Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2233567Z 
2025-09-07T10:17:49.2233665Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2234021Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2234356Z     return mod(*inputs)
2025-09-07T10:17:49.2234676Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2235036Z     features = self.features(x)
2025-09-07T10:17:49.2235376Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2235729Z     new_features = layer(features)
2025-09-07T10:17:49.2236083Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2236466Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2236852Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2237316Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2237557Z 
2025-09-07T10:17:49.2237655Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2238025Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2238356Z     return mod(*inputs)
2025-09-07T10:17:49.2238674Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2239043Z     features = self.features(x)
2025-09-07T10:17:49.2239392Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2239752Z     new_features = layer(features)
2025-09-07T10:17:49.2240099Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2240486Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2240886Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2241358Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2241583Z 
2025-09-07T10:17:49.2241694Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2242103Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2242430Z     return mod(*inputs)
2025-09-07T10:17:49.2242758Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2243123Z     features = self.features(x)
2025-09-07T10:17:49.2243461Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2243838Z     new_features = layer(features)
2025-09-07T10:17:49.2244188Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2244607Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2244837Z 
2025-09-07T10:17:49.2244953Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2245308Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2245641Z     return mod(*inputs)
2025-09-07T10:17:49.2245959Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2246316Z     features = self.features(x)
2025-09-07T10:17:49.2246718Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2247078Z     new_features = layer(features)
2025-09-07T10:17:49.2247422Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2247834Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2248026Z 
2025-09-07T10:17:49.2248133Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2248487Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2248814Z     return mod(*inputs)
2025-09-07T10:17:49.2249137Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2249495Z     features = self.features(x)
2025-09-07T10:17:49.2249838Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2250202Z     new_features = layer(features)
2025-09-07T10:17:49.2250553Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2250933Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2251326Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2251709Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2251848Z 
2025-09-07T10:17:49.2251950Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2252303Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2252631Z     return mod(*inputs)
2025-09-07T10:17:49.2252956Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2253307Z     features = self.features(x)
2025-09-07T10:17:49.2253647Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2254020Z     new_features = layer(features)
2025-09-07T10:17:49.2254385Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2254771Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2255164Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2255629Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2257056Z 
2025-09-07T10:17:49.2257157Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2257523Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2257856Z     return mod(*inputs)
2025-09-07T10:17:49.2258177Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2258539Z     features = self.features(x)
2025-09-07T10:17:49.2258877Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2259237Z     new_features = layer(features)
2025-09-07T10:17:49.2259573Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2260002Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2260398Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2260868Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2261101Z 
2025-09-07T10:17:49.2261208Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2261630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2261971Z     return mod(*inputs)
2025-09-07T10:17:49.2262298Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2262659Z     features = self.features(x)
2025-09-07T10:17:49.2263003Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2263353Z     new_features = layer(features)
2025-09-07T10:17:49.2263698Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2264146Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2264335Z 
2025-09-07T10:17:49.2264440Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2264792Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2265124Z     return mod(*inputs)
2025-09-07T10:17:49.2265446Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2265862Z     features = self.features(x)
2025-09-07T10:17:49.2266207Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2266564Z     new_features = layer(features)
2025-09-07T10:17:49.2266909Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2267326Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2267524Z 
2025-09-07T10:17:49.2267630Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2267989Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2268316Z     return mod(*inputs)
2025-09-07T10:17:49.2268641Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2268999Z     features = self.features(x)
2025-09-07T10:17:49.2269329Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2269675Z     new_features = layer(features)
2025-09-07T10:17:49.2270014Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2270401Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2270792Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2271223Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2271359Z 
2025-09-07T10:17:49.2271461Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2271822Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2272148Z     return mod(*inputs)
2025-09-07T10:17:49.2272477Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2272825Z     features = self.features(x)
2025-09-07T10:17:49.2273168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2273561Z     new_features = layer(features)
2025-09-07T10:17:49.2273906Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2274289Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2274675Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2275140Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2275376Z 
2025-09-07T10:17:49.2275542Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2275899Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2276229Z     return mod(*inputs)
2025-09-07T10:17:49.2276541Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2276895Z     features = self.features(x)
2025-09-07T10:17:49.2277233Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2277586Z     new_features = layer(features)
2025-09-07T10:17:49.2277925Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2278301Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2278688Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2279151Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2279377Z 
2025-09-07T10:17:49.2279482Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2279832Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2280157Z     return mod(*inputs)
2025-09-07T10:17:49.2280479Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2280834Z     features = self.features(x)
2025-09-07T10:17:49.2281168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2281527Z     new_features = layer(features)
2025-09-07T10:17:49.2281864Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2282278Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2282468Z 
2025-09-07T10:17:49.2282573Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2282921Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2283242Z     return mod(*inputs)
2025-09-07T10:17:49.2283564Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2283917Z     features = self.features(x)
2025-09-07T10:17:49.2284250Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2284645Z     new_features = layer(features)
2025-09-07T10:17:49.2284987Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2285400Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2285593Z 
2025-09-07T10:17:49.2285701Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2286048Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2286375Z     return mod(*inputs)
2025-09-07T10:17:49.2286705Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2287116Z     features = self.features(x)
2025-09-07T10:17:49.2287453Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2287802Z     new_features = layer(features)
2025-09-07T10:17:49.2288149Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2288528Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2288917Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2289359Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2289509Z 
2025-09-07T10:17:49.2289609Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2289962Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2290287Z     return mod(*inputs)
2025-09-07T10:17:49.2290606Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2290956Z     features = self.features(x)
2025-09-07T10:17:49.2291295Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2291661Z     new_features = layer(features)
2025-09-07T10:17:49.2292006Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2292388Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2292768Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2293231Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2293465Z 
2025-09-07T10:17:49.2293565Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2293921Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2294242Z     return mod(*inputs)
2025-09-07T10:17:49.2294569Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2294923Z     features = self.features(x)
2025-09-07T10:17:49.2295259Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2295613Z     new_features = layer(features)
2025-09-07T10:17:49.2295948Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2296336Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2296720Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2297178Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2297406Z 
2025-09-07T10:17:49.2297512Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2297861Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2298229Z     return mod(*inputs)
2025-09-07T10:17:49.2298571Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2299074Z     features = self.features(x)
2025-09-07T10:17:49.2299412Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2299780Z     new_features = layer(features)
2025-09-07T10:17:49.2300133Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2300557Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2300887Z 
2025-09-07T10:17:49.2300998Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2301427Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2301758Z     return mod(*inputs)
2025-09-07T10:17:49.2302086Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2302449Z     features = self.features(x)
2025-09-07T10:17:49.2302782Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2303143Z     new_features = layer(features)
2025-09-07T10:17:49.2303582Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2304011Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2304204Z 
2025-09-07T10:17:49.2304294Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2304527Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2304892Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2305217Z     return mod(*inputs)
2025-09-07T10:17:49.2305549Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2305998Z     features = self.features(x)
2025-09-07T10:17:49.2306348Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T10:17:49.2306703Z     return torch.cat(features, 1)
2025-09-07T10:17:49.2306823Z 
2025-09-07T10:17:49.2306932Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2307291Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2307609Z     return mod(*inputs)
2025-09-07T10:17:49.2307934Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2308292Z     features = self.features(x)
2025-09-07T10:17:49.2308403Z 
2025-09-07T10:17:49.2308508Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2308865Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2309182Z     return mod(*inputs)
2025-09-07T10:17:49.2309500Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2309852Z     features = self.features(x)
2025-09-07T10:17:49.2309965Z 
2025-09-07T10:17:49.2310071Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2310418Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2310739Z     return mod(*inputs)
2025-09-07T10:17:49.2311058Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2311412Z     features = self.features(x)
2025-09-07T10:17:49.2311752Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2312100Z     new_features = layer(features)
2025-09-07T10:17:49.2312510Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2312894Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2313290Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2313757Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2313997Z 
2025-09-07T10:17:49.2314098Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2314456Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2314781Z     return mod(*inputs)
2025-09-07T10:17:49.2315137Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2315489Z     features = self.features(x)
2025-09-07T10:17:49.2315830Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2316185Z     new_features = layer(features)
2025-09-07T10:17:49.2316534Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2316945Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2317260Z 
2025-09-07T10:17:49.2317360Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2317718Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2318055Z     return mod(*inputs)
2025-09-07T10:17:49.2318379Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2318729Z     features = self.features(x)
2025-09-07T10:17:49.2319060Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2331314Z     new_features = layer(features)
2025-09-07T10:17:49.2331733Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2332199Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2332398Z 
2025-09-07T10:17:49.2332514Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2332896Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2333235Z     return mod(*inputs)
2025-09-07T10:17:49.2333581Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2333948Z     features = self.features(x)
2025-09-07T10:17:49.2334287Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2334652Z     new_features = layer(features)
2025-09-07T10:17:49.2335010Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2335404Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2335795Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2336187Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2336334Z 
2025-09-07T10:17:49.2336435Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2336800Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2337128Z     return mod(*inputs)
2025-09-07T10:17:49.2337446Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2337805Z     features = self.features(x)
2025-09-07T10:17:49.2338150Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2338600Z     new_features = layer(features)
2025-09-07T10:17:49.2338950Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2339341Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2339741Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2340217Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2340449Z 
2025-09-07T10:17:49.2340559Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2340911Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2341280Z     return mod(*inputs)
2025-09-07T10:17:49.2341603Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2341963Z     features = self.features(x)
2025-09-07T10:17:49.2342304Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2342661Z     new_features = layer(features)
2025-09-07T10:17:49.2343080Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2343469Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2343864Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2344330Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2344562Z 
2025-09-07T10:17:49.2344663Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2345019Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2345346Z     return mod(*inputs)
2025-09-07T10:17:49.2345763Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2346126Z     features = self.features(x)
2025-09-07T10:17:49.2346462Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2346819Z     new_features = layer(features)
2025-09-07T10:17:49.2347165Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2347581Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2347773Z 
2025-09-07T10:17:49.2347869Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2348228Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2348554Z     return mod(*inputs)
2025-09-07T10:17:49.2348873Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2349221Z     features = self.features(x)
2025-09-07T10:17:49.2349562Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2349919Z     new_features = layer(features)
2025-09-07T10:17:49.2350263Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2350679Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2350869Z 
2025-09-07T10:17:49.2350968Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2351328Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2351654Z     return mod(*inputs)
2025-09-07T10:17:49.2351975Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2352375Z     features = self.features(x)
2025-09-07T10:17:49.2352701Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2353052Z     new_features = layer(features)
2025-09-07T10:17:49.2353410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2353785Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2354167Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2354547Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2354729Z 
2025-09-07T10:17:49.2354827Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2355185Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2355507Z     return mod(*inputs)
2025-09-07T10:17:49.2355819Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2356171Z     features = self.features(x)
2025-09-07T10:17:49.2356506Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2356928Z     new_features = layer(features)
2025-09-07T10:17:49.2357261Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2357639Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2358025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2358488Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2358715Z 
2025-09-07T10:17:49.2358820Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2359168Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2359496Z     return mod(*inputs)
2025-09-07T10:17:49.2359816Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2360169Z     features = self.features(x)
2025-09-07T10:17:49.2360509Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2360854Z     new_features = layer(features)
2025-09-07T10:17:49.2361192Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2361565Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2361952Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2362401Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2362636Z 
2025-09-07T10:17:49.2362734Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2363089Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2363417Z     return mod(*inputs)
2025-09-07T10:17:49.2363734Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2364080Z     features = self.features(x)
2025-09-07T10:17:49.2364410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2364765Z     new_features = layer(features)
2025-09-07T10:17:49.2365103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2365515Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2365707Z 
2025-09-07T10:17:49.2365850Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2366202Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2366529Z     return mod(*inputs)
2025-09-07T10:17:49.2366848Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2367197Z     features = self.features(x)
2025-09-07T10:17:49.2367532Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2367888Z     new_features = layer(features)
2025-09-07T10:17:49.2368226Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2368673Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2368864Z 
2025-09-07T10:17:49.2368967Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2369328Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2369650Z     return mod(*inputs)
2025-09-07T10:17:49.2369968Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2370311Z     features = self.features(x)
2025-09-07T10:17:49.2370710Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2371068Z     new_features = layer(features)
2025-09-07T10:17:49.2371411Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2371789Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2372171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2372554Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2372697Z 
2025-09-07T10:17:49.2372794Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2373151Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2373468Z     return mod(*inputs)
2025-09-07T10:17:49.2373784Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2374135Z     features = self.features(x)
2025-09-07T10:17:49.2374470Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2374818Z     new_features = layer(features)
2025-09-07T10:17:49.2375148Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2375524Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2375912Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2376375Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2376602Z 
2025-09-07T10:17:49.2376704Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2377053Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2377377Z     return mod(*inputs)
2025-09-07T10:17:49.2377698Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2378055Z     features = self.features(x)
2025-09-07T10:17:49.2378388Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2378746Z     new_features = layer(features)
2025-09-07T10:17:49.2379088Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2379512Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2379900Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2380354Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2380590Z 
2025-09-07T10:17:49.2380694Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2381051Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2381375Z     return mod(*inputs)
2025-09-07T10:17:49.2381692Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2382081Z     features = self.features(x)
2025-09-07T10:17:49.2382410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2382764Z     new_features = layer(features)
2025-09-07T10:17:49.2383106Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2383516Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2383716Z 
2025-09-07T10:17:49.2383813Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2384238Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2384564Z     return mod(*inputs)
2025-09-07T10:17:49.2384881Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2385227Z     features = self.features(x)
2025-09-07T10:17:49.2385574Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2385995Z     new_features = layer(features)
2025-09-07T10:17:49.2386345Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2386766Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2386954Z 
2025-09-07T10:17:49.2387054Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2387433Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2387749Z     return mod(*inputs)
2025-09-07T10:17:49.2388087Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2388425Z     features = self.features(x)
2025-09-07T10:17:49.2388788Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2389137Z     new_features = layer(features)
2025-09-07T10:17:49.2389476Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2389871Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2390249Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2390633Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2390774Z 
2025-09-07T10:17:49.2390873Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2391225Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2391560Z     return mod(*inputs)
2025-09-07T10:17:49.2391863Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2392212Z     features = self.features(x)
2025-09-07T10:17:49.2392562Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2392912Z     new_features = layer(features)
2025-09-07T10:17:49.2393321Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2393710Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2394094Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2394575Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2394803Z 
2025-09-07T10:17:49.2394901Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2395267Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2395585Z     return mod(*inputs)
2025-09-07T10:17:49.2395964Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2396321Z     features = self.features(x)
2025-09-07T10:17:49.2396645Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2397019Z     new_features = layer(features)
2025-09-07T10:17:49.2397360Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2397729Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2398217Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2398679Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2399115Z 
2025-09-07T10:17:49.2399216Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2399597Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2399912Z     return mod(*inputs)
2025-09-07T10:17:49.2400228Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2400597Z     features = self.features(x)
2025-09-07T10:17:49.2400926Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2401305Z     new_features = layer(features)
2025-09-07T10:17:49.2401640Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2402045Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2402244Z 
2025-09-07T10:17:49.2402338Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2402682Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2402997Z     return mod(*inputs)
2025-09-07T10:17:49.2403306Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2403648Z     features = self.features(x)
2025-09-07T10:17:49.2403976Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2404330Z     new_features = layer(features)
2025-09-07T10:17:49.2404665Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2405066Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2405256Z 
2025-09-07T10:17:49.2405350Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2405699Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2406012Z     return mod(*inputs)
2025-09-07T10:17:49.2406324Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2406663Z     features = self.features(x)
2025-09-07T10:17:49.2406993Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2407438Z     new_features = layer(features)
2025-09-07T10:17:49.2407780Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2408159Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2408545Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2408919Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2409057Z 
2025-09-07T10:17:49.2409154Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2409505Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2409873Z     return mod(*inputs)
2025-09-07T10:17:49.2410191Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2410545Z     features = self.features(x)
2025-09-07T10:17:49.2410874Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2411222Z     new_features = layer(features)
2025-09-07T10:17:49.2411650Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2412032Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2412415Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2412872Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2413103Z 
2025-09-07T10:17:49.2413201Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2413545Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2413864Z     return mod(*inputs)
2025-09-07T10:17:49.2414176Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2414528Z     features = self.features(x)
2025-09-07T10:17:49.2414851Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2415200Z     new_features = layer(features)
2025-09-07T10:17:49.2415546Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2415922Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2416306Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2416759Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2416990Z 
2025-09-07T10:17:49.2417086Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2417459Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2417778Z     return mod(*inputs)
2025-09-07T10:17:49.2418086Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2418434Z     features = self.features(x)
2025-09-07T10:17:49.2418763Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2419108Z     new_features = layer(features)
2025-09-07T10:17:49.2419443Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2419844Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2420038Z 
2025-09-07T10:17:49.2420132Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2420479Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2420848Z     return mod(*inputs)
2025-09-07T10:17:49.2421160Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2421501Z     features = self.features(x)
2025-09-07T10:17:49.2421828Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2422176Z     new_features = layer(features)
2025-09-07T10:17:49.2422507Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2422911Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2423139Z 
2025-09-07T10:17:49.2423235Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2423577Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2423893Z     return mod(*inputs)
2025-09-07T10:17:49.2424203Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2424546Z     features = self.features(x)
2025-09-07T10:17:49.2424869Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2425278Z     new_features = layer(features)
2025-09-07T10:17:49.2425687Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2426065Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2426451Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2426833Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2426968Z 
2025-09-07T10:17:49.2427075Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2427432Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2427751Z     return mod(*inputs)
2025-09-07T10:17:49.2428063Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2428413Z     features = self.features(x)
2025-09-07T10:17:49.2428747Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2429083Z     new_features = layer(features)
2025-09-07T10:17:49.2429415Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2429787Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2430173Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2430632Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2430858Z 
2025-09-07T10:17:49.2430954Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2431303Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2431619Z     return mod(*inputs)
2025-09-07T10:17:49.2431936Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2432285Z     features = self.features(x)
2025-09-07T10:17:49.2432616Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2432961Z     new_features = layer(features)
2025-09-07T10:17:49.2433297Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2433673Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2434048Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2434553Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2434782Z 
2025-09-07T10:17:49.2434876Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2435230Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2435542Z     return mod(*inputs)
2025-09-07T10:17:49.2435853Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2436203Z     features = self.features(x)
2025-09-07T10:17:49.2436529Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2436954Z     new_features = layer(features)
2025-09-07T10:17:49.2437292Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2437700Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2437892Z 
2025-09-07T10:17:49.2437989Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2438341Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2439135Z     return mod(*inputs)
2025-09-07T10:17:49.2439455Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2439804Z     features = self.features(x)
2025-09-07T10:17:49.2440129Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2440475Z     new_features = layer(features)
2025-09-07T10:17:49.2440814Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2441224Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2441423Z 
2025-09-07T10:17:49.2441522Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2441872Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2442196Z     return mod(*inputs)
2025-09-07T10:17:49.2442515Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2442864Z     features = self.features(x)
2025-09-07T10:17:49.2443194Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2443546Z     new_features = layer(features)
2025-09-07T10:17:49.2443891Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2444259Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2444647Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2445023Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2445160Z 
2025-09-07T10:17:49.2445261Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2445609Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2445925Z     return mod(*inputs)
2025-09-07T10:17:49.2446237Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2446582Z     features = self.features(x)
2025-09-07T10:17:49.2446903Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2447248Z     new_features = layer(features)
2025-09-07T10:17:49.2447587Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2448043Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2448431Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2448892Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2449119Z 
2025-09-07T10:17:49.2449222Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2449577Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2449893Z     return mod(*inputs)
2025-09-07T10:17:49.2450207Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2450595Z     features = self.features(x)
2025-09-07T10:17:49.2450927Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2451273Z     new_features = layer(features)
2025-09-07T10:17:49.2451610Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2451986Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2452365Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2452902Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2453133Z 
2025-09-07T10:17:49.2453228Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2453594Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2453912Z     return mod(*inputs)
2025-09-07T10:17:49.2454225Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2454572Z     features = self.features(x)
2025-09-07T10:17:49.2454909Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2455254Z     new_features = layer(features)
2025-09-07T10:17:49.2455587Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2456002Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2456207Z 
2025-09-07T10:17:49.2456304Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2456651Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2456972Z     return mod(*inputs)
2025-09-07T10:17:49.2457279Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2457643Z     features = self.features(x)
2025-09-07T10:17:49.2457969Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2458332Z     new_features = layer(features)
2025-09-07T10:17:49.2458667Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2459072Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2459261Z 
2025-09-07T10:17:49.2459357Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2459695Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2460029Z     return mod(*inputs)
2025-09-07T10:17:49.2460357Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2460703Z     features = self.features(x)
2025-09-07T10:17:49.2461036Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2461378Z     new_features = layer(features)
2025-09-07T10:17:49.2461751Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2462129Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2462509Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2462879Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2463025Z 
2025-09-07T10:17:49.2463124Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2463494Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2463810Z     return mod(*inputs)
2025-09-07T10:17:49.2464156Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2464505Z     features = self.features(x)
2025-09-07T10:17:49.2464827Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2465170Z     new_features = layer(features)
2025-09-07T10:17:49.2465503Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2465944Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2466403Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2466879Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2467107Z 
2025-09-07T10:17:49.2467203Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2467550Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2467892Z     return mod(*inputs)
2025-09-07T10:17:49.2468201Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2468543Z     features = self.features(x)
2025-09-07T10:17:49.2468886Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2469228Z     new_features = layer(features)
2025-09-07T10:17:49.2469571Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2469941Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2470317Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2470786Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2471019Z 
2025-09-07T10:17:49.2471112Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2471472Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2471791Z     return mod(*inputs)
2025-09-07T10:17:49.2472098Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2472444Z     features = self.features(x)
2025-09-07T10:17:49.2472773Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2473116Z     new_features = layer(features)
2025-09-07T10:17:49.2473465Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2473870Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2474059Z 
2025-09-07T10:17:49.2474176Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2474520Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2474843Z     return mod(*inputs)
2025-09-07T10:17:49.2475202Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2475543Z     features = self.features(x)
2025-09-07T10:17:49.2475864Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2476243Z     new_features = layer(features)
2025-09-07T10:17:49.2476576Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2477001Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2477192Z 
2025-09-07T10:17:49.2477285Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2477681Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2477995Z     return mod(*inputs)
2025-09-07T10:17:49.2478303Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2478669Z     features = self.features(x)
2025-09-07T10:17:49.2478989Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2479351Z     new_features = layer(features)
2025-09-07T10:17:49.2479752Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2480137Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2480535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2480901Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2481052Z 
2025-09-07T10:17:49.2481154Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2481491Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2481806Z     return mod(*inputs)
2025-09-07T10:17:49.2482132Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2482484Z     features = self.features(x)
2025-09-07T10:17:49.2482821Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2483164Z     new_features = layer(features)
2025-09-07T10:17:49.2483497Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2483882Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2484278Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2484730Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2484961Z 
2025-09-07T10:17:49.2485053Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2485426Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2485761Z     return mod(*inputs)
2025-09-07T10:17:49.2486075Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2486413Z     features = self.features(x)
2025-09-07T10:17:49.2486765Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2487109Z     new_features = layer(features)
2025-09-07T10:17:49.2487450Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2487855Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2488234Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2488707Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2489005Z 
2025-09-07T10:17:49.2489108Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2489471Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2489808Z     return mod(*inputs)
2025-09-07T10:17:49.2490137Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2490499Z     features = self.features(x)
2025-09-07T10:17:49.2490833Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2491181Z     new_features = layer(features)
2025-09-07T10:17:49.2491571Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2491981Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2492174Z 
2025-09-07T10:17:49.2492270Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2492630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2492960Z     return mod(*inputs)
2025-09-07T10:17:49.2493368Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2493733Z     features = self.features(x)
2025-09-07T10:17:49.2494067Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2494415Z     new_features = layer(features)
2025-09-07T10:17:49.2494774Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2495192Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2495402Z 
2025-09-07T10:17:49.2495496Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2495847Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2496161Z     return mod(*inputs)
2025-09-07T10:17:49.2496491Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2496846Z     features = self.features(x)
2025-09-07T10:17:49.2497173Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2497521Z     new_features = layer(features)
2025-09-07T10:17:49.2497866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2498240Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2498638Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2499177Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2499318Z 
2025-09-07T10:17:49.2499421Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2499790Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2500107Z     return mod(*inputs)
2025-09-07T10:17:49.2500429Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2500780Z     features = self.features(x)
2025-09-07T10:17:49.2501122Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2501474Z     new_features = layer(features)
2025-09-07T10:17:49.2501824Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2502207Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2502589Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2503142Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2503377Z 
2025-09-07T10:17:49.2503474Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2503834Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2504175Z     return mod(*inputs)
2025-09-07T10:17:49.2504499Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2504847Z     features = self.features(x)
2025-09-07T10:17:49.2505192Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2505603Z     new_features = layer(features)
2025-09-07T10:17:49.2506004Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2506379Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2506781Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2507241Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2507504Z 
2025-09-07T10:17:49.2507691Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2508057Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2508374Z     return mod(*inputs)
2025-09-07T10:17:49.2508698Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2509078Z     features = self.features(x)
2025-09-07T10:17:49.2509416Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2509765Z     new_features = layer(features)
2025-09-07T10:17:49.2510107Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2510522Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2510716Z 
2025-09-07T10:17:49.2510828Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2511188Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2511509Z     return mod(*inputs)
2025-09-07T10:17:49.2511830Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2512198Z     features = self.features(x)
2025-09-07T10:17:49.2512536Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2512895Z     new_features = layer(features)
2025-09-07T10:17:49.2513228Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2513643Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2513844Z 
2025-09-07T10:17:49.2513937Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2514291Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2514619Z     return mod(*inputs)
2025-09-07T10:17:49.2514930Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2515279Z     features = self.features(x)
2025-09-07T10:17:49.2515621Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2515975Z     new_features = layer(features)
2025-09-07T10:17:49.2516298Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2516733Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2517135Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2517515Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2517651Z 
2025-09-07T10:17:49.2517759Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2518112Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2518440Z     return mod(*inputs)
2025-09-07T10:17:49.2518760Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2519167Z     features = self.features(x)
2025-09-07T10:17:49.2519497Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2519847Z     new_features = layer(features)
2025-09-07T10:17:49.2520189Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2520571Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2520961Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2521484Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2521721Z 
2025-09-07T10:17:49.2521823Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2522180Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2522505Z     return mod(*inputs)
2025-09-07T10:17:49.2522823Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2523166Z     features = self.features(x)
2025-09-07T10:17:49.2523496Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2523848Z     new_features = layer(features)
2025-09-07T10:17:49.2524189Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2524559Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2524945Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2525405Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2525630Z 
2025-09-07T10:17:49.2525735Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2526088Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2526401Z     return mod(*inputs)
2025-09-07T10:17:49.2526721Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2527078Z     features = self.features(x)
2025-09-07T10:17:49.2527419Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2527766Z     new_features = layer(features)
2025-09-07T10:17:49.2528110Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2528530Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2528722Z 
2025-09-07T10:17:49.2528830Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2529188Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2529507Z     return mod(*inputs)
2025-09-07T10:17:49.2529830Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2530262Z     features = self.features(x)
2025-09-07T10:17:49.2530592Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2530947Z     new_features = layer(features)
2025-09-07T10:17:49.2531284Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2531695Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2531888Z 
2025-09-07T10:17:49.2531965Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2532175Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2532363Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2532561Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2532797Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2533003Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2533222Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2533583Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2533911Z     return mod(*inputs)
2025-09-07T10:17:49.2534245Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2534598Z     features = self.features(x)
2025-09-07T10:17:49.2535011Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T10:17:49.2535376Z     return torch.cat(features, 1)
2025-09-07T10:17:49.2535501Z 
2025-09-07T10:17:49.2535603Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2535963Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2536286Z     return mod(*inputs)
2025-09-07T10:17:49.2536620Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2536975Z     features = self.features(x)
2025-09-07T10:17:49.2537090Z 
2025-09-07T10:17:49.2537413Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2537767Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2538081Z     return mod(*inputs)
2025-09-07T10:17:49.2538407Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2538758Z     features = self.features(x)
2025-09-07T10:17:49.2538867Z 
2025-09-07T10:17:49.2538969Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2539313Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2539628Z     return mod(*inputs)
2025-09-07T10:17:49.2539951Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2540302Z     features = self.features(x)
2025-09-07T10:17:49.2540636Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2540986Z     new_features = layer(features)
2025-09-07T10:17:49.2541333Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2541715Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2542106Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2542571Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2542802Z 
2025-09-07T10:17:49.2542903Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2543259Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2543582Z     return mod(*inputs)
2025-09-07T10:17:49.2543948Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2544296Z     features = self.features(x)
2025-09-07T10:17:49.2544623Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2544976Z     new_features = layer(features)
2025-09-07T10:17:49.2545326Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2545805Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2545997Z 
2025-09-07T10:17:49.2546094Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2546489Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2546815Z     return mod(*inputs)
2025-09-07T10:17:49.2547137Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2547496Z     features = self.features(x)
2025-09-07T10:17:49.2547821Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2548173Z     new_features = layer(features)
2025-09-07T10:17:49.2548579Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2548997Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2549185Z 
2025-09-07T10:17:49.2549282Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2549642Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2549966Z     return mod(*inputs)
2025-09-07T10:17:49.2550287Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2550637Z     features = self.features(x)
2025-09-07T10:17:49.2550966Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2551039Z     new_features = layer(features)
2025-09-07T10:17:49.2551257Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2551356Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2551585Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2551667Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2551670Z 
2025-09-07T10:17:49.2551773Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2551970Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2552035Z     return mod(*inputs)
2025-09-07T10:17:49.2552255Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2552332Z     features = self.features(x)
2025-09-07T10:17:49.2552567Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2552634Z     new_features = layer(features)
2025-09-07T10:17:49.2552863Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2552959Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2553192Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2553361Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2553365Z 
2025-09-07T10:17:49.2553467Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2553672Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2553775Z     return mod(*inputs)
2025-09-07T10:17:49.2554001Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2554068Z     features = self.features(x)
2025-09-07T10:17:49.2554293Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2554367Z     new_features = layer(features)
2025-09-07T10:17:49.2554585Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2554686Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2554957Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2555122Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2555132Z 
2025-09-07T10:17:49.2555230Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2555425Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2555489Z     return mod(*inputs)
2025-09-07T10:17:49.2555774Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2555843Z     features = self.features(x)
2025-09-07T10:17:49.2556063Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2556130Z     new_features = layer(features)
2025-09-07T10:17:49.2556351Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2556484Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2556487Z 
2025-09-07T10:17:49.2556587Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2556784Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2556843Z     return mod(*inputs)
2025-09-07T10:17:49.2557065Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2557130Z     features = self.features(x)
2025-09-07T10:17:49.2557356Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2557420Z     new_features = layer(features)
2025-09-07T10:17:49.2557639Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2557770Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2557772Z 
2025-09-07T10:17:49.2557865Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2558066Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2558126Z     return mod(*inputs)
2025-09-07T10:17:49.2558345Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2558405Z     features = self.features(x)
2025-09-07T10:17:49.2558624Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2558695Z     new_features = layer(features)
2025-09-07T10:17:49.2558914Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2559012Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2559240Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2559319Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2559327Z 
2025-09-07T10:17:49.2559424Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2559660Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2559723Z     return mod(*inputs)
2025-09-07T10:17:49.2559940Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2560013Z     features = self.features(x)
2025-09-07T10:17:49.2560227Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2560293Z     new_features = layer(features)
2025-09-07T10:17:49.2560510Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2560641Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2560872Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2561043Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2561047Z 
2025-09-07T10:17:49.2561144Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2561343Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2561401Z     return mod(*inputs)
2025-09-07T10:17:49.2561688Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2561755Z     features = self.features(x)
2025-09-07T10:17:49.2561972Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2562046Z     new_features = layer(features)
2025-09-07T10:17:49.2562257Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2562357Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2562585Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2562754Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2562757Z 
2025-09-07T10:17:49.2562853Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2563045Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2563113Z     return mod(*inputs)
2025-09-07T10:17:49.2563331Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2563400Z     features = self.features(x)
2025-09-07T10:17:49.2563616Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2563681Z     new_features = layer(features)
2025-09-07T10:17:49.2563901Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2564030Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2564033Z 
2025-09-07T10:17:49.2564129Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2564320Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2564382Z     return mod(*inputs)
2025-09-07T10:17:49.2564596Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2564659Z     features = self.features(x)
2025-09-07T10:17:49.2564882Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2564949Z     new_features = layer(features)
2025-09-07T10:17:49.2565172Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2565339Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2565342Z 
2025-09-07T10:17:49.2565433Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2565634Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2565697Z     return mod(*inputs)
2025-09-07T10:17:49.2565917Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2565981Z     features = self.features(x)
2025-09-07T10:17:49.2566203Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2566308Z     new_features = layer(features)
2025-09-07T10:17:49.2566527Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2566627Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2566859Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2566943Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2566946Z 
2025-09-07T10:17:49.2567043Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2567316Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2567380Z     return mod(*inputs)
2025-09-07T10:17:49.2567598Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2567669Z     features = self.features(x)
2025-09-07T10:17:49.2567883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2567951Z     new_features = layer(features)
2025-09-07T10:17:49.2568170Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2568265Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2568498Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2568661Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2568667Z 
2025-09-07T10:17:49.2568766Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2568958Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2569016Z     return mod(*inputs)
2025-09-07T10:17:49.2569235Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2569300Z     features = self.features(x)
2025-09-07T10:17:49.2569522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2569587Z     new_features = layer(features)
2025-09-07T10:17:49.2569804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2569902Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2570130Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2570293Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2570295Z 
2025-09-07T10:17:49.2570389Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2570577Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2570642Z     return mod(*inputs)
2025-09-07T10:17:49.2570856Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2570961Z     features = self.features(x)
2025-09-07T10:17:49.2571178Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2571250Z     new_features = layer(features)
2025-09-07T10:17:49.2571468Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2571598Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2571602Z 
2025-09-07T10:17:49.2571699Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2571891Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2571958Z     return mod(*inputs)
2025-09-07T10:17:49.2572208Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2572274Z     features = self.features(x)
2025-09-07T10:17:49.2572496Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2572564Z     new_features = layer(features)
2025-09-07T10:17:49.2572783Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2572973Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2572976Z 
2025-09-07T10:17:49.2573072Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2573272Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2573335Z     return mod(*inputs)
2025-09-07T10:17:49.2573556Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2573619Z     features = self.features(x)
2025-09-07T10:17:49.2573838Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2573903Z     new_features = layer(features)
2025-09-07T10:17:49.2574117Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2574231Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2574456Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2574537Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2574540Z 
2025-09-07T10:17:49.2574634Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2574832Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2574895Z     return mod(*inputs)
2025-09-07T10:17:49.2575114Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2575179Z     features = self.features(x)
2025-09-07T10:17:49.2575393Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2575456Z     new_features = layer(features)
2025-09-07T10:17:49.2575673Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2575769Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2576003Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2576166Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2576169Z 
2025-09-07T10:17:49.2576271Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2576469Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2576529Z     return mod(*inputs)
2025-09-07T10:17:49.2576756Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2576858Z     features = self.features(x)
2025-09-07T10:17:49.2577081Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2577148Z     new_features = layer(features)
2025-09-07T10:17:49.2577368Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2577469Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2577697Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2577903Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2577906Z 
2025-09-07T10:17:49.2578001Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2578205Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2578268Z     return mod(*inputs)
2025-09-07T10:17:49.2578488Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2578561Z     features = self.features(x)
2025-09-07T10:17:49.2578845Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2578920Z     new_features = layer(features)
2025-09-07T10:17:49.2579135Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2579262Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2579267Z 
2025-09-07T10:17:49.2579371Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2579565Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2579637Z     return mod(*inputs)
2025-09-07T10:17:49.2579858Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2579921Z     features = self.features(x)
2025-09-07T10:17:49.2580146Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2580214Z     new_features = layer(features)
2025-09-07T10:17:49.2580437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2580572Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2580575Z 
2025-09-07T10:17:49.2580682Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2580895Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2580955Z     return mod(*inputs)
2025-09-07T10:17:49.2581178Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2581243Z     features = self.features(x)
2025-09-07T10:17:49.2581467Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2581531Z     new_features = layer(features)
2025-09-07T10:17:49.2581747Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2581850Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2582134Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2582276Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2582278Z 
2025-09-07T10:17:49.2582414Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2582766Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2582931Z     return mod(*inputs)
2025-09-07T10:17:49.2583161Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2591261Z     features = self.features(x)
2025-09-07T10:17:49.2591565Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2591640Z     new_features = layer(features)
2025-09-07T10:17:49.2591885Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2591986Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2592239Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2592505Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2592509Z 
2025-09-07T10:17:49.2592626Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2592831Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2592893Z     return mod(*inputs)
2025-09-07T10:17:49.2593127Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2593261Z     features = self.features(x)
2025-09-07T10:17:49.2593496Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2593565Z     new_features = layer(features)
2025-09-07T10:17:49.2593788Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2593894Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2594129Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2594303Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2594306Z 
2025-09-07T10:17:49.2594409Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2594613Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2594678Z     return mod(*inputs)
2025-09-07T10:17:49.2594905Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2594978Z     features = self.features(x)
2025-09-07T10:17:49.2595198Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2595272Z     new_features = layer(features)
2025-09-07T10:17:49.2595491Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2595627Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2595632Z 
2025-09-07T10:17:49.2595736Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2595934Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2595998Z     return mod(*inputs)
2025-09-07T10:17:49.2596219Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2596285Z     features = self.features(x)
2025-09-07T10:17:49.2596505Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2596569Z     new_features = layer(features)
2025-09-07T10:17:49.2596792Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2596913Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2596916Z 
2025-09-07T10:17:49.2597052Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2597250Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2597310Z     return mod(*inputs)
2025-09-07T10:17:49.2597535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2597598Z     features = self.features(x)
2025-09-07T10:17:49.2597822Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2597887Z     new_features = layer(features)
2025-09-07T10:17:49.2598103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2598254Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2598481Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2598571Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2598575Z 
2025-09-07T10:17:49.2598671Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2599038Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2599106Z     return mod(*inputs)
2025-09-07T10:17:49.2599440Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2599512Z     features = self.features(x)
2025-09-07T10:17:49.2599730Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2599797Z     new_features = layer(features)
2025-09-07T10:17:49.2600015Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2600110Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2600358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2600523Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2600527Z 
2025-09-07T10:17:49.2600634Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2600835Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2600893Z     return mod(*inputs)
2025-09-07T10:17:49.2601123Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2601186Z     features = self.features(x)
2025-09-07T10:17:49.2601419Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2601485Z     new_features = layer(features)
2025-09-07T10:17:49.2601704Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2601803Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2602032Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2602199Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2602203Z 
2025-09-07T10:17:49.2602299Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2602502Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2602559Z     return mod(*inputs)
2025-09-07T10:17:49.2602779Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2602846Z     features = self.features(x)
2025-09-07T10:17:49.2603061Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2603181Z     new_features = layer(features)
2025-09-07T10:17:49.2603410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2603539Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2603547Z 
2025-09-07T10:17:49.2603645Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2603841Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2603904Z     return mod(*inputs)
2025-09-07T10:17:49.2604130Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2604248Z     features = self.features(x)
2025-09-07T10:17:49.2604469Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2604533Z     new_features = layer(features)
2025-09-07T10:17:49.2604762Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2604889Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2604892Z 
2025-09-07T10:17:49.2604990Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2605245Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2605307Z     return mod(*inputs)
2025-09-07T10:17:49.2605529Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2605592Z     features = self.features(x)
2025-09-07T10:17:49.2605820Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2605883Z     new_features = layer(features)
2025-09-07T10:17:49.2606103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2606203Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2606431Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2606514Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2606519Z 
2025-09-07T10:17:49.2606614Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2606811Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2606867Z     return mod(*inputs)
2025-09-07T10:17:49.2607084Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2607155Z     features = self.features(x)
2025-09-07T10:17:49.2607373Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2607441Z     new_features = layer(features)
2025-09-07T10:17:49.2607654Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2607748Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2607987Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2608153Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2608156Z 
2025-09-07T10:17:49.2608253Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2608448Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2608505Z     return mod(*inputs)
2025-09-07T10:17:49.2608727Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2608787Z     features = self.features(x)
2025-09-07T10:17:49.2609050Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2609115Z     new_features = layer(features)
2025-09-07T10:17:49.2609339Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2609439Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2609668Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2609838Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2609841Z 
2025-09-07T10:17:49.2609971Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2610173Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2610230Z     return mod(*inputs)
2025-09-07T10:17:49.2610452Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2610519Z     features = self.features(x)
2025-09-07T10:17:49.2610739Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2610807Z     new_features = layer(features)
2025-09-07T10:17:49.2611086Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2611220Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2611223Z 
2025-09-07T10:17:49.2611318Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2611515Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2611573Z     return mod(*inputs)
2025-09-07T10:17:49.2611790Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2611860Z     features = self.features(x)
2025-09-07T10:17:49.2612076Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2612139Z     new_features = layer(features)
2025-09-07T10:17:49.2612368Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2612494Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2612497Z 
2025-09-07T10:17:49.2612597Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2612790Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2612850Z     return mod(*inputs)
2025-09-07T10:17:49.2613072Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2613136Z     features = self.features(x)
2025-09-07T10:17:49.2613350Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2613413Z     new_features = layer(features)
2025-09-07T10:17:49.2613635Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2613731Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2613960Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2614043Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2614047Z 
2025-09-07T10:17:49.2614140Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2614337Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2614394Z     return mod(*inputs)
2025-09-07T10:17:49.2614610Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2614710Z     features = self.features(x)
2025-09-07T10:17:49.2614930Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2614998Z     new_features = layer(features)
2025-09-07T10:17:49.2615215Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2615309Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2615538Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2615703Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2615740Z 
2025-09-07T10:17:49.2615837Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2616024Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2616088Z     return mod(*inputs)
2025-09-07T10:17:49.2616310Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2616374Z     features = self.features(x)
2025-09-07T10:17:49.2616654Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2616717Z     new_features = layer(features)
2025-09-07T10:17:49.2616938Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2617029Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2617254Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2617421Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2617428Z 
2025-09-07T10:17:49.2617525Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2617724Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2617780Z     return mod(*inputs)
2025-09-07T10:17:49.2618008Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2618072Z     features = self.features(x)
2025-09-07T10:17:49.2618293Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2618357Z     new_features = layer(features)
2025-09-07T10:17:49.2618573Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2618704Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2618707Z 
2025-09-07T10:17:49.2618800Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2618991Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2619051Z     return mod(*inputs)
2025-09-07T10:17:49.2619271Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2619340Z     features = self.features(x)
2025-09-07T10:17:49.2619558Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2619621Z     new_features = layer(features)
2025-09-07T10:17:49.2619837Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2619957Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2619960Z 
2025-09-07T10:17:49.2620056Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2620251Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2620417Z     return mod(*inputs)
2025-09-07T10:17:49.2620633Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2620695Z     features = self.features(x)
2025-09-07T10:17:49.2620916Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2620978Z     new_features = layer(features)
2025-09-07T10:17:49.2621191Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2621283Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2621550Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2621628Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2621631Z 
2025-09-07T10:17:49.2621725Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2621921Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2621977Z     return mod(*inputs)
2025-09-07T10:17:49.2622196Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2622323Z     features = self.features(x)
2025-09-07T10:17:49.2622538Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2622607Z     new_features = layer(features)
2025-09-07T10:17:49.2622823Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2622918Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2623142Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2623312Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2623316Z 
2025-09-07T10:17:49.2623413Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2623606Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2623667Z     return mod(*inputs)
2025-09-07T10:17:49.2623884Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2623946Z     features = self.features(x)
2025-09-07T10:17:49.2624167Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2624230Z     new_features = layer(features)
2025-09-07T10:17:49.2624447Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2624538Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2624763Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2624925Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2624928Z 
2025-09-07T10:17:49.2625027Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2625225Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2625284Z     return mod(*inputs)
2025-09-07T10:17:49.2625508Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2625573Z     features = self.features(x)
2025-09-07T10:17:49.2625864Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2625933Z     new_features = layer(features)
2025-09-07T10:17:49.2626145Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2626329Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2626332Z 
2025-09-07T10:17:49.2626427Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2626622Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2626686Z     return mod(*inputs)
2025-09-07T10:17:49.2626904Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2626972Z     features = self.features(x)
2025-09-07T10:17:49.2627181Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2627283Z     new_features = layer(features)
2025-09-07T10:17:49.2627496Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2627624Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2627627Z 
2025-09-07T10:17:49.2627726Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2627920Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2628044Z     return mod(*inputs)
2025-09-07T10:17:49.2628263Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2628328Z     features = self.features(x)
2025-09-07T10:17:49.2628546Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2628610Z     new_features = layer(features)
2025-09-07T10:17:49.2628828Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2628920Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2629150Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2629232Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2629235Z 
2025-09-07T10:17:49.2629327Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2629528Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2629585Z     return mod(*inputs)
2025-09-07T10:17:49.2629808Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2629871Z     features = self.features(x)
2025-09-07T10:17:49.2630091Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2630156Z     new_features = layer(features)
2025-09-07T10:17:49.2630371Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2630468Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2630692Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2630857Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2630860Z 
2025-09-07T10:17:49.2630955Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2631149Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2631210Z     return mod(*inputs)
2025-09-07T10:17:49.2631423Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2631494Z     features = self.features(x)
2025-09-07T10:17:49.2631709Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2631819Z     new_features = layer(features)
2025-09-07T10:17:49.2632037Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2632128Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2632360Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2632521Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2632524Z 
2025-09-07T10:17:49.2632616Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2632816Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2632910Z     return mod(*inputs)
2025-09-07T10:17:49.2633131Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2633194Z     features = self.features(x)
2025-09-07T10:17:49.2633411Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2633485Z     new_features = layer(features)
2025-09-07T10:17:49.2633779Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2633911Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2633914Z 
2025-09-07T10:17:49.2634007Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2634197Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2634255Z     return mod(*inputs)
2025-09-07T10:17:49.2634474Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2634537Z     features = self.features(x)
2025-09-07T10:17:49.2634756Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2634823Z     new_features = layer(features)
2025-09-07T10:17:49.2635038Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2635166Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2635170Z 
2025-09-07T10:17:49.2635264Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2635456Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2635515Z     return mod(*inputs)
2025-09-07T10:17:49.2635729Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2635794Z     features = self.features(x)
2025-09-07T10:17:49.2636013Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2636077Z     new_features = layer(features)
2025-09-07T10:17:49.2636295Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2636383Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2636615Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2636690Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2636693Z 
2025-09-07T10:17:49.2636787Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2636981Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2637038Z     return mod(*inputs)
2025-09-07T10:17:49.2637250Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2637313Z     features = self.features(x)
2025-09-07T10:17:49.2637572Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2637635Z     new_features = layer(features)
2025-09-07T10:17:49.2637850Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2637943Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2638168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2638328Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2638332Z 
2025-09-07T10:17:49.2638464Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2638657Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2638717Z     return mod(*inputs)
2025-09-07T10:17:49.2638934Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2638995Z     features = self.features(x)
2025-09-07T10:17:49.2639208Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2639269Z     new_features = layer(features)
2025-09-07T10:17:49.2639569Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2639660Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2639888Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2640046Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2640050Z 
2025-09-07T10:17:49.2640144Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2640353Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2640415Z     return mod(*inputs)
2025-09-07T10:17:49.2640631Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2640693Z     features = self.features(x)
2025-09-07T10:17:49.2640911Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2640976Z     new_features = layer(features)
2025-09-07T10:17:49.2641187Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2641316Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2641320Z 
2025-09-07T10:17:49.2641412Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2641612Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2641671Z     return mod(*inputs)
2025-09-07T10:17:49.2641887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2641951Z     features = self.features(x)
2025-09-07T10:17:49.2642168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2642236Z     new_features = layer(features)
2025-09-07T10:17:49.2642448Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2642573Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2642576Z 
2025-09-07T10:17:49.2642675Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2642861Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2642921Z     return mod(*inputs)
2025-09-07T10:17:49.2643171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2643232Z     features = self.features(x)
2025-09-07T10:17:49.2643446Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2643507Z     new_features = layer(features)
2025-09-07T10:17:49.2643727Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2643818Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2644044Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2644156Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2644159Z 
2025-09-07T10:17:49.2644250Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2644443Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2644503Z     return mod(*inputs)
2025-09-07T10:17:49.2644718Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2644780Z     features = self.features(x)
2025-09-07T10:17:49.2645056Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2645125Z     new_features = layer(features)
2025-09-07T10:17:49.2645336Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2645427Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2645652Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2645813Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2645821Z 
2025-09-07T10:17:49.2645911Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2646104Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2646164Z     return mod(*inputs)
2025-09-07T10:17:49.2646378Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2646445Z     features = self.features(x)
2025-09-07T10:17:49.2646659Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2646720Z     new_features = layer(features)
2025-09-07T10:17:49.2646933Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2647025Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2647249Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2647410Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2647414Z 
2025-09-07T10:17:49.2647505Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2647702Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2647764Z     return mod(*inputs)
2025-09-07T10:17:49.2647984Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2648045Z     features = self.features(x)
2025-09-07T10:17:49.2648264Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2648328Z     new_features = layer(features)
2025-09-07T10:17:49.2648542Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2648672Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2648713Z 
2025-09-07T10:17:49.2648808Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2649003Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2649063Z     return mod(*inputs)
2025-09-07T10:17:49.2649280Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2649345Z     features = self.features(x)
2025-09-07T10:17:49.2649556Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2649621Z     new_features = layer(features)
2025-09-07T10:17:49.2649884Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2650013Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2650020Z 
2025-09-07T10:17:49.2650123Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2650319Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2650380Z     return mod(*inputs)
2025-09-07T10:17:49.2650656Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2650726Z     features = self.features(x)
2025-09-07T10:17:49.2650940Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2651003Z     new_features = layer(features)
2025-09-07T10:17:49.2651219Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2651315Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2651547Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2651629Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2651632Z 
2025-09-07T10:17:49.2651726Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2651926Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2651982Z     return mod(*inputs)
2025-09-07T10:17:49.2652204Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2652267Z     features = self.features(x)
2025-09-07T10:17:49.2652480Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2652546Z     new_features = layer(features)
2025-09-07T10:17:49.2652758Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2652853Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2653077Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2653241Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2653244Z 
2025-09-07T10:17:49.2653334Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2653528Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2653587Z     return mod(*inputs)
2025-09-07T10:17:49.2653804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2653873Z     features = self.features(x)
2025-09-07T10:17:49.2654086Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2654148Z     new_features = layer(features)
2025-09-07T10:17:49.2654362Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2654489Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2654716Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2654877Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2654881Z 
2025-09-07T10:17:49.2654979Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2655176Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2655233Z     return mod(*inputs)
2025-09-07T10:17:49.2655482Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2655545Z     features = self.features(x)
2025-09-07T10:17:49.2655768Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2655832Z     new_features = layer(features)
2025-09-07T10:17:49.2656042Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2656169Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2656172Z 
2025-09-07T10:17:49.2656335Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2656533Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2656590Z     return mod(*inputs)
2025-09-07T10:17:49.2656809Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2656879Z     features = self.features(x)
2025-09-07T10:17:49.2657093Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2657163Z     new_features = layer(features)
2025-09-07T10:17:49.2657378Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2657507Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2657511Z 
2025-09-07T10:17:49.2657606Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2657802Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2657863Z     return mod(*inputs)
2025-09-07T10:17:49.2658077Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2658139Z     features = self.features(x)
2025-09-07T10:17:49.2658358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2658420Z     new_features = layer(features)
2025-09-07T10:17:49.2658640Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2658736Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2658967Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2659045Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2659048Z 
2025-09-07T10:17:49.2659139Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2659338Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2659393Z     return mod(*inputs)
2025-09-07T10:17:49.2659615Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2659679Z     features = self.features(x)
2025-09-07T10:17:49.2659897Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2659995Z     new_features = layer(features)
2025-09-07T10:17:49.2660207Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2660299Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2660522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2660690Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2660694Z 
2025-09-07T10:17:49.2660786Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2660982Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2661265Z     return mod(*inputs)
2025-09-07T10:17:49.2661481Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2661551Z     features = self.features(x)
2025-09-07T10:17:49.2661765Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2661826Z     new_features = layer(features)
2025-09-07T10:17:49.2662043Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2662207Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2662437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2662597Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2662602Z 
2025-09-07T10:17:49.2662697Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2662888Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2662946Z     return mod(*inputs)
2025-09-07T10:17:49.2663165Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2663227Z     features = self.features(x)
2025-09-07T10:17:49.2663445Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2663509Z     new_features = layer(features)
2025-09-07T10:17:49.2663719Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2663846Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2663849Z 
2025-09-07T10:17:49.2663938Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2664133Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2664191Z     return mod(*inputs)
2025-09-07T10:17:49.2664411Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2664474Z     features = self.features(x)
2025-09-07T10:17:49.2664691Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2664758Z     new_features = layer(features)
2025-09-07T10:17:49.2664985Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2665106Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2665109Z 
2025-09-07T10:17:49.2665198Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2665389Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2665452Z     return mod(*inputs)
2025-09-07T10:17:49.2665738Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2665842Z     features = self.features(x)
2025-09-07T10:17:49.2666055Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2666118Z     new_features = layer(features)
2025-09-07T10:17:49.2666338Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2666433Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2666658Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2666732Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2666736Z 
2025-09-07T10:17:49.2666829Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2667060Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2667116Z     return mod(*inputs)
2025-09-07T10:17:49.2667331Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2667394Z     features = self.features(x)
2025-09-07T10:17:49.2667614Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2667680Z     new_features = layer(features)
2025-09-07T10:17:49.2667961Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2668062Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2668290Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2668460Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2668464Z 
2025-09-07T10:17:49.2668561Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2668760Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2668820Z     return mod(*inputs)
2025-09-07T10:17:49.2669040Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2669109Z     features = self.features(x)
2025-09-07T10:17:49.2669328Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2669395Z     new_features = layer(features)
2025-09-07T10:17:49.2669613Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2669706Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2669938Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2670103Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2670107Z 
2025-09-07T10:17:49.2670207Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2670402Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2670460Z     return mod(*inputs)
2025-09-07T10:17:49.2670685Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2670752Z     features = self.features(x)
2025-09-07T10:17:49.2670974Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2671039Z     new_features = layer(features)
2025-09-07T10:17:49.2671260Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2671391Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2671394Z 
2025-09-07T10:17:49.2671489Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2671722Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2671780Z     return mod(*inputs)
2025-09-07T10:17:49.2671999Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2672064Z     features = self.features(x)
2025-09-07T10:17:49.2672281Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2672345Z     new_features = layer(features)
2025-09-07T10:17:49.2672557Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2672719Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2672722Z 
2025-09-07T10:17:49.2672813Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2673011Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2673075Z     return mod(*inputs)
2025-09-07T10:17:49.2673290Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2673358Z     features = self.features(x)
2025-09-07T10:17:49.2673628Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2673697Z     new_features = layer(features)
2025-09-07T10:17:49.2673910Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2674006Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2674237Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2674312Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2674315Z 
2025-09-07T10:17:49.2674414Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2674607Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2674665Z     return mod(*inputs)
2025-09-07T10:17:49.2674887Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2674950Z     features = self.features(x)
2025-09-07T10:17:49.2675167Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2675233Z     new_features = layer(features)
2025-09-07T10:17:49.2675447Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2675552Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2675779Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2675947Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2675950Z 
2025-09-07T10:17:49.2676045Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2676238Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2676297Z     return mod(*inputs)
2025-09-07T10:17:49.2676507Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2676571Z     features = self.features(x)
2025-09-07T10:17:49.2676784Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2676850Z     new_features = layer(features)
2025-09-07T10:17:49.2677061Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2677152Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2677423Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2677585Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2677588Z 
2025-09-07T10:17:49.2677691Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2677884Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2677942Z     return mod(*inputs)
2025-09-07T10:17:49.2678160Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2678256Z     features = self.features(x)
2025-09-07T10:17:49.2678475Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2678537Z     new_features = layer(features)
2025-09-07T10:17:49.2678758Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2678883Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2678887Z 
2025-09-07T10:17:49.2678982Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2679241Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2679303Z     return mod(*inputs)
2025-09-07T10:17:49.2679525Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2679588Z     features = self.features(x)
2025-09-07T10:17:49.2679805Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2679873Z     new_features = layer(features)
2025-09-07T10:17:49.2680088Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2680216Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2680219Z 
2025-09-07T10:17:49.2680311Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2680507Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2680567Z     return mod(*inputs)
2025-09-07T10:17:49.2680784Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2680847Z     features = self.features(x)
2025-09-07T10:17:49.2681060Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2681124Z     new_features = layer(features)
2025-09-07T10:17:49.2681338Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2681431Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2681660Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2681736Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2681739Z 
2025-09-07T10:17:49.2681835Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2682034Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2682090Z     return mod(*inputs)
2025-09-07T10:17:49.2682312Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2682376Z     features = self.features(x)
2025-09-07T10:17:49.2682592Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2682653Z     new_features = layer(features)
2025-09-07T10:17:49.2682866Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2682992Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2683215Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2683384Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2683387Z 
2025-09-07T10:17:49.2683480Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2683672Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2683729Z     return mod(*inputs)
2025-09-07T10:17:49.2683949Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2684067Z     features = self.features(x)
2025-09-07T10:17:49.2684282Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2684347Z     new_features = layer(features)
2025-09-07T10:17:49.2684559Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2684651Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2684934Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2685095Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2685098Z 
2025-09-07T10:17:49.2685191Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2685381Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2685441Z     return mod(*inputs)
2025-09-07T10:17:49.2685656Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2685719Z     features = self.features(x)
2025-09-07T10:17:49.2685933Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2685994Z     new_features = layer(features)
2025-09-07T10:17:49.2686209Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2686334Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2686338Z 
2025-09-07T10:17:49.2686429Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2686622Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2686680Z     return mod(*inputs)
2025-09-07T10:17:49.2686898Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2686961Z     features = self.features(x)
2025-09-07T10:17:49.2687178Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2687241Z     new_features = layer(features)
2025-09-07T10:17:49.2687454Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2687582Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2687585Z 
2025-09-07T10:17:49.2687676Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2687868Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2687925Z     return mod(*inputs)
2025-09-07T10:17:49.2688141Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2688210Z     features = self.features(x)
2025-09-07T10:17:49.2688426Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2688531Z     new_features = layer(features)
2025-09-07T10:17:49.2688750Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2688842Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2689073Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2689149Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2689152Z 
2025-09-07T10:17:49.2689249Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2689438Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2689532Z     return mod(*inputs)
2025-09-07T10:17:49.2689747Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2689820Z     features = self.features(x)
2025-09-07T10:17:49.2690040Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2690104Z     new_features = layer(features)
2025-09-07T10:17:49.2690323Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2690479Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2690709Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2690877Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2690880Z 
2025-09-07T10:17:49.2690977Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2691180Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2691239Z     return mod(*inputs)
2025-09-07T10:17:49.2691464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2691527Z     features = self.features(x)
2025-09-07T10:17:49.2691746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2691818Z     new_features = layer(features)
2025-09-07T10:17:49.2692050Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2692143Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2692366Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2692533Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2692536Z 
2025-09-07T10:17:49.2692636Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2692830Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2692893Z     return mod(*inputs)
2025-09-07T10:17:49.2693113Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2693177Z     features = self.features(x)
2025-09-07T10:17:49.2693401Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2693464Z     new_features = layer(features)
2025-09-07T10:17:49.2693684Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2693809Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2693813Z 
2025-09-07T10:17:49.2693911Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2694104Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2694216Z     return mod(*inputs)
2025-09-07T10:17:49.2694437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2694498Z     features = self.features(x)
2025-09-07T10:17:49.2694723Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2694788Z     new_features = layer(features)
2025-09-07T10:17:49.2695002Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2695132Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2695168Z 
2025-09-07T10:17:49.2695262Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2695457Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2695514Z     return mod(*inputs)
2025-09-07T10:17:49.2695739Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2695811Z     features = self.features(x)
2025-09-07T10:17:49.2696031Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2696158Z     new_features = layer(features)
2025-09-07T10:17:49.2696379Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2696481Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2696714Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2696793Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2696795Z 
2025-09-07T10:17:49.2696896Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2697090Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2697154Z     return mod(*inputs)
2025-09-07T10:17:49.2697373Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2697440Z     features = self.features(x)
2025-09-07T10:17:49.2697667Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2697733Z     new_features = layer(features)
2025-09-07T10:17:49.2697955Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2698049Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2698276Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2698442Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2698447Z 
2025-09-07T10:17:49.2698540Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2698895Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2698959Z     return mod(*inputs)
2025-09-07T10:17:49.2699208Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2699275Z     features = self.features(x)
2025-09-07T10:17:49.2699490Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2699562Z     new_features = layer(features)
2025-09-07T10:17:49.2699772Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2699871Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2700097Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2700347Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2700356Z 
2025-09-07T10:17:49.2700449Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2700646Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2700710Z     return mod(*inputs)
2025-09-07T10:17:49.2700927Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2700997Z     features = self.features(x)
2025-09-07T10:17:49.2701210Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2701323Z     new_features = layer(features)
2025-09-07T10:17:49.2701544Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2701673Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2701677Z 
2025-09-07T10:17:49.2701779Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2701972Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2702030Z     return mod(*inputs)
2025-09-07T10:17:49.2702352Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2702418Z     features = self.features(x)
2025-09-07T10:17:49.2702640Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2702705Z     new_features = layer(features)
2025-09-07T10:17:49.2702920Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2703052Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2703057Z 
2025-09-07T10:17:49.2703147Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2703346Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2703402Z     return mod(*inputs)
2025-09-07T10:17:49.2703627Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2703690Z     features = self.features(x)
2025-09-07T10:17:49.2703907Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2703977Z     new_features = layer(features)
2025-09-07T10:17:49.2704188Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2704288Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2704514Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2704592Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2704595Z 
2025-09-07T10:17:49.2704692Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2704882Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2704947Z     return mod(*inputs)
2025-09-07T10:17:49.2705163Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2705232Z     features = self.features(x)
2025-09-07T10:17:49.2705451Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2705517Z     new_features = layer(features)
2025-09-07T10:17:49.2705804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2705901Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2706200Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2706366Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2706370Z 
2025-09-07T10:17:49.2706467Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2706665Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2706723Z     return mod(*inputs)
2025-09-07T10:17:49.2706947Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2707009Z     features = self.features(x)
2025-09-07T10:17:49.2707266Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2707338Z     new_features = layer(features)
2025-09-07T10:17:49.2707554Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2707655Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2707880Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2708202Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2708205Z 
2025-09-07T10:17:49.2708301Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2708492Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2708556Z     return mod(*inputs)
2025-09-07T10:17:49.2708778Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2708849Z     features = self.features(x)
2025-09-07T10:17:49.2709062Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2709128Z     new_features = layer(features)
2025-09-07T10:17:49.2709345Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2709471Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2709477Z 
2025-09-07T10:17:49.2709574Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2709767Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2709832Z     return mod(*inputs)
2025-09-07T10:17:49.2710046Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2710112Z     features = self.features(x)
2025-09-07T10:17:49.2710327Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2710393Z     new_features = layer(features)
2025-09-07T10:17:49.2710613Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2710740Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2710743Z 
2025-09-07T10:17:49.2710840Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2711038Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2711095Z     return mod(*inputs)
2025-09-07T10:17:49.2711315Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2711381Z     features = self.features(x)
2025-09-07T10:17:49.2711596Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2711664Z     new_features = layer(features)
2025-09-07T10:17:49.2711920Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2712020Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2712243Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2712327Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2712331Z 
2025-09-07T10:17:49.2712426Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2712618Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2712679Z     return mod(*inputs)
2025-09-07T10:17:49.2712911Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2713024Z     features = self.features(x)
2025-09-07T10:17:49.2713241Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2713307Z     new_features = layer(features)
2025-09-07T10:17:49.2713522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2713614Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2713907Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2714069Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2714072Z 
2025-09-07T10:17:49.2714165Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2714364Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2714424Z     return mod(*inputs)
2025-09-07T10:17:49.2714646Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2714709Z     features = self.features(x)
2025-09-07T10:17:49.2714929Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2714992Z     new_features = layer(features)
2025-09-07T10:17:49.2715209Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2715308Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2715529Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2715697Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2715702Z 
2025-09-07T10:17:49.2715795Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2715988Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2716051Z     return mod(*inputs)
2025-09-07T10:17:49.2716275Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2716343Z     features = self.features(x)
2025-09-07T10:17:49.2716557Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2716623Z     new_features = layer(features)
2025-09-07T10:17:49.2716840Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2716967Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2716970Z 
2025-09-07T10:17:49.2717070Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2717262Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2717322Z     return mod(*inputs)
2025-09-07T10:17:49.2717539Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2717641Z     features = self.features(x)
2025-09-07T10:17:49.2717895Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2717960Z     new_features = layer(features)
2025-09-07T10:17:49.2718185Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2718309Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2718312Z 
2025-09-07T10:17:49.2718407Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2718605Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2718696Z     return mod(*inputs)
2025-09-07T10:17:49.2718916Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2718981Z     features = self.features(x)
2025-09-07T10:17:49.2719197Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2719260Z     new_features = layer(features)
2025-09-07T10:17:49.2719533Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2719633Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2719860Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2719945Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2719948Z 
2025-09-07T10:17:49.2720050Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2720247Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2720309Z     return mod(*inputs)
2025-09-07T10:17:49.2720533Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2720602Z     features = self.features(x)
2025-09-07T10:17:49.2720818Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2720884Z     new_features = layer(features)
2025-09-07T10:17:49.2721108Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2721202Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2721435Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2721604Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2721607Z 
2025-09-07T10:17:49.2721707Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2721901Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2721961Z     return mod(*inputs)
2025-09-07T10:17:49.2722185Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2722251Z     features = self.features(x)
2025-09-07T10:17:49.2722471Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2722535Z     new_features = layer(features)
2025-09-07T10:17:49.2722753Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2722854Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2723084Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2723252Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2723289Z 
2025-09-07T10:17:49.2723385Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2723586Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2723645Z     return mod(*inputs)
2025-09-07T10:17:49.2723867Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2723935Z     features = self.features(x)
2025-09-07T10:17:49.2724154Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2724223Z     new_features = layer(features)
2025-09-07T10:17:49.2724437Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2724599Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2724602Z 
2025-09-07T10:17:49.2724701Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2724893Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2724955Z     return mod(*inputs)
2025-09-07T10:17:49.2725173Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2725312Z     features = self.features(x)
2025-09-07T10:17:49.2725535Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2725598Z     new_features = layer(features)
2025-09-07T10:17:49.2725817Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2725946Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2725949Z 
2025-09-07T10:17:49.2726047Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2726246Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2726304Z     return mod(*inputs)
2025-09-07T10:17:49.2726526Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2726589Z     features = self.features(x)
2025-09-07T10:17:49.2726810Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2726875Z     new_features = layer(features)
2025-09-07T10:17:49.2727090Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2727194Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2727424Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2727508Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2727513Z 
2025-09-07T10:17:49.2727607Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2727806Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2727871Z     return mod(*inputs)
2025-09-07T10:17:49.2728092Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2728162Z     features = self.features(x)
2025-09-07T10:17:49.2728379Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2728450Z     new_features = layer(features)
2025-09-07T10:17:49.2728668Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2728765Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2728999Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2729200Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2729202Z 
2025-09-07T10:17:49.2729301Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2729495Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2729559Z     return mod(*inputs)
2025-09-07T10:17:49.2729782Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2729845Z     features = self.features(x)
2025-09-07T10:17:49.2730066Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2730164Z     new_features = layer(features)
2025-09-07T10:17:49.2730379Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2730477Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2730698Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2730868Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2730871Z 
2025-09-07T10:17:49.2731026Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2731232Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2731292Z     return mod(*inputs)
2025-09-07T10:17:49.2731510Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2731581Z     features = self.features(x)
2025-09-07T10:17:49.2731800Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2731869Z     new_features = layer(features)
2025-09-07T10:17:49.2732085Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2732212Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2732220Z 
2025-09-07T10:17:49.2732314Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2732509Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2732569Z     return mod(*inputs)
2025-09-07T10:17:49.2732790Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2732857Z     features = self.features(x)
2025-09-07T10:17:49.2733076Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2733139Z     new_features = layer(features)
2025-09-07T10:17:49.2733358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2733486Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2733490Z 
2025-09-07T10:17:49.2733571Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2733643Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2733712Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2733788Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2736491Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2736597Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2736712Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2736925Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2736998Z     return mod(*inputs)
2025-09-07T10:17:49.2737240Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2737364Z     features = self.features(x)
2025-09-07T10:17:49.2737603Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T10:17:49.2737672Z     return torch.cat(features, 1)
2025-09-07T10:17:49.2737676Z 
2025-09-07T10:17:49.2737782Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2737986Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2738085Z     return mod(*inputs)
2025-09-07T10:17:49.2738314Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2738383Z     features = self.features(x)
2025-09-07T10:17:49.2738422Z 
2025-09-07T10:17:49.2738524Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2738719Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2738778Z     return mod(*inputs)
2025-09-07T10:17:49.2739001Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2739070Z     features = self.features(x)
2025-09-07T10:17:49.2739074Z 
2025-09-07T10:17:49.2739169Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2739403Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2739463Z     return mod(*inputs)
2025-09-07T10:17:49.2739686Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2739757Z     features = self.features(x)
2025-09-07T10:17:49.2739975Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2740048Z     new_features = layer(features)
2025-09-07T10:17:49.2740273Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2740374Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2740610Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2740779Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2740784Z 
2025-09-07T10:17:49.2740884Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2741081Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2741143Z     return mod(*inputs)
2025-09-07T10:17:49.2741364Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2741431Z     features = self.features(x)
2025-09-07T10:17:49.2741651Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2741718Z     new_features = layer(features)
2025-09-07T10:17:49.2741938Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2742070Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2742073Z 
2025-09-07T10:17:49.2742170Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2742454Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2742516Z     return mod(*inputs)
2025-09-07T10:17:49.2742746Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2742809Z     features = self.features(x)
2025-09-07T10:17:49.2743025Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2743097Z     new_features = layer(features)
2025-09-07T10:17:49.2743318Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2743486Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2743490Z 
2025-09-07T10:17:49.2743585Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2743789Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2743849Z     return mod(*inputs)
2025-09-07T10:17:49.2744071Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2744139Z     features = self.features(x)
2025-09-07T10:17:49.2744358Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2744465Z     new_features = layer(features)
2025-09-07T10:17:49.2744681Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2744782Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2745013Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2745092Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2745096Z 
2025-09-07T10:17:49.2745230Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2745427Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2745491Z     return mod(*inputs)
2025-09-07T10:17:49.2745790Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2745871Z     features = self.features(x)
2025-09-07T10:17:49.2746090Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2746163Z     new_features = layer(features)
2025-09-07T10:17:49.2746380Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2746474Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2746708Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2746877Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2746882Z 
2025-09-07T10:17:49.2746984Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2747178Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2747245Z     return mod(*inputs)
2025-09-07T10:17:49.2747461Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2747525Z     features = self.features(x)
2025-09-07T10:17:49.2747748Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2747813Z     new_features = layer(features)
2025-09-07T10:17:49.2748032Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2748128Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2748405Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2748583Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2748587Z 
2025-09-07T10:17:49.2748689Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2748897Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2748958Z     return mod(*inputs)
2025-09-07T10:17:49.2749187Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2749296Z     features = self.features(x)
2025-09-07T10:17:49.2749518Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2749591Z     new_features = layer(features)
2025-09-07T10:17:49.2749810Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2749946Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2749949Z 
2025-09-07T10:17:49.2750047Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2750244Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2750366Z     return mod(*inputs)
2025-09-07T10:17:49.2750583Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2750657Z     features = self.features(x)
2025-09-07T10:17:49.2750874Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2750942Z     new_features = layer(features)
2025-09-07T10:17:49.2751209Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2751340Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2751346Z 
2025-09-07T10:17:49.2751446Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2751643Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2751711Z     return mod(*inputs)
2025-09-07T10:17:49.2751936Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2752001Z     features = self.features(x)
2025-09-07T10:17:49.2752230Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2752294Z     new_features = layer(features)
2025-09-07T10:17:49.2752521Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2752620Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2752856Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2752940Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2752942Z 
2025-09-07T10:17:49.2753038Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2753242Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2753302Z     return mod(*inputs)
2025-09-07T10:17:49.2753520Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2753592Z     features = self.features(x)
2025-09-07T10:17:49.2753813Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2753884Z     new_features = layer(features)
2025-09-07T10:17:49.2754103Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2754256Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2754490Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2754660Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2754666Z 
2025-09-07T10:17:49.2754772Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2754969Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2755076Z     return mod(*inputs)
2025-09-07T10:17:49.2755299Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2755365Z     features = self.features(x)
2025-09-07T10:17:49.2755596Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2755662Z     new_features = layer(features)
2025-09-07T10:17:49.2755886Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2755981Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2756212Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2756425Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2756428Z 
2025-09-07T10:17:49.2756526Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2756728Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2756787Z     return mod(*inputs)
2025-09-07T10:17:49.2757011Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2757112Z     features = self.features(x)
2025-09-07T10:17:49.2757334Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2757404Z     new_features = layer(features)
2025-09-07T10:17:49.2757625Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2757762Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2757766Z 
2025-09-07T10:17:49.2757857Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2758054Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2758119Z     return mod(*inputs)
2025-09-07T10:17:49.2758337Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2758406Z     features = self.features(x)
2025-09-07T10:17:49.2758628Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2758699Z     new_features = layer(features)
2025-09-07T10:17:49.2758918Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2759043Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2759049Z 
2025-09-07T10:17:49.2759148Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2759342Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2759409Z     return mod(*inputs)
2025-09-07T10:17:49.2759629Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2759695Z     features = self.features(x)
2025-09-07T10:17:49.2759921Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2759984Z     new_features = layer(features)
2025-09-07T10:17:49.2760253Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2760351Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2760577Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2760664Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2760667Z 
2025-09-07T10:17:49.2760764Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2760999Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2761059Z     return mod(*inputs)
2025-09-07T10:17:49.2761284Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2761352Z     features = self.features(x)
2025-09-07T10:17:49.2761573Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2761641Z     new_features = layer(features)
2025-09-07T10:17:49.2761855Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2761987Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2762214Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2762381Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2762387Z 
2025-09-07T10:17:49.2762487Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2762680Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2762741Z     return mod(*inputs)
2025-09-07T10:17:49.2762988Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2763054Z     features = self.features(x)
2025-09-07T10:17:49.2763270Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2763335Z     new_features = layer(features)
2025-09-07T10:17:49.2763556Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2763647Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2763876Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2764040Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2764043Z 
2025-09-07T10:17:49.2764140Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2764338Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2764396Z     return mod(*inputs)
2025-09-07T10:17:49.2764616Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2764680Z     features = self.features(x)
2025-09-07T10:17:49.2764896Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2764964Z     new_features = layer(features)
2025-09-07T10:17:49.2765174Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2765305Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2765308Z 
2025-09-07T10:17:49.2765400Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2765592Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2765652Z     return mod(*inputs)
2025-09-07T10:17:49.2765909Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2765979Z     features = self.features(x)
2025-09-07T10:17:49.2766197Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2766267Z     new_features = layer(features)
2025-09-07T10:17:49.2766483Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2766645Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2766648Z 
2025-09-07T10:17:49.2766754Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2766947Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2767011Z     return mod(*inputs)
2025-09-07T10:17:49.2767229Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2767296Z     features = self.features(x)
2025-09-07T10:17:49.2767521Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2767587Z     new_features = layer(features)
2025-09-07T10:17:49.2767846Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2767942Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2768177Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2768255Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2768259Z 
2025-09-07T10:17:49.2768357Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2768593Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2768653Z     return mod(*inputs)
2025-09-07T10:17:49.2768876Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2768940Z     features = self.features(x)
2025-09-07T10:17:49.2769156Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2769229Z     new_features = layer(features)
2025-09-07T10:17:49.2769446Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2769547Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2769775Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2769939Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2769946Z 
2025-09-07T10:17:49.2770046Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2770240Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2770302Z     return mod(*inputs)
2025-09-07T10:17:49.2770517Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2770590Z     features = self.features(x)
2025-09-07T10:17:49.2770805Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2770871Z     new_features = layer(features)
2025-09-07T10:17:49.2771094Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2771192Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2771425Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2771628Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2771631Z 
2025-09-07T10:17:49.2771731Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2771931Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2771993Z     return mod(*inputs)
2025-09-07T10:17:49.2772216Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2772282Z     features = self.features(x)
2025-09-07T10:17:49.2772561Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2772627Z     new_features = layer(features)
2025-09-07T10:17:49.2772842Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2772980Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2772983Z 
2025-09-07T10:17:49.2773079Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2773281Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2773338Z     return mod(*inputs)
2025-09-07T10:17:49.2773596Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2773665Z     features = self.features(x)
2025-09-07T10:17:49.2773883Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2773956Z     new_features = layer(features)
2025-09-07T10:17:49.2774171Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2774298Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2774305Z 
2025-09-07T10:17:49.2774430Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2774630Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2774693Z     return mod(*inputs)
2025-09-07T10:17:49.2774908Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2774976Z     features = self.features(x)
2025-09-07T10:17:49.2775186Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2775253Z     new_features = layer(features)
2025-09-07T10:17:49.2775473Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2775567Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2775800Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2775877Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2775880Z 
2025-09-07T10:17:49.2775979Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2776179Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2776237Z     return mod(*inputs)
2025-09-07T10:17:49.2776464Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2776528Z     features = self.features(x)
2025-09-07T10:17:49.2776740Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2776809Z     new_features = layer(features)
2025-09-07T10:17:49.2777024Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2777121Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2777389Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2777561Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2777564Z 
2025-09-07T10:17:49.2777659Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2777855Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2777918Z     return mod(*inputs)
2025-09-07T10:17:49.2778136Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2778239Z     features = self.features(x)
2025-09-07T10:17:49.2778451Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2778517Z     new_features = layer(features)
2025-09-07T10:17:49.2778738Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2778834Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2779067Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2779225Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2779262Z 
2025-09-07T10:17:49.2779366Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2779554Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2779616Z     return mod(*inputs)
2025-09-07T10:17:49.2779839Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2779902Z     features = self.features(x)
2025-09-07T10:17:49.2780155Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2780221Z     new_features = layer(features)
2025-09-07T10:17:49.2780440Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2780570Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2780574Z 
2025-09-07T10:17:49.2780666Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2780863Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2780921Z     return mod(*inputs)
2025-09-07T10:17:49.2781140Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2781207Z     features = self.features(x)
2025-09-07T10:17:49.2781424Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2781493Z     new_features = layer(features)
2025-09-07T10:17:49.2781711Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2781838Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2781842Z 
2025-09-07T10:17:49.2781935Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2782131Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2782197Z     return mod(*inputs)
2025-09-07T10:17:49.2782426Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2782497Z     features = self.features(x)
2025-09-07T10:17:49.2782716Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2782778Z     new_features = layer(features)
2025-09-07T10:17:49.2783003Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2783136Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2783372Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2783451Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2783457Z 
2025-09-07T10:17:49.2783558Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2783755Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2783850Z     return mod(*inputs)
2025-09-07T10:17:49.2784072Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2784138Z     features = self.features(x)
2025-09-07T10:17:49.2784352Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2784419Z     new_features = layer(features)
2025-09-07T10:17:49.2784634Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2784731Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2784960Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2785164Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2785168Z 
2025-09-07T10:17:49.2785263Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2785461Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2785525Z     return mod(*inputs)
2025-09-07T10:17:49.2785816Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2785924Z     features = self.features(x)
2025-09-07T10:17:49.2786148Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2786220Z     new_features = layer(features)
2025-09-07T10:17:49.2786439Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2786536Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2786768Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2786933Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2786936Z 
2025-09-07T10:17:49.2787041Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2787235Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2787295Z     return mod(*inputs)
2025-09-07T10:17:49.2787522Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2787587Z     features = self.features(x)
2025-09-07T10:17:49.2787804Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2787870Z     new_features = layer(features)
2025-09-07T10:17:49.2788087Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2788223Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2788228Z 
2025-09-07T10:17:49.2788321Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2788521Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2788579Z     return mod(*inputs)
2025-09-07T10:17:49.2788802Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2788865Z     features = self.features(x)
2025-09-07T10:17:49.2789114Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2789188Z     new_features = layer(features)
2025-09-07T10:17:49.2789405Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2789538Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2789541Z 
2025-09-07T10:17:49.2789635Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2789863Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2789926Z     return mod(*inputs)
2025-09-07T10:17:49.2790139Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2790210Z     features = self.features(x)
2025-09-07T10:17:49.2790424Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2790490Z     new_features = layer(features)
2025-09-07T10:17:49.2790710Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2790838Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2791070Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2791149Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2791153Z 
2025-09-07T10:17:49.2791250Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2791447Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2791504Z     return mod(*inputs)
2025-09-07T10:17:49.2791759Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2791826Z     features = self.features(x)
2025-09-07T10:17:49.2792042Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2792107Z     new_features = layer(features)
2025-09-07T10:17:49.2792324Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2792420Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2792646Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2792815Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2792818Z 
2025-09-07T10:17:49.2792912Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2793109Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2793168Z     return mod(*inputs)
2025-09-07T10:17:49.2793390Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2793458Z     features = self.features(x)
2025-09-07T10:17:49.2793673Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2793743Z     new_features = layer(features)
2025-09-07T10:17:49.2793961Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2794055Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2794284Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2794449Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2794454Z 
2025-09-07T10:17:49.2794549Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2794795Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2794859Z     return mod(*inputs)
2025-09-07T10:17:49.2795082Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2795146Z     features = self.features(x)
2025-09-07T10:17:49.2795367Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2795468Z     new_features = layer(features)
2025-09-07T10:17:49.2795683Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2795809Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2795812Z 
2025-09-07T10:17:49.2795909Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2796110Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2796169Z     return mod(*inputs)
2025-09-07T10:17:49.2796393Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2796492Z     features = self.features(x)
2025-09-07T10:17:49.2796707Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2796775Z     new_features = layer(features)
2025-09-07T10:17:49.2796991Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2797120Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2797123Z 
2025-09-07T10:17:49.2797216Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2797444Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2797502Z     return mod(*inputs)
2025-09-07T10:17:49.2797719Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2797787Z     features = self.features(x)
2025-09-07T10:17:49.2798000Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2798067Z     new_features = layer(features)
2025-09-07T10:17:49.2798280Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2798374Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2798603Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2798682Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2798685Z 
2025-09-07T10:17:49.2798954Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2799151Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2799209Z     return mod(*inputs)
2025-09-07T10:17:49.2799431Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2799496Z     features = self.features(x)
2025-09-07T10:17:49.2799713Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2799780Z     new_features = layer(features)
2025-09-07T10:17:49.2799998Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2800104Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2800331Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2800501Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2800591Z 
2025-09-07T10:17:49.2800689Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2800883Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2800947Z     return mod(*inputs)
2025-09-07T10:17:49.2801168Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2801236Z     features = self.features(x)
2025-09-07T10:17:49.2801513Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2801585Z     new_features = layer(features)
2025-09-07T10:17:49.2801802Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2801899Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2802135Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2802302Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2802305Z 
2025-09-07T10:17:49.2802407Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2802696Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2802758Z     return mod(*inputs)
2025-09-07T10:17:49.2802976Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2803043Z     features = self.features(x)
2025-09-07T10:17:49.2803268Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2803333Z     new_features = layer(features)
2025-09-07T10:17:49.2803601Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2803731Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2803734Z 
2025-09-07T10:17:49.2803833Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2804033Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2804095Z     return mod(*inputs)
2025-09-07T10:17:49.2804317Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2804383Z     features = self.features(x)
2025-09-07T10:17:49.2804600Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2804673Z     new_features = layer(features)
2025-09-07T10:17:49.2804890Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2805021Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2805025Z 
2025-09-07T10:17:49.2805126Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2805327Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2805388Z     return mod(*inputs)
2025-09-07T10:17:49.2805604Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2805673Z     features = self.features(x)
2025-09-07T10:17:49.2805891Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2805960Z     new_features = layer(features)
2025-09-07T10:17:49.2806176Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2806274Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2806547Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2806627Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2806630Z 
2025-09-07T10:17:49.2806728Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2806923Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2806987Z     return mod(*inputs)
2025-09-07T10:17:49.2807204Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2807301Z     features = self.features(x)
2025-09-07T10:17:49.2807523Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2807589Z     new_features = layer(features)
2025-09-07T10:17:49.2807810Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2807905Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2808133Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2808299Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2808338Z 
2025-09-07T10:17:49.2808502Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2808771Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2808862Z     return mod(*inputs)
2025-09-07T10:17:49.2809257Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2809380Z     features = self.features(x)
2025-09-07T10:17:49.2816909Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2817010Z     new_features = layer(features)
2025-09-07T10:17:49.2817274Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2817380Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2817638Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2817813Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2817818Z 
2025-09-07T10:17:49.2817930Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2818132Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2818198Z     return mod(*inputs)
2025-09-07T10:17:49.2818433Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2818503Z     features = self.features(x)
2025-09-07T10:17:49.2818722Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2818790Z     new_features = layer(features)
2025-09-07T10:17:49.2819012Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2819144Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2819147Z 
2025-09-07T10:17:49.2819251Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2819446Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2819505Z     return mod(*inputs)
2025-09-07T10:17:49.2819731Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2819795Z     features = self.features(x)
2025-09-07T10:17:49.2820039Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2820148Z     new_features = layer(features)
2025-09-07T10:17:49.2820390Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2820519Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2820524Z 
2025-09-07T10:17:49.2820621Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2820818Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2820914Z     return mod(*inputs)
2025-09-07T10:17:49.2821139Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2821201Z     features = self.features(x)
2025-09-07T10:17:49.2821420Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2821485Z     new_features = layer(features)
2025-09-07T10:17:49.2821701Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2821798Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2822027Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2822142Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2822145Z 
2025-09-07T10:17:49.2822246Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2822443Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2822503Z     return mod(*inputs)
2025-09-07T10:17:49.2822727Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2822826Z     features = self.features(x)
2025-09-07T10:17:49.2823053Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2823116Z     new_features = layer(features)
2025-09-07T10:17:49.2823336Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2823431Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2823664Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2823829Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2823835Z 
2025-09-07T10:17:49.2823931Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2824130Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2824186Z     return mod(*inputs)
2025-09-07T10:17:49.2824410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2824473Z     features = self.features(x)
2025-09-07T10:17:49.2824690Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2824758Z     new_features = layer(features)
2025-09-07T10:17:49.2824976Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2825075Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2825304Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2825475Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2825481Z 
2025-09-07T10:17:49.2825574Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2825836Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2825955Z     return mod(*inputs)
2025-09-07T10:17:49.2826180Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2826248Z     features = self.features(x)
2025-09-07T10:17:49.2826470Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2826533Z     new_features = layer(features)
2025-09-07T10:17:49.2826757Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2826920Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2826923Z 
2025-09-07T10:17:49.2827025Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2827223Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2827281Z     return mod(*inputs)
2025-09-07T10:17:49.2827507Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2827570Z     features = self.features(x)
2025-09-07T10:17:49.2827790Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2827889Z     new_features = layer(features)
2025-09-07T10:17:49.2828106Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2828235Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2828238Z 
2025-09-07T10:17:49.2828333Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2828528Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2828586Z     return mod(*inputs)
2025-09-07T10:17:49.2828841Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2828906Z     features = self.features(x)
2025-09-07T10:17:49.2829125Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2829189Z     new_features = layer(features)
2025-09-07T10:17:49.2829406Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2829506Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2829734Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2829811Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2829819Z 
2025-09-07T10:17:49.2829913Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2830109Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2830170Z     return mod(*inputs)
2025-09-07T10:17:49.2830400Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2830467Z     features = self.features(x)
2025-09-07T10:17:49.2830677Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2830739Z     new_features = layer(features)
2025-09-07T10:17:49.2830957Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2831052Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2831295Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2831460Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2831464Z 
2025-09-07T10:17:49.2831559Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2831798Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2831859Z     return mod(*inputs)
2025-09-07T10:17:49.2832083Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2832147Z     features = self.features(x)
2025-09-07T10:17:49.2832376Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2832476Z     new_features = layer(features)
2025-09-07T10:17:49.2832698Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2832797Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2833030Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2833201Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2833205Z 
2025-09-07T10:17:49.2833302Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2833502Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2833600Z     return mod(*inputs)
2025-09-07T10:17:49.2833823Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2833890Z     features = self.features(x)
2025-09-07T10:17:49.2834112Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2834174Z     new_features = layer(features)
2025-09-07T10:17:49.2834399Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2834560Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2834563Z 
2025-09-07T10:17:49.2834666Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2834859Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2834921Z     return mod(*inputs)
2025-09-07T10:17:49.2835141Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2835203Z     features = self.features(x)
2025-09-07T10:17:49.2835424Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2835489Z     new_features = layer(features)
2025-09-07T10:17:49.2835713Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2835842Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2835847Z 
2025-09-07T10:17:49.2835941Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2836142Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2836199Z     return mod(*inputs)
2025-09-07T10:17:49.2836427Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2836490Z     features = self.features(x)
2025-09-07T10:17:49.2836715Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2836784Z     new_features = layer(features)
2025-09-07T10:17:49.2837001Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2837100Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2837327Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2837409Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2837449Z 
2025-09-07T10:17:49.2837547Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2837743Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2837810Z     return mod(*inputs)
2025-09-07T10:17:49.2838031Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2838099Z     features = self.features(x)
2025-09-07T10:17:49.2838361Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2838428Z     new_features = layer(features)
2025-09-07T10:17:49.2838651Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2838750Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2838985Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2839149Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2839152Z 
2025-09-07T10:17:49.2839256Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2839487Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2839547Z     return mod(*inputs)
2025-09-07T10:17:49.2839769Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2839835Z     features = self.features(x)
2025-09-07T10:17:49.2840058Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2840122Z     new_features = layer(features)
2025-09-07T10:17:49.2840372Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2840472Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2840702Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2840869Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2840874Z 
2025-09-07T10:17:49.2840969Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2841163Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2841227Z     return mod(*inputs)
2025-09-07T10:17:49.2841445Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2841513Z     features = self.features(x)
2025-09-07T10:17:49.2841731Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2841800Z     new_features = layer(features)
2025-09-07T10:17:49.2842016Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2842142Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2842146Z 
2025-09-07T10:17:49.2842247Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2842437Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2842500Z     return mod(*inputs)
2025-09-07T10:17:49.2842719Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2842784Z     features = self.features(x)
2025-09-07T10:17:49.2843003Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2843065Z     new_features = layer(features)
2025-09-07T10:17:49.2843334Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2843465Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2843469Z 
2025-09-07T10:17:49.2843565Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2843770Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2843830Z     return mod(*inputs)
2025-09-07T10:17:49.2844053Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2844153Z     features = self.features(x)
2025-09-07T10:17:49.2844376Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2844438Z     new_features = layer(features)
2025-09-07T10:17:49.2844652Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2844752Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2844977Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2845058Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2845096Z 
2025-09-07T10:17:49.2845188Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2845379Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2845443Z     return mod(*inputs)
2025-09-07T10:17:49.2845662Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2845729Z     features = self.features(x)
2025-09-07T10:17:49.2845995Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2846061Z     new_features = layer(features)
2025-09-07T10:17:49.2846283Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2846376Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2846599Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2846764Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2846767Z 
2025-09-07T10:17:49.2846872Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2847068Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2847124Z     return mod(*inputs)
2025-09-07T10:17:49.2847340Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2847406Z     features = self.features(x)
2025-09-07T10:17:49.2847626Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2847687Z     new_features = layer(features)
2025-09-07T10:17:49.2847899Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2847997Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2848222Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2848389Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2848392Z 
2025-09-07T10:17:49.2848485Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2848679Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2848739Z     return mod(*inputs)
2025-09-07T10:17:49.2848989Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2849054Z     features = self.features(x)
2025-09-07T10:17:49.2849271Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2849341Z     new_features = layer(features)
2025-09-07T10:17:49.2849553Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2849678Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2849715Z 
2025-09-07T10:17:49.2849809Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2850000Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2850062Z     return mod(*inputs)
2025-09-07T10:17:49.2850281Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2850342Z     features = self.features(x)
2025-09-07T10:17:49.2850556Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2850619Z     new_features = layer(features)
2025-09-07T10:17:49.2850873Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2850998Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2851001Z 
2025-09-07T10:17:49.2851104Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2851300Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2851360Z     return mod(*inputs)
2025-09-07T10:17:49.2851578Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2851675Z     features = self.features(x)
2025-09-07T10:17:49.2851902Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2851968Z     new_features = layer(features)
2025-09-07T10:17:49.2852182Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2852285Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2852513Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2852598Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2852601Z 
2025-09-07T10:17:49.2852695Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2852894Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2852955Z     return mod(*inputs)
2025-09-07T10:17:49.2853174Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2853241Z     features = self.features(x)
2025-09-07T10:17:49.2853456Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2853524Z     new_features = layer(features)
2025-09-07T10:17:49.2853740Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2853832Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2854066Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2854228Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2854231Z 
2025-09-07T10:17:49.2854334Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2854529Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2854621Z     return mod(*inputs)
2025-09-07T10:17:49.2854846Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2854910Z     features = self.features(x)
2025-09-07T10:17:49.2855131Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2855195Z     new_features = layer(features)
2025-09-07T10:17:49.2855410Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2855544Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2855769Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2855938Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2855941Z 
2025-09-07T10:17:49.2856035Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2856236Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2856295Z     return mod(*inputs)
2025-09-07T10:17:49.2856511Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2856612Z     features = self.features(x)
2025-09-07T10:17:49.2856829Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2856901Z     new_features = layer(features)
2025-09-07T10:17:49.2857114Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2857242Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2857251Z 
2025-09-07T10:17:49.2857377Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2857574Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2857637Z     return mod(*inputs)
2025-09-07T10:17:49.2857854Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2857923Z     features = self.features(x)
2025-09-07T10:17:49.2858140Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2858203Z     new_features = layer(features)
2025-09-07T10:17:49.2858424Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2858549Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2858552Z 
2025-09-07T10:17:49.2858655Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2858849Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2858910Z     return mod(*inputs)
2025-09-07T10:17:49.2859129Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2859193Z     features = self.features(x)
2025-09-07T10:17:49.2859419Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2859483Z     new_features = layer(features)
2025-09-07T10:17:49.2859700Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2859802Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2860026Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 48, in bn_function
2025-09-07T10:17:49.2860104Z     concated_features = torch.cat(inputs, 1)
2025-09-07T10:17:49.2860107Z 
2025-09-07T10:17:49.2860201Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2860433Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2860493Z     return mod(*inputs)
2025-09-07T10:17:49.2860712Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2860783Z     features = self.features(x)
2025-09-07T10:17:49.2860996Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2861101Z     new_features = layer(features)
2025-09-07T10:17:49.2861318Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2861412Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2861638Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2861804Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2861807Z 
2025-09-07T10:17:49.2861907Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2862099Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2862196Z     return mod(*inputs)
2025-09-07T10:17:49.2862413Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2862479Z     features = self.features(x)
2025-09-07T10:17:49.2862696Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2862758Z     new_features = layer(features)
2025-09-07T10:17:49.2862978Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 88, in forward
2025-09-07T10:17:49.2863107Z     bottleneck_output = self.bn_function(prev_features)
2025-09-07T10:17:49.2863343Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 49, in bn_function
2025-09-07T10:17:49.2863509Z     bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features)))  # noqa: T484
2025-09-07T10:17:49.2863513Z 
2025-09-07T10:17:49.2863615Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2863812Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2863879Z     return mod(*inputs)
2025-09-07T10:17:49.2864101Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2864168Z     features = self.features(x)
2025-09-07T10:17:49.2864388Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2864451Z     new_features = layer(features)
2025-09-07T10:17:49.2864665Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2864800Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2864803Z 
2025-09-07T10:17:49.2864898Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2865097Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2865158Z     return mod(*inputs)
2025-09-07T10:17:49.2865376Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2865445Z     features = self.features(x)
2025-09-07T10:17:49.2865721Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 122, in forward
2025-09-07T10:17:49.2865790Z     new_features = layer(features)
2025-09-07T10:17:49.2866008Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 90, in forward
2025-09-07T10:17:49.2866173Z     new_features = self.conv2(self.relu2(self.norm2(bottleneck_output)))
2025-09-07T10:17:49.2866179Z 
2025-09-07T10:17:49.2866255Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866328Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866402Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866475Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866545Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866614Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866682Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2866814Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2867004Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2867065Z     return mod(*inputs)
2025-09-07T10:17:49.2867289Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 213, in forward
2025-09-07T10:17:49.2867350Z     features = self.features(x)
2025-09-07T10:17:49.2867570Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 124, in forward
2025-09-07T10:17:49.2867637Z     return torch.cat(features, 1)
2025-09-07T10:17:49.2867641Z 
2025-09-07T10:17:49.2867711Z cudagraph partition due to non gpu ops
2025-09-07T10:17:49.2867852Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2868044Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2868111Z     return mod(*inputs)
2025-09-07T10:17:49.2868327Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 215, in forward
2025-09-07T10:17:49.2868408Z     out = F.adaptive_avg_pool2d(out, (1, 1))
2025-09-07T10:17:49.2868411Z 
2025-09-07T10:17:49.2868505Z cudagraph partition due to non gpu ops. Found from : 
2025-09-07T10:17:49.2868729Z    File "/var/lib/jenkins/workspace/benchmarks/dynamo/torchbench.py", line 482, in forward_pass
2025-09-07T10:17:49.2868794Z     return mod(*inputs)
2025-09-07T10:17:49.2869012Z   File "/opt/conda/envs/py_3.9/lib/python3.9/site-packages/torchvision/models/densenet.py", line 217, in forward
2025-09-07T10:17:49.2869082Z     out = self.classifier(out)
2025-09-07T10:17:49.2869087Z 
2025-09-07T10:18:45.6902424Z 
2025-09-07T10:18:46.0563760Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:18:46.3623301Z running benchmark:   3% 1/30 [00:00<00:10,  2.73it/s]
2025-09-07T10:18:46.7388171Z running benchmark:   7% 2/30 [00:00<00:09,  3.02it/s]
2025-09-07T10:18:47.0495506Z running benchmark:  10% 3/30 [00:01<00:09,  2.84it/s]
2025-09-07T10:18:47.3564230Z running benchmark:  13% 4/30 [00:01<00:08,  2.98it/s]
2025-09-07T10:18:47.6638302Z running benchmark:  17% 5/30 [00:01<00:08,  3.07it/s]
2025-09-07T10:18:47.9771456Z running benchmark:  20% 6/30 [00:01<00:07,  3.13it/s]
2025-09-07T10:18:48.2867820Z running benchmark:  23% 7/30 [00:02<00:07,  3.15it/s]
2025-09-07T10:18:48.5943548Z running benchmark:  27% 8/30 [00:02<00:06,  3.18it/s]
2025-09-07T10:18:48.9005591Z running benchmark:  30% 9/30 [00:02<00:06,  3.20it/s]
2025-09-07T10:18:49.2063453Z running benchmark:  33% 10/30 [00:03<00:06,  3.22it/s]
2025-09-07T10:18:49.5120352Z running benchmark:  37% 11/30 [00:03<00:05,  3.24it/s]
2025-09-07T10:18:49.8200470Z running benchmark:  40% 12/30 [00:03<00:05,  3.25it/s]
2025-09-07T10:18:50.1289803Z running benchmark:  43% 13/30 [00:04<00:05,  3.25it/s]
2025-09-07T10:18:50.4360472Z running benchmark:  47% 14/30 [00:04<00:04,  3.24it/s]
2025-09-07T10:18:50.7487528Z running benchmark:  50% 15/30 [00:04<00:04,  3.25it/s]
2025-09-07T10:18:51.0576691Z running benchmark:  53% 16/30 [00:05<00:04,  3.23it/s]
2025-09-07T10:18:51.3642593Z running benchmark:  57% 17/30 [00:05<00:04,  3.23it/s]
2025-09-07T10:18:51.6725658Z running benchmark:  60% 18/30 [00:05<00:03,  3.24it/s]
2025-09-07T10:18:51.9834432Z running benchmark:  63% 19/30 [00:05<00:03,  3.24it/s]
2025-09-07T10:18:52.2939973Z running benchmark:  67% 20/30 [00:06<00:03,  3.23it/s]
2025-09-07T10:18:52.6016353Z running benchmark:  70% 21/30 [00:06<00:02,  3.23it/s]
2025-09-07T10:18:52.9075567Z running benchmark:  73% 22/30 [00:06<00:02,  3.24it/s]
2025-09-07T10:18:53.2149329Z running benchmark:  77% 23/30 [00:07<00:02,  3.25it/s]
2025-09-07T10:18:53.5235425Z running benchmark:  80% 24/30 [00:07<00:01,  3.25it/s]
2025-09-07T10:18:53.8315447Z running benchmark:  83% 25/30 [00:07<00:01,  3.25it/s]
2025-09-07T10:18:54.1392015Z running benchmark:  87% 26/30 [00:08<00:01,  3.25it/s]
2025-09-07T10:18:54.4504327Z running benchmark:  90% 27/30 [00:08<00:00,  3.25it/s]
2025-09-07T10:18:54.7598270Z running benchmark:  93% 28/30 [00:08<00:00,  3.24it/s]
2025-09-07T10:18:55.0715851Z running benchmark:  97% 29/30 [00:09<00:00,  3.24it/s]
2025-09-07T10:18:55.0716342Z running benchmark: 100% 30/30 [00:09<00:00,  3.23it/s]
2025-09-07T10:18:55.0716630Z running benchmark: 100% 30/30 [00:09<00:00,  3.20it/s]
2025-09-07T10:18:55.2279698Z 2.034x
2025-09-07T10:18:55.2282465Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:18:58.0345764Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:18:58.0347080Z   import pynvml  # type: ignore[import]
2025-09-07T10:19:00.0588166Z 
2025-09-07T10:19:00.2782575Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:19:00.2782989Z   what():  std::bad_array_new_length
2025-09-07T10:20:42.8811776Z Run failed with return code:  -6
2025-09-07T10:20:42.8812025Z Output:  None
2025-09-07T10:20:42.8812177Z Error:  None
2025-09-07T10:20:43.2899603Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:20:43.2900490Z   import pynvml  # type: ignore[import]
2025-09-07T10:20:45.3054094Z 
2025-09-07T10:20:45.5237675Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:20:45.5238112Z   what():  std::bad_array_new_length
2025-09-07T10:22:28.7820578Z Run failed with return code:  -6
2025-09-07T10:22:28.7820841Z Output:  None
2025-09-07T10:22:28.7821027Z Error:  None
2025-09-07T10:22:29.1931601Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:22:29.1932511Z   import pynvml  # type: ignore[import]
2025-09-07T10:22:31.2132819Z 
2025-09-07T10:22:31.4324389Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:22:31.4324781Z   what():  std::bad_array_new_length
2025-09-07T10:24:15.4846901Z Run failed with return code:  -6
2025-09-07T10:24:15.4847177Z Output:  None
2025-09-07T10:24:15.4847371Z Error:  None
2025-09-07T10:24:15.8895234Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:24:15.8896234Z   import pynvml  # type: ignore[import]
2025-09-07T10:24:17.9160962Z 
2025-09-07T10:24:18.1346248Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:24:18.1346665Z   what():  std::bad_array_new_length
2025-09-07T10:26:01.2323067Z Run failed with return code:  -6
2025-09-07T10:26:01.2323334Z Output:  None
2025-09-07T10:26:01.2323835Z Error:  None
2025-09-07T10:26:01.6437328Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:26:01.6438268Z   import pynvml  # type: ignore[import]
2025-09-07T10:26:03.6636810Z 
2025-09-07T10:26:03.8823562Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:26:03.8824249Z   what():  std::bad_array_new_length
2025-09-07T10:27:46.9815433Z Run failed with return code:  -6
2025-09-07T10:27:46.9815677Z Output:  None
2025-09-07T10:27:46.9815833Z Error:  None
2025-09-07T10:27:47.3916347Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:27:47.3917292Z   import pynvml  # type: ignore[import]
2025-09-07T10:27:49.4160992Z 
2025-09-07T10:27:49.6343548Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:27:49.6344570Z   what():  std::bad_array_new_length
2025-09-07T10:29:33.0817145Z Run failed with return code:  -6
2025-09-07T10:29:33.0817403Z Output:  None
2025-09-07T10:29:33.0817595Z Error:  None
2025-09-07T10:29:33.4916715Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:29:33.4917930Z   import pynvml  # type: ignore[import]
2025-09-07T10:29:35.5064019Z 
2025-09-07T10:29:35.7243378Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:29:35.7243769Z   what():  std::bad_array_new_length
2025-09-07T10:31:18.9310904Z Run failed with return code:  -6
2025-09-07T10:31:18.9311173Z Output:  None
2025-09-07T10:31:18.9314637Z Error:  None
2025-09-07T10:31:19.3390343Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:31:19.3391336Z   import pynvml  # type: ignore[import]
2025-09-07T10:31:21.3602669Z 
2025-09-07T10:31:21.5785044Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:31:21.5785443Z   what():  std::bad_array_new_length
2025-09-07T10:33:04.6799974Z Run failed with return code:  -6
2025-09-07T10:33:04.6800222Z Output:  None
2025-09-07T10:33:04.6800390Z Error:  None
2025-09-07T10:33:05.0911658Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:33:05.0912695Z   import pynvml  # type: ignore[import]
2025-09-07T10:33:07.1266367Z 
2025-09-07T10:33:07.3489487Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:33:07.3489904Z   what():  std::bad_array_new_length
2025-09-07T10:34:50.6816392Z Run failed with return code:  -6
2025-09-07T10:34:50.6816653Z Output:  None
2025-09-07T10:34:50.6816807Z Error:  None
2025-09-07T10:34:51.0923296Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:34:51.0926072Z   import pynvml  # type: ignore[import]
2025-09-07T10:34:53.1291340Z 
2025-09-07T10:34:53.3517489Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:34:53.3517894Z   what():  std::bad_array_new_length
2025-09-07T10:36:36.6810156Z Run failed with return code:  -6
2025-09-07T10:36:36.6810410Z Output:  None
2025-09-07T10:36:36.6810994Z Error:  None
2025-09-07T10:36:37.0907283Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:36:37.0908161Z   import pynvml  # type: ignore[import]
2025-09-07T10:36:39.1179545Z 
2025-09-07T10:36:39.3397940Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:36:39.3398357Z   what():  std::bad_array_new_length
2025-09-07T10:38:22.8324419Z Run failed with return code:  -6
2025-09-07T10:38:22.8324676Z Output:  None
2025-09-07T10:38:22.8325300Z Error:  None
2025-09-07T10:38:22.8364338Z speedup             gmean=1.17x mean=1.200x
2025-09-07T10:38:22.8366211Z abs_latency         gmean=42.26x mean=78.028x
2025-09-07T10:38:22.8366723Z compilation_latency mean=22.946 seconds
2025-09-07T10:38:22.8367331Z compression_ratio   mean=0.923x
2025-09-07T10:38:22.8370204Z eager_peak_mem      gmean=149.16x mean=195.360x
2025-09-07T10:38:22.8372503Z dynamo_peak_mem     gmean=161.78x mean=208.183x
2025-09-07T10:38:22.8374644Z calls_captured      gmean=87.14x mean=160.250x
2025-09-07T10:38:22.8376749Z unique_graphs       gmean=1.27x mean=1.583x
2025-09-07T10:38:22.8379026Z graph_breaks        gmean=0.00x mean=0.750x
2025-09-07T10:38:22.8381000Z unique_graph_breaks gmean=0.00x mean=0.167x
2025-09-07T10:38:22.8383129Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T10:38:22.8385221Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T10:38:22.8387442Z cudagraph_skips     gmean=1.27x mean=1.583x
2025-09-07T10:38:23.4082223Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *cppwrapper-true* ]]
2025-09-07T10:38:23.4082786Z + TORCHINDUCTOR_CPP_WRAPPER=1
2025-09-07T10:38:23.4083762Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --backend inductor --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv
2025-09-07T10:38:23.8061683Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:38:23.8062577Z   import pynvml  # type: ignore[import]
2025-09-07T10:38:26.2627395Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:38:26.2628292Z   import pynvml  # type: ignore[import]
2025-09-07T10:38:28.2927167Z 
2025-09-07T10:38:29.9257998Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:38:29.9258578Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:38:29.9439477Z cpu  eval  BERT_pytorch                       
2025-09-07T10:38:54.8230121Z 
2025-09-07T10:38:54.9567506Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:38:55.0962175Z running benchmark:   3% 1/30 [00:00<00:03,  7.50it/s]
2025-09-07T10:38:55.2264490Z running benchmark:   7% 2/30 [00:00<00:03,  7.30it/s]
2025-09-07T10:38:55.3553042Z running benchmark:  10% 3/30 [00:00<00:03,  7.47it/s]
2025-09-07T10:38:55.4849494Z running benchmark:  13% 4/30 [00:00<00:03,  7.58it/s]
2025-09-07T10:38:55.6140065Z running benchmark:  17% 5/30 [00:00<00:03,  7.63it/s]
2025-09-07T10:38:55.7447783Z running benchmark:  20% 6/30 [00:00<00:03,  7.67it/s]
2025-09-07T10:38:55.8742923Z running benchmark:  23% 7/30 [00:00<00:03,  7.66it/s]
2025-09-07T10:38:56.0051075Z running benchmark:  27% 8/30 [00:01<00:02,  7.68it/s]
2025-09-07T10:38:56.1353481Z running benchmark:  30% 9/30 [00:01<00:02,  7.67it/s]
2025-09-07T10:38:56.2660904Z running benchmark:  33% 10/30 [00:01<00:02,  7.67it/s]
2025-09-07T10:38:56.3948796Z running benchmark:  37% 11/30 [00:01<00:02,  7.66it/s]
2025-09-07T10:38:56.5245960Z running benchmark:  40% 12/30 [00:01<00:02,  7.70it/s]
2025-09-07T10:38:56.6538654Z running benchmark:  43% 13/30 [00:01<00:02,  7.70it/s]
2025-09-07T10:38:56.7850274Z running benchmark:  47% 14/30 [00:01<00:02,  7.71it/s]
2025-09-07T10:38:56.9145667Z running benchmark:  50% 15/30 [00:01<00:01,  7.68it/s]
2025-09-07T10:38:57.0462222Z running benchmark:  53% 16/30 [00:02<00:01,  7.69it/s]
2025-09-07T10:38:57.1750617Z running benchmark:  57% 17/30 [00:02<00:01,  7.66it/s]
2025-09-07T10:38:57.3056048Z running benchmark:  60% 18/30 [00:02<00:01,  7.69it/s]
2025-09-07T10:38:57.4351015Z running benchmark:  63% 19/30 [00:02<00:01,  7.68it/s]
2025-09-07T10:38:57.5643517Z running benchmark:  67% 20/30 [00:02<00:01,  7.70it/s]
2025-09-07T10:38:57.6934410Z running benchmark:  70% 21/30 [00:02<00:01,  7.71it/s]
2025-09-07T10:38:57.8235733Z running benchmark:  73% 22/30 [00:02<00:01,  7.72it/s]
2025-09-07T10:38:57.9548185Z running benchmark:  77% 23/30 [00:03<00:00,  7.71it/s]
2025-09-07T10:38:58.0848080Z running benchmark:  80% 24/30 [00:03<00:00,  7.68it/s]
2025-09-07T10:38:58.2141253Z running benchmark:  83% 25/30 [00:03<00:00,  7.69it/s]
2025-09-07T10:38:58.3451729Z running benchmark:  87% 26/30 [00:03<00:00,  7.70it/s]
2025-09-07T10:38:58.4752625Z running benchmark:  90% 27/30 [00:03<00:00,  7.68it/s]
2025-09-07T10:38:58.6054874Z running benchmark:  93% 28/30 [00:03<00:00,  7.68it/s]
2025-09-07T10:38:58.7356751Z running benchmark:  97% 29/30 [00:03<00:00,  7.68it/s]
2025-09-07T10:38:58.7357169Z running benchmark: 100% 30/30 [00:03<00:00,  7.69it/s]
2025-09-07T10:38:58.7357616Z running benchmark: 100% 30/30 [00:03<00:00,  7.67it/s]
2025-09-07T10:38:58.8212929Z 1.421x
2025-09-07T10:38:58.8215992Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:39:01.2059573Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:39:01.2060522Z   import pynvml  # type: ignore[import]
2025-09-07T10:39:03.2213081Z 
2025-09-07T10:39:05.4465656Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:39:05.4465989Z loading model: 0it [00:02, ?it/s]
2025-09-07T10:39:05.4560977Z cpu  eval  Background_Matting                 
2025-09-07T10:39:30.4350575Z 
2025-09-07T10:39:30.8526091Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:39:31.2558434Z running benchmark:   3% 1/30 [00:00<00:12,  2.40it/s]
2025-09-07T10:39:31.6604699Z running benchmark:   7% 2/30 [00:00<00:11,  2.45it/s]
2025-09-07T10:39:32.0695248Z running benchmark:  10% 3/30 [00:01<00:10,  2.46it/s]
2025-09-07T10:39:32.4741913Z running benchmark:  13% 4/30 [00:01<00:10,  2.45it/s]
2025-09-07T10:39:32.8789503Z running benchmark:  17% 5/30 [00:02<00:10,  2.46it/s]
2025-09-07T10:39:33.2893747Z running benchmark:  20% 6/30 [00:02<00:09,  2.46it/s]
2025-09-07T10:39:33.7284361Z running benchmark:  23% 7/30 [00:02<00:09,  2.45it/s]
2025-09-07T10:39:34.1315655Z running benchmark:  27% 8/30 [00:03<00:09,  2.39it/s]
2025-09-07T10:39:34.5404674Z running benchmark:  30% 9/30 [00:03<00:08,  2.42it/s]
2025-09-07T10:39:34.9484866Z running benchmark:  33% 10/30 [00:04<00:08,  2.43it/s]
2025-09-07T10:39:35.3583759Z running benchmark:  37% 11/30 [00:04<00:07,  2.44it/s]
2025-09-07T10:39:35.7634716Z running benchmark:  40% 12/30 [00:04<00:07,  2.44it/s]
2025-09-07T10:39:36.1685130Z running benchmark:  43% 13/30 [00:05<00:06,  2.45it/s]
2025-09-07T10:39:36.5754232Z running benchmark:  47% 14/30 [00:05<00:06,  2.45it/s]
2025-09-07T10:39:36.9800862Z running benchmark:  50% 15/30 [00:06<00:06,  2.45it/s]
2025-09-07T10:39:37.3854317Z running benchmark:  53% 16/30 [00:06<00:05,  2.46it/s]
2025-09-07T10:39:37.8651316Z running benchmark:  57% 17/30 [00:06<00:05,  2.46it/s]
2025-09-07T10:39:38.2735942Z running benchmark:  60% 18/30 [00:07<00:05,  2.33it/s]
2025-09-07T10:39:38.6799646Z running benchmark:  63% 19/30 [00:07<00:04,  2.37it/s]
2025-09-07T10:39:39.0864192Z running benchmark:  67% 20/30 [00:08<00:04,  2.39it/s]
2025-09-07T10:39:39.4942940Z running benchmark:  70% 21/30 [00:08<00:03,  2.41it/s]
2025-09-07T10:39:39.8984437Z running benchmark:  73% 22/30 [00:09<00:03,  2.43it/s]
2025-09-07T10:39:40.3095539Z running benchmark:  77% 23/30 [00:09<00:02,  2.44it/s]
2025-09-07T10:39:40.7144454Z running benchmark:  80% 24/30 [00:09<00:02,  2.44it/s]
2025-09-07T10:39:41.1195269Z running benchmark:  83% 25/30 [00:10<00:02,  2.45it/s]
2025-09-07T10:39:41.5862137Z running benchmark:  87% 26/30 [00:10<00:01,  2.45it/s]
2025-09-07T10:39:41.9936122Z running benchmark:  90% 27/30 [00:11<00:01,  2.35it/s]
2025-09-07T10:39:42.3974941Z running benchmark:  93% 28/30 [00:11<00:00,  2.38it/s]
2025-09-07T10:39:42.8036919Z running benchmark:  97% 29/30 [00:11<00:00,  2.41it/s]
2025-09-07T10:39:42.8037279Z running benchmark: 100% 30/30 [00:12<00:00,  2.43it/s]
2025-09-07T10:39:42.8037564Z running benchmark: 100% 30/30 [00:12<00:00,  2.43it/s]
2025-09-07T10:39:42.9201294Z 0.870x
2025-09-07T10:39:42.9205518Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:39:45.5695484Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:39:45.5696384Z   import pynvml  # type: ignore[import]
2025-09-07T10:39:47.5880222Z 
2025-09-07T10:39:49.7132591Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:39:49.7132873Z loading model: 0it [00:02, ?it/s]
2025-09-07T10:39:49.7166874Z cpu  eval  LearningToPaint                    
2025-09-07T10:40:01.6986044Z 
2025-09-07T10:40:01.8001937Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:40:01.9655969Z running benchmark:   7% 2/30 [00:00<00:01, 19.86it/s]
2025-09-07T10:40:02.1076443Z running benchmark:  13% 4/30 [00:00<00:01, 14.38it/s]
2025-09-07T10:40:02.2475618Z running benchmark:  23% 7/30 [00:00<00:01, 17.49it/s]
2025-09-07T10:40:02.3893498Z running benchmark:  33% 10/30 [00:00<00:01, 19.05it/s]
2025-09-07T10:40:02.5340231Z running benchmark:  43% 13/30 [00:00<00:00, 19.81it/s]
2025-09-07T10:40:02.6722139Z running benchmark:  53% 16/30 [00:00<00:00, 20.14it/s]
2025-09-07T10:40:02.8126872Z running benchmark:  63% 19/30 [00:00<00:00, 20.64it/s]
2025-09-07T10:40:02.9547415Z running benchmark:  73% 22/30 [00:01<00:00, 20.87it/s]
2025-09-07T10:40:03.0927241Z running benchmark:  83% 25/30 [00:01<00:00, 20.95it/s]
2025-09-07T10:40:03.1885696Z running benchmark:  93% 28/30 [00:01<00:00, 21.19it/s]
2025-09-07T10:40:03.1886056Z running benchmark: 100% 30/30 [00:01<00:00, 20.14it/s]
2025-09-07T10:40:03.2815987Z 1.209x
2025-09-07T10:40:03.2818720Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:40:05.6367720Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:40:05.6368845Z   import pynvml  # type: ignore[import]
2025-09-07T10:40:07.6718299Z 
2025-09-07T10:40:09.1377505Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T10:40:09.6919212Z 
2025-09-07T10:40:09.6919623Z loading model: 0it [00:02, ?it/s]
2025-09-07T10:40:09.6920012Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T10:40:09.6920367Z cpu  eval  Super_SloMo                        
2025-09-07T10:40:09.6921051Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T10:40:51.5412628Z 
2025-09-07T10:40:52.3101511Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:40:53.0749769Z running benchmark:   3% 1/30 [00:00<00:22,  1.30it/s]
2025-09-07T10:40:53.8300288Z running benchmark:   7% 2/30 [00:01<00:21,  1.30it/s]
2025-09-07T10:40:54.5840224Z running benchmark:  10% 3/30 [00:02<00:20,  1.31it/s]
2025-09-07T10:40:55.4082101Z running benchmark:  13% 4/30 [00:03<00:19,  1.32it/s]
2025-09-07T10:40:56.1662040Z running benchmark:  17% 5/30 [00:03<00:19,  1.28it/s]
2025-09-07T10:40:56.9255737Z running benchmark:  20% 6/30 [00:04<00:18,  1.29it/s]
2025-09-07T10:40:57.6819164Z running benchmark:  23% 7/30 [00:05<00:17,  1.30it/s]
2025-09-07T10:40:58.4325027Z running benchmark:  27% 8/30 [00:06<00:16,  1.31it/s]
2025-09-07T10:40:59.2566902Z running benchmark:  30% 9/30 [00:06<00:15,  1.31it/s]
2025-09-07T10:41:00.0069634Z running benchmark:  33% 10/30 [00:07<00:15,  1.28it/s]
2025-09-07T10:41:00.7654297Z running benchmark:  37% 11/30 [00:08<00:14,  1.30it/s]
2025-09-07T10:41:01.5121281Z running benchmark:  40% 12/30 [00:09<00:13,  1.30it/s]
2025-09-07T10:41:02.2740541Z running benchmark:  43% 13/30 [00:09<00:12,  1.31it/s]
2025-09-07T10:41:03.0935277Z running benchmark:  47% 14/30 [00:10<00:12,  1.31it/s]
2025-09-07T10:41:03.8434620Z running benchmark:  50% 15/30 [00:11<00:11,  1.28it/s]
2025-09-07T10:41:04.5977362Z running benchmark:  53% 16/30 [00:12<00:10,  1.30it/s]
2025-09-07T10:41:05.3556437Z running benchmark:  57% 17/30 [00:13<00:09,  1.31it/s]
2025-09-07T10:41:06.1083426Z running benchmark:  60% 18/30 [00:13<00:09,  1.31it/s]
2025-09-07T10:41:06.8699244Z running benchmark:  63% 19/30 [00:14<00:08,  1.32it/s]
2025-09-07T10:41:07.6938294Z running benchmark:  67% 20/30 [00:15<00:07,  1.32it/s]
2025-09-07T10:41:08.4506985Z running benchmark:  70% 21/30 [00:16<00:07,  1.28it/s]
2025-09-07T10:41:09.2068079Z running benchmark:  73% 22/30 [00:16<00:06,  1.29it/s]
2025-09-07T10:41:09.9607768Z running benchmark:  77% 23/30 [00:17<00:05,  1.30it/s]
2025-09-07T10:41:10.7093190Z running benchmark:  80% 24/30 [00:18<00:04,  1.31it/s]
2025-09-07T10:41:11.5418547Z running benchmark:  83% 25/30 [00:19<00:03,  1.32it/s]
2025-09-07T10:41:12.2944783Z running benchmark:  87% 26/30 [00:20<00:03,  1.28it/s]
2025-09-07T10:41:13.0508601Z running benchmark:  90% 27/30 [00:20<00:02,  1.29it/s]
2025-09-07T10:41:13.8047030Z running benchmark:  93% 28/30 [00:21<00:01,  1.30it/s]
2025-09-07T10:41:14.5631426Z running benchmark:  97% 29/30 [00:22<00:00,  1.31it/s]
2025-09-07T10:41:14.5631753Z running benchmark: 100% 30/30 [00:23<00:00,  1.31it/s]
2025-09-07T10:41:14.5632035Z running benchmark: 100% 30/30 [00:23<00:00,  1.30it/s]
2025-09-07T10:41:14.7044353Z 1.119x
2025-09-07T10:41:14.7046738Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:41:17.6983659Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:41:17.6984628Z   import pynvml  # type: ignore[import]
2025-09-07T10:41:19.7189064Z 
2025-09-07T10:41:20.5689045Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:41:20.5689338Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:41:20.5744775Z cpu  eval  alexnet                            
2025-09-07T10:41:30.8974277Z 
2025-09-07T10:41:31.0323564Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:41:31.1625133Z running benchmark:   7% 2/30 [00:00<00:01, 14.86it/s]
2025-09-07T10:41:31.2913342Z running benchmark:  13% 4/30 [00:00<00:01, 15.16it/s]
2025-09-07T10:41:31.4217409Z running benchmark:  20% 6/30 [00:00<00:01, 15.32it/s]
2025-09-07T10:41:31.6183831Z running benchmark:  27% 8/30 [00:00<00:01, 15.33it/s]
2025-09-07T10:41:31.7483557Z running benchmark:  33% 10/30 [00:00<00:01, 12.96it/s]
2025-09-07T10:41:31.8785898Z running benchmark:  40% 12/30 [00:00<00:01, 13.69it/s]
2025-09-07T10:41:32.0082894Z running benchmark:  47% 14/30 [00:00<00:01, 14.20it/s]
2025-09-07T10:41:32.1362574Z running benchmark:  53% 16/30 [00:01<00:00, 14.56it/s]
2025-09-07T10:41:32.2686700Z running benchmark:  60% 18/30 [00:01<00:00, 14.88it/s]
2025-09-07T10:41:32.4011229Z running benchmark:  67% 20/30 [00:01<00:00, 14.95it/s]
2025-09-07T10:41:32.5329228Z running benchmark:  73% 22/30 [00:01<00:00, 15.00it/s]
2025-09-07T10:41:32.6633634Z running benchmark:  80% 24/30 [00:01<00:00, 15.05it/s]
2025-09-07T10:41:32.7945002Z running benchmark:  87% 26/30 [00:01<00:00, 15.14it/s]
2025-09-07T10:41:32.9235368Z running benchmark:  93% 28/30 [00:01<00:00, 15.17it/s]
2025-09-07T10:41:32.9236260Z running benchmark: 100% 30/30 [00:02<00:00, 15.27it/s]
2025-09-07T10:41:32.9237868Z running benchmark: 100% 30/30 [00:02<00:00, 14.81it/s]
2025-09-07T10:41:32.9980024Z 1.461x
2025-09-07T10:41:32.9983716Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:41:35.0632864Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:41:35.0633730Z   import pynvml  # type: ignore[import]
2025-09-07T10:41:37.0879744Z 
2025-09-07T10:41:38.5861912Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:41:38.5862207Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:41:38.5870720Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T10:41:45.9394434Z 
2025-09-07T10:41:46.0588855Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:41:46.1728697Z running benchmark:  10% 3/30 [00:00<00:01, 25.21it/s]
2025-09-07T10:41:46.2879990Z running benchmark:  20% 6/30 [00:00<00:00, 25.84it/s]
2025-09-07T10:41:46.4023515Z running benchmark:  30% 9/30 [00:00<00:00, 25.94it/s]
2025-09-07T10:41:46.5165632Z running benchmark:  40% 12/30 [00:00<00:00, 26.06it/s]
2025-09-07T10:41:46.6306839Z running benchmark:  50% 15/30 [00:00<00:00, 26.13it/s]
2025-09-07T10:41:46.7459192Z running benchmark:  60% 18/30 [00:00<00:00, 26.18it/s]
2025-09-07T10:41:46.8616784Z running benchmark:  70% 21/30 [00:00<00:00, 26.13it/s]
2025-09-07T10:41:46.9772042Z running benchmark:  80% 24/30 [00:00<00:00, 26.07it/s]
2025-09-07T10:41:47.0925741Z running benchmark:  90% 27/30 [00:01<00:00, 26.04it/s]
2025-09-07T10:41:47.0926080Z running benchmark: 100% 30/30 [00:01<00:00, 26.03it/s]
2025-09-07T10:41:47.0926369Z running benchmark: 100% 30/30 [00:01<00:00, 26.02it/s]
2025-09-07T10:41:47.1562879Z 1.648x
2025-09-07T10:41:47.1566323Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:41:49.2175398Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:41:49.2176295Z   import pynvml  # type: ignore[import]
2025-09-07T10:41:51.2431028Z 
2025-09-07T10:41:52.7434616Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:41:52.7434938Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:41:52.7439404Z cpu  eval  basic_gnn_gcn                      
2025-09-07T10:42:03.2968833Z 
2025-09-07T10:42:03.4151723Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:42:03.5300367Z running benchmark:   7% 2/30 [00:00<00:01, 16.97it/s]
2025-09-07T10:42:03.6416050Z running benchmark:  13% 4/30 [00:00<00:01, 17.22it/s]
2025-09-07T10:42:03.7496300Z running benchmark:  20% 6/30 [00:00<00:01, 17.53it/s]
2025-09-07T10:42:03.8584466Z running benchmark:  27% 8/30 [00:00<00:01, 17.91it/s]
2025-09-07T10:42:03.9694869Z running benchmark:  33% 10/30 [00:00<00:01, 18.08it/s]
2025-09-07T10:42:04.0801642Z running benchmark:  40% 12/30 [00:00<00:00, 18.05it/s]
2025-09-07T10:42:04.2656658Z running benchmark:  47% 14/30 [00:00<00:00, 18.06it/s]
2025-09-07T10:42:04.3732610Z running benchmark:  53% 16/30 [00:00<00:00, 14.87it/s]
2025-09-07T10:42:04.4851374Z running benchmark:  60% 18/30 [00:01<00:00, 15.86it/s]
2025-09-07T10:42:04.5958143Z running benchmark:  67% 20/30 [00:01<00:00, 16.43it/s]
2025-09-07T10:42:04.7084387Z running benchmark:  73% 22/30 [00:01<00:00, 16.90it/s]
2025-09-07T10:42:04.8217387Z running benchmark:  80% 24/30 [00:01<00:00, 17.16it/s]
2025-09-07T10:42:04.9307873Z running benchmark:  87% 26/30 [00:01<00:00, 17.30it/s]
2025-09-07T10:42:05.0434135Z running benchmark:  93% 28/30 [00:01<00:00, 17.60it/s]
2025-09-07T10:42:05.0434903Z running benchmark: 100% 30/30 [00:01<00:00, 17.65it/s]
2025-09-07T10:42:05.0435176Z running benchmark: 100% 30/30 [00:01<00:00, 17.18it/s]
2025-09-07T10:42:05.0922315Z 1.128x
2025-09-07T10:42:05.0925910Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:42:07.1318352Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:42:07.1319520Z   import pynvml  # type: ignore[import]
2025-09-07T10:42:09.1553752Z 
2025-09-07T10:42:10.6417872Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:42:10.6418173Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:42:10.6424540Z cpu  eval  basic_gnn_gin                      
2025-09-07T10:42:17.8678655Z 
2025-09-07T10:42:18.0067200Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:42:18.1436966Z running benchmark:  10% 3/30 [00:00<00:01, 21.67it/s]
2025-09-07T10:42:18.2821147Z running benchmark:  20% 6/30 [00:00<00:01, 21.80it/s]
2025-09-07T10:42:18.4186368Z running benchmark:  30% 9/30 [00:00<00:00, 21.75it/s]
2025-09-07T10:42:18.5569326Z running benchmark:  40% 12/30 [00:00<00:00, 21.83it/s]
2025-09-07T10:42:18.6933659Z running benchmark:  50% 15/30 [00:00<00:00, 21.79it/s]
2025-09-07T10:42:18.8312213Z running benchmark:  60% 18/30 [00:00<00:00, 21.85it/s]
2025-09-07T10:42:18.9682959Z running benchmark:  70% 21/30 [00:00<00:00, 21.82it/s]
2025-09-07T10:42:19.1058084Z running benchmark:  80% 24/30 [00:01<00:00, 21.84it/s]
2025-09-07T10:42:19.2414574Z running benchmark:  90% 27/30 [00:01<00:00, 21.84it/s]
2025-09-07T10:42:19.2414907Z running benchmark: 100% 30/30 [00:01<00:00, 21.92it/s]
2025-09-07T10:42:19.2415167Z running benchmark: 100% 30/30 [00:01<00:00, 21.84it/s]
2025-09-07T10:42:19.2894182Z 1.051x
2025-09-07T10:42:19.2897923Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:42:21.3328446Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:42:21.3329402Z   import pynvml  # type: ignore[import]
2025-09-07T10:42:23.3394933Z 
2025-09-07T10:42:24.8239055Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:42:24.8239334Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:42:24.8244907Z cpu  eval  basic_gnn_sage                     
2025-09-07T10:42:32.0675458Z 
2025-09-07T10:42:32.2063997Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:42:32.3449170Z running benchmark:  10% 3/30 [00:00<00:01, 21.68it/s]
2025-09-07T10:42:32.4806587Z running benchmark:  20% 6/30 [00:00<00:01, 21.66it/s]
2025-09-07T10:42:32.6161876Z running benchmark:  30% 9/30 [00:00<00:00, 21.86it/s]
2025-09-07T10:42:32.8224959Z running benchmark:  40% 12/30 [00:00<00:00, 21.96it/s]
2025-09-07T10:42:32.9599563Z running benchmark:  50% 15/30 [00:00<00:00, 18.55it/s]
2025-09-07T10:42:33.0949581Z running benchmark:  60% 18/30 [00:00<00:00, 19.55it/s]
2025-09-07T10:42:33.2345671Z running benchmark:  70% 21/30 [00:01<00:00, 20.35it/s]
2025-09-07T10:42:33.3709849Z running benchmark:  80% 24/30 [00:01<00:00, 20.70it/s]
2025-09-07T10:42:33.5062004Z running benchmark:  90% 27/30 [00:01<00:00, 21.08it/s]
2025-09-07T10:42:33.5062304Z running benchmark: 100% 30/30 [00:01<00:00, 21.41it/s]
2025-09-07T10:42:33.5062587Z running benchmark: 100% 30/30 [00:01<00:00, 20.86it/s]
2025-09-07T10:42:33.5536121Z 1.088x
2025-09-07T10:42:33.5539424Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:42:35.5923580Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:42:35.5924752Z   import pynvml  # type: ignore[import]
2025-09-07T10:42:37.6107102Z 
2025-09-07T10:42:37.8614431Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:42:37.8614742Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:42:37.8625593Z cpu  eval  dcgan                              
2025-09-07T10:42:46.3504392Z 
2025-09-07T10:42:46.4525151Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:42:46.5713270Z running benchmark:  17% 5/30 [00:00<00:00, 49.22it/s]
2025-09-07T10:42:46.6899402Z running benchmark:  37% 11/30 [00:00<00:00, 50.00it/s]
2025-09-07T10:42:46.8079501Z running benchmark:  57% 17/30 [00:00<00:00, 50.29it/s]
2025-09-07T10:42:46.9250280Z running benchmark:  77% 23/30 [00:00<00:00, 50.50it/s]
2025-09-07T10:42:46.9448347Z running benchmark:  97% 29/30 [00:00<00:00, 50.77it/s]
2025-09-07T10:42:46.9448695Z running benchmark: 100% 30/30 [00:00<00:00, 50.48it/s]
2025-09-07T10:42:46.9967071Z 0.976x
2025-09-07T10:42:46.9970168Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:42:49.0169056Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:42:49.0170072Z   import pynvml  # type: ignore[import]
2025-09-07T10:42:51.0345323Z 
2025-09-07T10:42:52.7193853Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:42:52.7194128Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:42:52.7383098Z cpu  eval  demucs                             
2025-09-07T10:43:05.3314086Z 
2025-09-07T10:43:05.4617698Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:43:05.5906821Z running benchmark:   3% 1/30 [00:00<00:03,  7.68it/s]
2025-09-07T10:43:05.7175632Z running benchmark:   7% 2/30 [00:00<00:03,  7.73it/s]
2025-09-07T10:43:05.8455249Z running benchmark:  10% 3/30 [00:00<00:03,  7.80it/s]
2025-09-07T10:43:05.9739547Z running benchmark:  13% 4/30 [00:00<00:03,  7.80it/s]
2025-09-07T10:43:06.1035789Z running benchmark:  17% 5/30 [00:00<00:03,  7.80it/s]
2025-09-07T10:43:06.2319295Z running benchmark:  20% 6/30 [00:00<00:03,  7.77it/s]
2025-09-07T10:43:06.3605500Z running benchmark:  23% 7/30 [00:00<00:02,  7.78it/s]
2025-09-07T10:43:06.4896202Z running benchmark:  27% 8/30 [00:01<00:02,  7.78it/s]
2025-09-07T10:43:06.6163500Z running benchmark:  30% 9/30 [00:01<00:02,  7.77it/s]
2025-09-07T10:43:06.7435261Z running benchmark:  33% 10/30 [00:01<00:02,  7.80it/s]
2025-09-07T10:43:06.8713659Z running benchmark:  37% 11/30 [00:01<00:02,  7.82it/s]
2025-09-07T10:43:06.9989806Z running benchmark:  40% 12/30 [00:01<00:02,  7.82it/s]
2025-09-07T10:43:07.1277322Z running benchmark:  43% 13/30 [00:01<00:02,  7.83it/s]
2025-09-07T10:43:07.2557992Z running benchmark:  47% 14/30 [00:01<00:02,  7.81it/s]
2025-09-07T10:43:07.3844359Z running benchmark:  50% 15/30 [00:01<00:01,  7.81it/s]
2025-09-07T10:43:07.5125546Z running benchmark:  53% 16/30 [00:02<00:01,  7.80it/s]
2025-09-07T10:43:07.6403922Z running benchmark:  57% 17/30 [00:02<00:01,  7.80it/s]
2025-09-07T10:43:07.7684390Z running benchmark:  60% 18/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:43:07.8971372Z running benchmark:  63% 19/30 [00:02<00:01,  7.81it/s]
2025-09-07T10:43:08.0255558Z running benchmark:  67% 20/30 [00:02<00:01,  7.80it/s]
2025-09-07T10:43:08.1550256Z running benchmark:  70% 21/30 [00:02<00:01,  7.79it/s]
2025-09-07T10:43:08.2834708Z running benchmark:  73% 22/30 [00:02<00:01,  7.77it/s]
2025-09-07T10:43:08.4119064Z running benchmark:  77% 23/30 [00:02<00:00,  7.78it/s]
2025-09-07T10:43:08.5415901Z running benchmark:  80% 24/30 [00:03<00:00,  7.78it/s]
2025-09-07T10:43:08.6697221Z running benchmark:  83% 25/30 [00:03<00:00,  7.76it/s]
2025-09-07T10:43:08.7976089Z running benchmark:  87% 26/30 [00:03<00:00,  7.77it/s]
2025-09-07T10:43:08.9253813Z running benchmark:  90% 27/30 [00:03<00:00,  7.79it/s]
2025-09-07T10:43:09.0539470Z running benchmark:  93% 28/30 [00:03<00:00,  7.80it/s]
2025-09-07T10:43:09.1829204Z running benchmark:  97% 29/30 [00:03<00:00,  7.79it/s]
2025-09-07T10:43:09.1829591Z running benchmark: 100% 30/30 [00:03<00:00,  7.78it/s]
2025-09-07T10:43:09.1829882Z running benchmark: 100% 30/30 [00:03<00:00,  7.79it/s]
2025-09-07T10:43:09.2870797Z 1.042x
2025-09-07T10:43:09.2873646Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:43:11.3707000Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:43:11.3707899Z   import pynvml  # type: ignore[import]
2025-09-07T10:43:13.3947570Z 
2025-09-07T10:43:14.4063430Z loading model: 0it [00:00, ?it/s]
2025-09-07T10:43:14.4063723Z loading model: 0it [00:01, ?it/s]
2025-09-07T10:43:14.4218062Z cpu  eval  densenet121                        
2025-09-07T10:44:10.5614729Z 
2025-09-07T10:44:10.8743617Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T10:44:11.1812422Z running benchmark:   3% 1/30 [00:00<00:09,  3.20it/s]
2025-09-07T10:44:11.4888341Z running benchmark:   7% 2/30 [00:00<00:08,  3.23it/s]
2025-09-07T10:44:11.7959527Z running benchmark:  10% 3/30 [00:00<00:08,  3.24it/s]
2025-09-07T10:44:12.1039605Z running benchmark:  13% 4/30 [00:01<00:08,  3.25it/s]
2025-09-07T10:44:12.4101251Z running benchmark:  17% 5/30 [00:01<00:07,  3.25it/s]
2025-09-07T10:44:12.7165662Z running benchmark:  20% 6/30 [00:01<00:07,  3.25it/s]
2025-09-07T10:44:13.0290181Z running benchmark:  23% 7/30 [00:02<00:07,  3.26it/s]
2025-09-07T10:44:13.3402130Z running benchmark:  27% 8/30 [00:02<00:06,  3.24it/s]
2025-09-07T10:44:13.6472326Z running benchmark:  30% 9/30 [00:02<00:06,  3.23it/s]
2025-09-07T10:44:13.9546936Z running benchmark:  33% 10/30 [00:03<00:06,  3.24it/s]
2025-09-07T10:44:14.2621325Z running benchmark:  37% 11/30 [00:03<00:05,  3.24it/s]
2025-09-07T10:44:14.6411150Z running benchmark:  40% 12/30 [00:03<00:05,  3.25it/s]
2025-09-07T10:44:14.9500997Z running benchmark:  43% 13/30 [00:04<00:05,  3.03it/s]
2025-09-07T10:44:15.2604931Z running benchmark:  47% 14/30 [00:04<00:05,  3.09it/s]
2025-09-07T10:44:15.5698024Z running benchmark:  50% 15/30 [00:04<00:04,  3.13it/s]
2025-09-07T10:44:15.8783149Z running benchmark:  53% 16/30 [00:05<00:04,  3.16it/s]
2025-09-07T10:44:16.1873997Z running benchmark:  57% 17/30 [00:05<00:04,  3.18it/s]
2025-09-07T10:44:16.4929797Z running benchmark:  60% 18/30 [00:05<00:03,  3.20it/s]
2025-09-07T10:44:16.8025115Z running benchmark:  63% 19/30 [00:05<00:03,  3.22it/s]
2025-09-07T10:44:17.1110966Z running benchmark:  67% 20/30 [00:06<00:03,  3.22it/s]
2025-09-07T10:44:17.4163247Z running benchmark:  70% 21/30 [00:06<00:02,  3.23it/s]
2025-09-07T10:44:17.7225934Z running benchmark:  73% 22/30 [00:06<00:02,  3.24it/s]
2025-09-07T10:44:18.0288987Z running benchmark:  77% 23/30 [00:07<00:02,  3.25it/s]
2025-09-07T10:44:18.3372556Z running benchmark:  80% 24/30 [00:07<00:01,  3.25it/s]
2025-09-07T10:44:18.7154982Z running benchmark:  83% 25/30 [00:07<00:01,  3.25it/s]
2025-09-07T10:44:19.0240086Z running benchmark:  87% 26/30 [00:08<00:01,  3.04it/s]
2025-09-07T10:44:19.3335873Z running benchmark:  90% 27/30 [00:08<00:00,  3.10it/s]
2025-09-07T10:44:19.6400419Z running benchmark:  93% 28/30 [00:08<00:00,  3.14it/s]
2025-09-07T10:44:19.9480388Z running benchmark:  97% 29/30 [00:09<00:00,  3.17it/s]
2025-09-07T10:44:19.9480737Z running benchmark: 100% 30/30 [00:09<00:00,  3.20it/s]
2025-09-07T10:44:19.9481044Z running benchmark: 100% 30/30 [00:09<00:00,  3.20it/s]
2025-09-07T10:44:20.1015734Z 2.197x
2025-09-07T10:44:20.1019316Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T10:44:23.4288779Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:44:23.4289962Z   import pynvml  # type: ignore[import]
2025-09-07T10:44:25.4575742Z 
2025-09-07T10:44:25.6766188Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:44:25.6766584Z   what():  std::bad_array_new_length
2025-09-07T10:46:08.8240500Z Run failed with return code:  -6
2025-09-07T10:46:08.8240772Z Output:  None
2025-09-07T10:46:08.8240922Z Error:  None
2025-09-07T10:46:09.2333735Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:46:09.2334667Z   import pynvml  # type: ignore[import]
2025-09-07T10:46:11.2562780Z 
2025-09-07T10:46:11.4761460Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:46:11.4761893Z   what():  std::bad_array_new_length
2025-09-07T10:47:54.5823062Z Run failed with return code:  -6
2025-09-07T10:47:54.5823331Z Output:  None
2025-09-07T10:47:54.5823488Z Error:  None
2025-09-07T10:47:54.9916676Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:47:54.9917546Z   import pynvml  # type: ignore[import]
2025-09-07T10:47:57.0099688Z 
2025-09-07T10:47:57.2284531Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:47:57.2284964Z   what():  std::bad_array_new_length
2025-09-07T10:49:40.1838875Z Run failed with return code:  -6
2025-09-07T10:49:40.1839130Z Output:  None
2025-09-07T10:49:40.1839283Z Error:  None
2025-09-07T10:49:40.5923395Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:49:40.5924261Z   import pynvml  # type: ignore[import]
2025-09-07T10:49:42.6162101Z 
2025-09-07T10:49:42.8352840Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:49:42.8353218Z   what():  std::bad_array_new_length
2025-09-07T10:51:26.3393295Z Run failed with return code:  -6
2025-09-07T10:51:26.3393507Z Output:  None
2025-09-07T10:51:26.3393666Z Error:  None
2025-09-07T10:51:26.7518632Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:51:26.7519999Z   import pynvml  # type: ignore[import]
2025-09-07T10:51:28.7802102Z 
2025-09-07T10:51:28.9985586Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:51:28.9985986Z   what():  std::bad_array_new_length
2025-09-07T10:53:12.1458061Z Run failed with return code:  -6
2025-09-07T10:53:12.1458330Z Output:  None
2025-09-07T10:53:12.1458482Z Error:  None
2025-09-07T10:53:12.5566429Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:53:12.5567644Z   import pynvml  # type: ignore[import]
2025-09-07T10:53:14.5678529Z 
2025-09-07T10:53:14.7851706Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:53:14.7852158Z   what():  std::bad_array_new_length
2025-09-07T10:54:57.9033956Z Run failed with return code:  -6
2025-09-07T10:54:57.9034221Z Output:  None
2025-09-07T10:54:57.9034382Z Error:  None
2025-09-07T10:54:58.3153995Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:54:58.3154943Z   import pynvml  # type: ignore[import]
2025-09-07T10:55:00.3503637Z 
2025-09-07T10:55:00.5692363Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:55:00.5692785Z   what():  std::bad_array_new_length
2025-09-07T10:56:43.9596579Z Run failed with return code:  -6
2025-09-07T10:56:43.9596834Z Output:  None
2025-09-07T10:56:43.9596990Z Error:  None
2025-09-07T10:56:44.3711962Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:56:44.3712914Z   import pynvml  # type: ignore[import]
2025-09-07T10:56:46.3901156Z 
2025-09-07T10:56:46.6089600Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:56:46.6089997Z   what():  std::bad_array_new_length
2025-09-07T10:58:29.6677428Z Run failed with return code:  -6
2025-09-07T10:58:29.6677713Z Output:  None
2025-09-07T10:58:29.6677875Z Error:  None
2025-09-07T10:58:30.0791103Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T10:58:30.0792002Z   import pynvml  # type: ignore[import]
2025-09-07T10:58:32.1028546Z 
2025-09-07T10:58:32.3216365Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T10:58:32.3216769Z   what():  std::bad_array_new_length
2025-09-07T11:00:16.1232274Z Run failed with return code:  -6
2025-09-07T11:00:16.1232528Z Output:  None
2025-09-07T11:00:16.1232682Z Error:  None
2025-09-07T11:00:16.5364389Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:00:16.5365273Z   import pynvml  # type: ignore[import]
2025-09-07T11:00:18.5531770Z 
2025-09-07T11:00:18.7711041Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:00:18.7711829Z   what():  std::bad_array_new_length
2025-09-07T11:02:02.0775989Z Run failed with return code:  -6
2025-09-07T11:02:02.0776260Z Output:  None
2025-09-07T11:02:02.0776409Z Error:  None
2025-09-07T11:02:02.4859204Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:02:02.4860080Z   import pynvml  # type: ignore[import]
2025-09-07T11:02:04.5029374Z 
2025-09-07T11:02:04.7214698Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:02:04.7215492Z   what():  std::bad_array_new_length
2025-09-07T11:03:48.2351017Z Run failed with return code:  -6
2025-09-07T11:03:48.2351282Z Output:  None
2025-09-07T11:03:48.2351442Z Error:  None
2025-09-07T11:03:48.2394307Z speedup             gmean=1.23x mean=1.267x
2025-09-07T11:03:48.2397495Z abs_latency         gmean=41.00x mean=77.036x
2025-09-07T11:03:48.2397723Z compilation_latency mean=17.355 seconds
2025-09-07T11:03:48.2398686Z compression_ratio   mean=0.927x
2025-09-07T11:03:48.2401332Z eager_peak_mem      gmean=149.25x mean=195.475x
2025-09-07T11:03:48.2403904Z dynamo_peak_mem     gmean=161.03x mean=207.054x
2025-09-07T11:03:48.2405833Z calls_captured      gmean=87.14x mean=160.250x
2025-09-07T11:03:48.2407822Z unique_graphs       gmean=1.27x mean=1.583x
2025-09-07T11:03:48.2409938Z graph_breaks        gmean=0.00x mean=0.750x
2025-09-07T11:03:48.2411991Z unique_graph_breaks gmean=0.00x mean=0.167x
2025-09-07T11:03:48.2414121Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T11:03:48.2416305Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T11:03:48.2418391Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T11:03:48.7943067Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *freezing_cudagraphs-true* ]]
2025-09-07T11:03:48.7943917Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *freeze_autotune_cudagraphs-true* ]]
2025-09-07T11:03:48.7944673Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *aotinductor-true* ]]
2025-09-07T11:03:48.7945127Z + [[ inference == \i\n\f\e\r\e\n\c\e ]]
2025-09-07T11:03:48.7945339Z + [[ performance == \a\c\c\u\r\a\c\y ]]
2025-09-07T11:03:48.7946387Z + taskset -c 0-94 python benchmarks/dynamo/torchbench.py --performance --cold-start-latency --inference --bfloat16 --export-aot-inductor --disable-cudagraphs --device cpu --total-partitions 4 --partition-id 0 --output /var/lib/jenkins/workspace/test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv
2025-09-07T11:03:49.1936533Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:03:49.1937519Z   import pynvml  # type: ignore[import]
2025-09-07T11:03:51.6437189Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:03:51.6438061Z   import pynvml  # type: ignore[import]
2025-09-07T11:03:53.6598062Z 
2025-09-07T11:03:55.3032801Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:03:55.3033147Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:03:55.3227721Z cpu  eval  BERT_pytorch                       
2025-09-07T11:04:21.3950604Z 
2025-09-07T11:04:21.5326526Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:04:21.6593143Z running benchmark:   3% 1/30 [00:00<00:03,  7.29it/s]
2025-09-07T11:04:21.7863011Z running benchmark:   7% 2/30 [00:00<00:03,  7.63it/s]
2025-09-07T11:04:21.9137282Z running benchmark:  10% 3/30 [00:00<00:03,  7.74it/s]
2025-09-07T11:04:22.0406805Z running benchmark:  13% 4/30 [00:00<00:03,  7.78it/s]
2025-09-07T11:04:22.1681629Z running benchmark:  17% 5/30 [00:00<00:03,  7.82it/s]
2025-09-07T11:04:22.2955478Z running benchmark:  20% 6/30 [00:00<00:03,  7.83it/s]
2025-09-07T11:04:22.4225440Z running benchmark:  23% 7/30 [00:00<00:02,  7.83it/s]
2025-09-07T11:04:22.5485924Z running benchmark:  27% 8/30 [00:01<00:02,  7.85it/s]
2025-09-07T11:04:22.6807559Z running benchmark:  30% 9/30 [00:01<00:02,  7.87it/s]
2025-09-07T11:04:22.8061754Z running benchmark:  33% 10/30 [00:01<00:02,  7.78it/s]
2025-09-07T11:04:22.9328014Z running benchmark:  37% 11/30 [00:01<00:02,  7.83it/s]
2025-09-07T11:04:23.0587972Z running benchmark:  40% 12/30 [00:01<00:02,  7.85it/s]
2025-09-07T11:04:23.1847107Z running benchmark:  43% 13/30 [00:01<00:02,  7.88it/s]
2025-09-07T11:04:23.3099258Z running benchmark:  47% 14/30 [00:01<00:02,  7.90it/s]
2025-09-07T11:04:23.4360646Z running benchmark:  50% 15/30 [00:01<00:01,  7.92it/s]
2025-09-07T11:04:23.5622745Z running benchmark:  53% 16/30 [00:02<00:01,  7.92it/s]
2025-09-07T11:04:23.6898168Z running benchmark:  57% 17/30 [00:02<00:01,  7.93it/s]
2025-09-07T11:04:23.8150906Z running benchmark:  60% 18/30 [00:02<00:01,  7.90it/s]
2025-09-07T11:04:23.9433088Z running benchmark:  63% 19/30 [00:02<00:01,  7.93it/s]
2025-09-07T11:04:24.0685262Z running benchmark:  67% 20/30 [00:02<00:01,  7.89it/s]
2025-09-07T11:04:24.1946370Z running benchmark:  70% 21/30 [00:02<00:01,  7.92it/s]
2025-09-07T11:04:24.3206721Z running benchmark:  73% 22/30 [00:02<00:01,  7.92it/s]
2025-09-07T11:04:24.5167881Z running benchmark:  77% 23/30 [00:02<00:00,  7.92it/s]
2025-09-07T11:04:24.6430614Z running benchmark:  80% 24/30 [00:03<00:00,  6.79it/s]
2025-09-07T11:04:24.7697398Z running benchmark:  83% 25/30 [00:03<00:00,  7.10it/s]
2025-09-07T11:04:24.8947514Z running benchmark:  87% 26/30 [00:03<00:00,  7.32it/s]
2025-09-07T11:04:25.0249327Z running benchmark:  90% 27/30 [00:03<00:00,  7.51it/s]
2025-09-07T11:04:25.1502384Z running benchmark:  93% 28/30 [00:03<00:00,  7.56it/s]
2025-09-07T11:04:25.2773748Z running benchmark:  97% 29/30 [00:03<00:00,  7.68it/s]
2025-09-07T11:04:25.2774154Z running benchmark: 100% 30/30 [00:03<00:00,  7.75it/s]
2025-09-07T11:04:25.2774593Z running benchmark: 100% 30/30 [00:03<00:00,  7.73it/s]
2025-09-07T11:04:25.3717292Z 1.472x
2025-09-07T11:04:25.3720187Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:04:27.4397865Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:04:27.4398967Z   import pynvml  # type: ignore[import]
2025-09-07T11:04:29.4600960Z 
2025-09-07T11:04:31.6707625Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:04:31.6707925Z loading model: 0it [00:02, ?it/s]
2025-09-07T11:04:31.6804241Z cpu  eval  Background_Matting                 
2025-09-07T11:04:52.5907070Z 
2025-09-07T11:04:53.1155933Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:04:53.5196739Z running benchmark:   3% 1/30 [00:00<00:15,  1.91it/s]
2025-09-07T11:04:53.9227802Z running benchmark:   7% 2/30 [00:00<00:12,  2.20it/s]
2025-09-07T11:04:54.3241631Z running benchmark:  10% 3/30 [00:01<00:11,  2.32it/s]
2025-09-07T11:04:54.7260539Z running benchmark:  13% 4/30 [00:01<00:10,  2.39it/s]
2025-09-07T11:04:55.1320838Z running benchmark:  17% 5/30 [00:02<00:10,  2.42it/s]
2025-09-07T11:04:55.5347072Z running benchmark:  20% 6/30 [00:02<00:09,  2.44it/s]
2025-09-07T11:04:55.9399650Z running benchmark:  23% 7/30 [00:02<00:09,  2.45it/s]
2025-09-07T11:04:56.3437345Z running benchmark:  27% 8/30 [00:03<00:08,  2.46it/s]
2025-09-07T11:04:56.7479335Z running benchmark:  30% 9/30 [00:03<00:08,  2.46it/s]
2025-09-07T11:04:57.2178814Z running benchmark:  33% 10/30 [00:04<00:08,  2.47it/s]
2025-09-07T11:04:57.6218589Z running benchmark:  37% 11/30 [00:04<00:08,  2.35it/s]
2025-09-07T11:04:58.0229597Z running benchmark:  40% 12/30 [00:05<00:07,  2.39it/s]
2025-09-07T11:04:58.4266837Z running benchmark:  43% 13/30 [00:05<00:07,  2.42it/s]
2025-09-07T11:04:58.8290322Z running benchmark:  47% 14/30 [00:05<00:06,  2.44it/s]
2025-09-07T11:04:59.2330249Z running benchmark:  50% 15/30 [00:06<00:06,  2.45it/s]
2025-09-07T11:04:59.6360726Z running benchmark:  53% 16/30 [00:06<00:05,  2.46it/s]
2025-09-07T11:05:00.0387913Z running benchmark:  57% 17/30 [00:07<00:05,  2.46it/s]
2025-09-07T11:05:00.4398011Z running benchmark:  60% 18/30 [00:07<00:04,  2.47it/s]
2025-09-07T11:05:00.8436741Z running benchmark:  63% 19/30 [00:07<00:04,  2.48it/s]
2025-09-07T11:05:01.3160125Z running benchmark:  67% 20/30 [00:08<00:04,  2.48it/s]
2025-09-07T11:05:01.7208346Z running benchmark:  70% 21/30 [00:08<00:03,  2.36it/s]
2025-09-07T11:05:02.1249493Z running benchmark:  73% 22/30 [00:09<00:03,  2.39it/s]
2025-09-07T11:05:02.5271721Z running benchmark:  77% 23/30 [00:09<00:02,  2.41it/s]
2025-09-07T11:05:02.9301167Z running benchmark:  80% 24/30 [00:09<00:02,  2.44it/s]
2025-09-07T11:05:03.3327840Z running benchmark:  83% 25/30 [00:10<00:02,  2.45it/s]
2025-09-07T11:05:03.7361661Z running benchmark:  87% 26/30 [00:10<00:01,  2.46it/s]
2025-09-07T11:05:04.1400319Z running benchmark:  90% 27/30 [00:11<00:01,  2.47it/s]
2025-09-07T11:05:04.5427798Z running benchmark:  93% 28/30 [00:11<00:00,  2.47it/s]
2025-09-07T11:05:04.9467520Z running benchmark:  97% 29/30 [00:11<00:00,  2.47it/s]
2025-09-07T11:05:04.9467874Z running benchmark: 100% 30/30 [00:12<00:00,  2.47it/s]
2025-09-07T11:05:04.9468155Z running benchmark: 100% 30/30 [00:12<00:00,  2.43it/s]
2025-09-07T11:05:05.0613181Z 0.885x
2025-09-07T11:05:05.0617203Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:05:07.3360238Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:05:07.3361247Z   import pynvml  # type: ignore[import]
2025-09-07T11:05:09.3455877Z 
2025-09-07T11:05:11.4110691Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:05:11.4111045Z loading model: 0it [00:02, ?it/s]
2025-09-07T11:05:11.4150481Z cpu  eval  LearningToPaint                    
2025-09-07T11:05:24.5069282Z 
2025-09-07T11:05:24.6270437Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:05:24.7676537Z running benchmark:   7% 2/30 [00:00<00:01, 16.70it/s]
2025-09-07T11:05:24.9081236Z running benchmark:  17% 5/30 [00:00<00:01, 19.61it/s]
2025-09-07T11:05:25.0559940Z running benchmark:  27% 8/30 [00:00<00:01, 20.43it/s]
2025-09-07T11:05:25.1994047Z running benchmark:  37% 11/30 [00:00<00:00, 20.37it/s]
2025-09-07T11:05:25.3458012Z running benchmark:  47% 14/30 [00:00<00:00, 20.57it/s]
2025-09-07T11:05:25.4863314Z running benchmark:  57% 17/30 [00:00<00:00, 20.56it/s]
2025-09-07T11:05:25.6992344Z running benchmark:  67% 20/30 [00:00<00:00, 20.79it/s]
2025-09-07T11:05:25.8174831Z running benchmark:  77% 23/30 [00:01<00:00, 18.04it/s]
2025-09-07T11:05:25.9325441Z running benchmark:  83% 25/30 [00:01<00:00, 17.77it/s]
2025-09-07T11:05:26.0741802Z running benchmark:  90% 27/30 [00:01<00:00, 17.67it/s]
2025-09-07T11:05:26.0744972Z running benchmark: 100% 30/30 [00:01<00:00, 18.75it/s]
2025-09-07T11:05:26.0745372Z running benchmark: 100% 30/30 [00:01<00:00, 19.14it/s]
2025-09-07T11:05:26.1608770Z 1.208x
2025-09-07T11:05:26.1611845Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:05:28.1547329Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:05:28.1548613Z   import pynvml  # type: ignore[import]
2025-09-07T11:05:30.1720684Z 
2025-09-07T11:05:31.6440492Z loading model: 0it [00:00, ?it/s]WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T11:05:32.1994148Z 
2025-09-07T11:05:32.1994561Z loading model: 0it [00:02, ?it/s]
2025-09-07T11:05:32.1994978Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T11:05:32.1995330Z cpu  eval  Super_SloMo                        
2025-09-07T11:05:32.1996016Z WARNING:common:Model Super_SloMo does not support bfloat16, running with amp instead
2025-09-07T11:06:14.2024105Z 
2025-09-07T11:06:15.1070408Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:06:15.8715575Z running benchmark:   3% 1/30 [00:00<00:26,  1.11it/s]
2025-09-07T11:06:16.6387309Z running benchmark:   7% 2/30 [00:01<00:23,  1.22it/s]
2025-09-07T11:06:17.4068179Z running benchmark:  10% 3/30 [00:02<00:21,  1.25it/s]
2025-09-07T11:06:18.1708229Z running benchmark:  13% 4/30 [00:03<00:20,  1.27it/s]
2025-09-07T11:06:19.0065799Z running benchmark:  17% 5/30 [00:03<00:19,  1.29it/s]
2025-09-07T11:06:19.7727175Z running benchmark:  20% 6/30 [00:04<00:19,  1.25it/s]
2025-09-07T11:06:20.5490949Z running benchmark:  23% 7/30 [00:05<00:18,  1.27it/s]
2025-09-07T11:06:21.3113844Z running benchmark:  27% 8/30 [00:06<00:17,  1.28it/s]
2025-09-07T11:06:22.0863769Z running benchmark:  30% 9/30 [00:07<00:16,  1.29it/s]
2025-09-07T11:06:22.9149172Z running benchmark:  33% 10/30 [00:07<00:15,  1.29it/s]
2025-09-07T11:06:23.6947935Z running benchmark:  37% 11/30 [00:08<00:15,  1.26it/s]
2025-09-07T11:06:24.4602218Z running benchmark:  40% 12/30 [00:09<00:14,  1.27it/s]
2025-09-07T11:06:25.2422921Z running benchmark:  43% 13/30 [00:10<00:13,  1.28it/s]
2025-09-07T11:06:26.0106223Z running benchmark:  47% 14/30 [00:11<00:12,  1.28it/s]
2025-09-07T11:06:26.8436636Z running benchmark:  50% 15/30 [00:11<00:11,  1.29it/s]
2025-09-07T11:06:27.6197909Z running benchmark:  53% 16/30 [00:12<00:11,  1.26it/s]
2025-09-07T11:06:28.3877335Z running benchmark:  57% 17/30 [00:13<00:10,  1.27it/s]
2025-09-07T11:06:29.1563017Z running benchmark:  60% 18/30 [00:14<00:09,  1.28it/s]
2025-09-07T11:06:29.9270713Z running benchmark:  63% 19/30 [00:14<00:08,  1.28it/s]
2025-09-07T11:06:30.6914857Z running benchmark:  67% 20/30 [00:15<00:07,  1.29it/s]
2025-09-07T11:06:31.5266882Z running benchmark:  70% 21/30 [00:16<00:06,  1.29it/s]
2025-09-07T11:06:32.2979069Z running benchmark:  73% 22/30 [00:17<00:06,  1.26it/s]
2025-09-07T11:06:33.0754999Z running benchmark:  77% 23/30 [00:18<00:05,  1.27it/s]
2025-09-07T11:06:33.8419267Z running benchmark:  80% 24/30 [00:18<00:04,  1.28it/s]
2025-09-07T11:06:34.6223232Z running benchmark:  83% 25/30 [00:19<00:03,  1.29it/s]
2025-09-07T11:06:35.4517128Z running benchmark:  87% 26/30 [00:20<00:03,  1.28it/s]
2025-09-07T11:06:36.2307456Z running benchmark:  90% 27/30 [00:21<00:02,  1.26it/s]
2025-09-07T11:06:37.0147438Z running benchmark:  93% 28/30 [00:22<00:01,  1.27it/s]
2025-09-07T11:06:37.7945552Z running benchmark:  97% 29/30 [00:22<00:00,  1.27it/s]
2025-09-07T11:06:37.7945911Z running benchmark: 100% 30/30 [00:23<00:00,  1.27it/s]
2025-09-07T11:06:37.7946223Z running benchmark: 100% 30/30 [00:23<00:00,  1.27it/s]
2025-09-07T11:06:37.9341502Z 1.105x
2025-09-07T11:06:37.9344356Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:06:40.5607629Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:06:40.5608648Z   import pynvml  # type: ignore[import]
2025-09-07T11:06:42.5784283Z 
2025-09-07T11:06:43.4281806Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:06:43.4282106Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:06:43.4344553Z cpu  eval  alexnet                            
2025-09-07T11:06:56.3536946Z 
2025-09-07T11:06:56.4972249Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:06:56.6250747Z running benchmark:   7% 2/30 [00:00<00:02, 13.98it/s]
2025-09-07T11:06:56.7530480Z running benchmark:  13% 4/30 [00:00<00:01, 14.91it/s]
2025-09-07T11:06:56.8824789Z running benchmark:  20% 6/30 [00:00<00:01, 15.23it/s]
2025-09-07T11:06:57.0101464Z running benchmark:  27% 8/30 [00:00<00:01, 15.33it/s]
2025-09-07T11:06:57.1383054Z running benchmark:  33% 10/30 [00:00<00:01, 15.44it/s]
2025-09-07T11:06:57.2672527Z running benchmark:  40% 12/30 [00:00<00:01, 15.49it/s]
2025-09-07T11:06:57.3953241Z running benchmark:  47% 14/30 [00:00<00:01, 15.50it/s]
2025-09-07T11:06:57.5220067Z running benchmark:  53% 16/30 [00:01<00:00, 15.54it/s]
2025-09-07T11:06:57.6494620Z running benchmark:  60% 18/30 [00:01<00:00, 15.61it/s]
2025-09-07T11:06:57.7793739Z running benchmark:  67% 20/30 [00:01<00:00, 15.64it/s]
2025-09-07T11:06:57.9073797Z running benchmark:  73% 22/30 [00:01<00:00, 15.56it/s]
2025-09-07T11:06:58.0353086Z running benchmark:  80% 24/30 [00:01<00:00, 15.58it/s]
2025-09-07T11:06:58.1633562Z running benchmark:  87% 26/30 [00:01<00:00, 15.60it/s]
2025-09-07T11:06:58.2931399Z running benchmark:  93% 28/30 [00:01<00:00, 15.61it/s]
2025-09-07T11:06:58.2931791Z running benchmark: 100% 30/30 [00:01<00:00, 15.55it/s]
2025-09-07T11:06:58.2932089Z running benchmark: 100% 30/30 [00:01<00:00, 15.47it/s]
2025-09-07T11:06:58.3675299Z 1.447x
2025-09-07T11:06:58.3678400Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:07:00.0266409Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:07:00.0267325Z   import pynvml  # type: ignore[import]
2025-09-07T11:07:02.0499655Z 
2025-09-07T11:07:03.5581186Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:07:03.5581470Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:07:03.5589656Z cpu  eval  basic_gnn_edgecnn                  
2025-09-07T11:07:13.5315856Z 
2025-09-07T11:07:13.6586908Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:07:13.7712158Z running benchmark:  10% 3/30 [00:00<00:01, 23.68it/s]
2025-09-07T11:07:13.8842890Z running benchmark:  20% 6/30 [00:00<00:00, 25.34it/s]
2025-09-07T11:07:13.9989532Z running benchmark:  30% 9/30 [00:00<00:00, 25.87it/s]
2025-09-07T11:07:14.1258564Z running benchmark:  40% 12/30 [00:00<00:00, 25.99it/s]
2025-09-07T11:07:14.2419314Z running benchmark:  50% 15/30 [00:00<00:00, 25.09it/s]
2025-09-07T11:07:14.3556070Z running benchmark:  60% 18/30 [00:00<00:00, 25.34it/s]
2025-09-07T11:07:14.4684890Z running benchmark:  70% 21/30 [00:00<00:00, 25.67it/s]
2025-09-07T11:07:14.5825375Z running benchmark:  80% 24/30 [00:00<00:00, 25.95it/s]
2025-09-07T11:07:14.6956412Z running benchmark:  90% 27/30 [00:01<00:00, 26.07it/s]
2025-09-07T11:07:14.6956746Z running benchmark: 100% 30/30 [00:01<00:00, 26.21it/s]
2025-09-07T11:07:14.6957062Z running benchmark: 100% 30/30 [00:01<00:00, 25.78it/s]
2025-09-07T11:07:14.7538949Z 1.730x
2025-09-07T11:07:14.7542827Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:07:16.3866314Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:07:16.3867925Z   import pynvml  # type: ignore[import]
2025-09-07T11:07:18.4026289Z 
2025-09-07T11:07:19.9033817Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:07:19.9034120Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:07:19.9037641Z cpu  eval  basic_gnn_gcn                      
2025-09-07T11:07:31.3588817Z 
2025-09-07T11:07:31.5116038Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:07:31.6513105Z running benchmark:   7% 2/30 [00:00<00:02, 13.13it/s]
2025-09-07T11:07:31.7847881Z running benchmark:  13% 4/30 [00:00<00:01, 13.80it/s]
2025-09-07T11:07:31.9915549Z running benchmark:  20% 6/30 [00:00<00:01, 14.32it/s]
2025-09-07T11:07:32.1273708Z running benchmark:  27% 8/30 [00:00<00:01, 12.03it/s]
2025-09-07T11:07:32.2647219Z running benchmark:  33% 10/30 [00:00<00:01, 12.89it/s]
2025-09-07T11:07:32.4000064Z running benchmark:  40% 12/30 [00:00<00:01, 13.41it/s]
2025-09-07T11:07:32.5346064Z running benchmark:  47% 14/30 [00:01<00:01, 13.83it/s]
2025-09-07T11:07:32.6746356Z running benchmark:  53% 16/30 [00:01<00:00, 14.14it/s]
2025-09-07T11:07:32.8082400Z running benchmark:  60% 18/30 [00:01<00:00, 14.19it/s]
2025-09-07T11:07:32.9465254Z running benchmark:  67% 20/30 [00:01<00:00, 14.42it/s]
2025-09-07T11:07:33.0825483Z running benchmark:  73% 22/30 [00:01<00:00, 14.43it/s]
2025-09-07T11:07:33.2211312Z running benchmark:  80% 24/30 [00:01<00:00, 14.51it/s]
2025-09-07T11:07:33.3584711Z running benchmark:  87% 26/30 [00:01<00:00, 14.49it/s]
2025-09-07T11:07:33.4954722Z running benchmark:  93% 28/30 [00:01<00:00, 14.51it/s]
2025-09-07T11:07:33.4955033Z running benchmark: 100% 30/30 [00:02<00:00, 14.54it/s]
2025-09-07T11:07:33.4955311Z running benchmark: 100% 30/30 [00:02<00:00, 14.04it/s]
2025-09-07T11:07:33.5438615Z 0.699x
2025-09-07T11:07:33.5441822Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:07:35.3515183Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:07:35.3516068Z   import pynvml  # type: ignore[import]
2025-09-07T11:07:37.3774174Z 
2025-09-07T11:07:38.8688898Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:07:38.8689177Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:07:38.8695042Z cpu  eval  basic_gnn_gin                      
2025-09-07T11:07:48.6230219Z 
2025-09-07T11:07:48.7660607Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:07:48.9009072Z running benchmark:  10% 3/30 [00:00<00:01, 21.04it/s]
2025-09-07T11:07:49.0336808Z running benchmark:  20% 6/30 [00:00<00:01, 21.73it/s]
2025-09-07T11:07:49.1670485Z running benchmark:  30% 9/30 [00:00<00:00, 22.11it/s]
2025-09-07T11:07:49.2999262Z running benchmark:  40% 12/30 [00:00<00:00, 22.26it/s]
2025-09-07T11:07:49.4337297Z running benchmark:  50% 15/30 [00:00<00:00, 22.37it/s]
2025-09-07T11:07:49.5664638Z running benchmark:  60% 18/30 [00:00<00:00, 22.39it/s]
2025-09-07T11:07:49.7018891Z running benchmark:  70% 21/30 [00:00<00:00, 22.46it/s]
2025-09-07T11:07:49.8357607Z running benchmark:  80% 24/30 [00:01<00:00, 22.36it/s]
2025-09-07T11:07:49.9690362Z running benchmark:  90% 27/30 [00:01<00:00, 22.38it/s]
2025-09-07T11:07:49.9690665Z running benchmark: 100% 30/30 [00:01<00:00, 22.42it/s]
2025-09-07T11:07:49.9690929Z running benchmark: 100% 30/30 [00:01<00:00, 22.29it/s]
2025-09-07T11:07:50.0162618Z 1.079x
2025-09-07T11:07:50.0166208Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:07:51.6549126Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:07:51.6550036Z   import pynvml  # type: ignore[import]
2025-09-07T11:07:53.6723503Z 
2025-09-07T11:07:55.1611437Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:07:55.1612216Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:07:55.1616545Z cpu  eval  basic_gnn_sage                     
2025-09-07T11:08:04.9764065Z 
2025-09-07T11:08:05.0790471Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:08:05.2144399Z running benchmark:   7% 2/30 [00:00<00:01, 19.57it/s]
2025-09-07T11:08:05.3506957Z running benchmark:  17% 5/30 [00:00<00:01, 21.26it/s]
2025-09-07T11:08:05.4832044Z running benchmark:  27% 8/30 [00:00<00:01, 21.62it/s]
2025-09-07T11:08:05.6165513Z running benchmark:  37% 11/30 [00:00<00:00, 22.03it/s]
2025-09-07T11:08:05.7512207Z running benchmark:  47% 14/30 [00:00<00:00, 22.21it/s]
2025-09-07T11:08:05.8866148Z running benchmark:  57% 17/30 [00:00<00:00, 22.23it/s]
2025-09-07T11:08:06.0205733Z running benchmark:  67% 20/30 [00:00<00:00, 22.21it/s]
2025-09-07T11:08:06.1547314Z running benchmark:  77% 23/30 [00:01<00:00, 22.27it/s]
2025-09-07T11:08:06.2887456Z running benchmark:  87% 26/30 [00:01<00:00, 22.30it/s]
2025-09-07T11:08:06.3333527Z running benchmark:  97% 29/30 [00:01<00:00, 22.32it/s]
2025-09-07T11:08:06.3333836Z running benchmark: 100% 30/30 [00:01<00:00, 22.11it/s]
2025-09-07T11:08:06.3856181Z 1.109x
2025-09-07T11:08:06.3859746Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:08:08.0192347Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:08:08.0193208Z   import pynvml  # type: ignore[import]
2025-09-07T11:08:10.0421935Z 
2025-09-07T11:08:10.2908023Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:08:10.2908376Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:08:10.2919471Z cpu  eval  dcgan                              
2025-09-07T11:08:21.0947037Z 
2025-09-07T11:08:21.2044820Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:08:21.3164818Z running benchmark:  17% 5/30 [00:00<00:00, 45.72it/s]
2025-09-07T11:08:21.4288983Z running benchmark:  37% 11/30 [00:00<00:00, 50.39it/s]
2025-09-07T11:08:21.5415283Z running benchmark:  57% 17/30 [00:00<00:00, 51.76it/s]
2025-09-07T11:08:21.6537114Z running benchmark:  77% 23/30 [00:00<00:00, 52.36it/s]
2025-09-07T11:08:21.6723677Z running benchmark:  97% 29/30 [00:00<00:00, 52.76it/s]
2025-09-07T11:08:21.6724004Z running benchmark: 100% 30/30 [00:00<00:00, 51.95it/s]
2025-09-07T11:08:21.7234047Z 1.096x
2025-09-07T11:08:21.7236939Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:08:23.2711241Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:08:23.2712172Z   import pynvml  # type: ignore[import]
2025-09-07T11:08:25.2869469Z 
2025-09-07T11:08:26.9657147Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:08:26.9657417Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:08:26.9844100Z cpu  eval  demucs                             
2025-09-07T11:08:43.2108270Z 
2025-09-07T11:08:43.3507665Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:08:43.4727021Z running benchmark:   3% 1/30 [00:00<00:04,  7.17it/s]
2025-09-07T11:08:43.5953548Z running benchmark:   7% 2/30 [00:00<00:03,  7.74it/s]
2025-09-07T11:08:43.7146281Z running benchmark:  10% 3/30 [00:00<00:03,  7.95it/s]
2025-09-07T11:08:43.8343810Z running benchmark:  13% 4/30 [00:00<00:03,  8.09it/s]
2025-09-07T11:08:43.9550602Z running benchmark:  17% 5/30 [00:00<00:03,  8.18it/s]
2025-09-07T11:08:44.0773246Z running benchmark:  20% 6/30 [00:00<00:02,  8.22it/s]
2025-09-07T11:08:44.1989180Z running benchmark:  23% 7/30 [00:00<00:02,  8.21it/s]
2025-09-07T11:08:44.3185750Z running benchmark:  27% 8/30 [00:00<00:02,  8.21it/s]
2025-09-07T11:08:44.4400229Z running benchmark:  30% 9/30 [00:01<00:02,  8.26it/s]
2025-09-07T11:08:44.5624900Z running benchmark:  33% 10/30 [00:01<00:02,  8.25it/s]
2025-09-07T11:08:44.6828237Z running benchmark:  37% 11/30 [00:01<00:02,  8.22it/s]
2025-09-07T11:08:44.8055372Z running benchmark:  40% 12/30 [00:01<00:02,  8.25it/s]
2025-09-07T11:08:44.9271779Z running benchmark:  43% 13/30 [00:01<00:02,  8.22it/s]
2025-09-07T11:08:45.0526388Z running benchmark:  47% 14/30 [00:01<00:01,  8.22it/s]
2025-09-07T11:08:45.2416844Z running benchmark:  50% 15/30 [00:01<00:01,  8.14it/s]
2025-09-07T11:08:45.3642685Z running benchmark:  53% 16/30 [00:02<00:01,  7.01it/s]
2025-09-07T11:08:45.4854518Z running benchmark:  57% 17/30 [00:02<00:01,  7.32it/s]
2025-09-07T11:08:45.6067034Z running benchmark:  60% 18/30 [00:02<00:01,  7.57it/s]
2025-09-07T11:08:45.7289907Z running benchmark:  63% 19/30 [00:02<00:01,  7.77it/s]
2025-09-07T11:08:45.8497579Z running benchmark:  67% 20/30 [00:02<00:01,  7.88it/s]
2025-09-07T11:08:45.9726783Z running benchmark:  70% 21/30 [00:02<00:01,  8.00it/s]
2025-09-07T11:08:46.0922324Z running benchmark:  73% 22/30 [00:02<00:00,  8.04it/s]
2025-09-07T11:08:46.2136591Z running benchmark:  77% 23/30 [00:02<00:00,  8.14it/s]
2025-09-07T11:08:46.3361325Z running benchmark:  80% 24/30 [00:03<00:00,  8.16it/s]
2025-09-07T11:08:46.4595509Z running benchmark:  83% 25/30 [00:03<00:00,  8.16it/s]
2025-09-07T11:08:46.5813421Z running benchmark:  87% 26/30 [00:03<00:00,  8.15it/s]
2025-09-07T11:08:46.7026625Z running benchmark:  90% 27/30 [00:03<00:00,  8.17it/s]
2025-09-07T11:08:46.8245194Z running benchmark:  93% 28/30 [00:03<00:00,  8.19it/s]
2025-09-07T11:08:46.9467281Z running benchmark:  97% 29/30 [00:03<00:00,  8.19it/s]
2025-09-07T11:08:46.9467604Z running benchmark: 100% 30/30 [00:03<00:00,  8.19it/s]
2025-09-07T11:08:46.9467925Z running benchmark: 100% 30/30 [00:03<00:00,  8.03it/s]
2025-09-07T11:08:47.0703078Z 1.091x
2025-09-07T11:08:47.0705829Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:08:48.9014326Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:08:48.9015217Z   import pynvml  # type: ignore[import]
2025-09-07T11:08:50.9399423Z 
2025-09-07T11:08:51.9557669Z loading model: 0it [00:00, ?it/s]
2025-09-07T11:08:51.9557970Z loading model: 0it [00:01, ?it/s]
2025-09-07T11:08:51.9711797Z cpu  eval  densenet121                        
2025-09-07T11:09:24.6077822Z 
2025-09-07T11:09:25.0686367Z running benchmark:   0% 0/30 [00:00<?, ?it/s]
2025-09-07T11:09:25.3821972Z running benchmark:   3% 1/30 [00:00<00:13,  2.17it/s]
2025-09-07T11:09:25.7001236Z running benchmark:   7% 2/30 [00:00<00:10,  2.67it/s]
2025-09-07T11:09:26.1250114Z running benchmark:  10% 3/30 [00:01<00:09,  2.87it/s]
2025-09-07T11:09:26.4501665Z running benchmark:  13% 4/30 [00:01<00:09,  2.64it/s]
2025-09-07T11:09:26.7655743Z running benchmark:  17% 5/30 [00:01<00:08,  2.78it/s]
2025-09-07T11:09:27.0805966Z running benchmark:  20% 6/30 [00:02<00:08,  2.90it/s]
2025-09-07T11:09:27.3967252Z running benchmark:  23% 7/30 [00:02<00:07,  2.99it/s]
2025-09-07T11:09:27.7112633Z running benchmark:  27% 8/30 [00:02<00:07,  3.04it/s]
2025-09-07T11:09:28.0267035Z running benchmark:  30% 9/30 [00:03<00:06,  3.08it/s]
2025-09-07T11:09:28.3429791Z running benchmark:  33% 10/30 [00:03<00:06,  3.11it/s]
2025-09-07T11:09:28.6588248Z running benchmark:  37% 11/30 [00:03<00:06,  3.13it/s]
2025-09-07T11:09:28.9726854Z running benchmark:  40% 12/30 [00:04<00:05,  3.14it/s]
2025-09-07T11:09:29.2908047Z running benchmark:  43% 13/30 [00:04<00:05,  3.15it/s]
2025-09-07T11:09:29.6057550Z running benchmark:  47% 14/30 [00:04<00:05,  3.15it/s]
2025-09-07T11:09:29.9920227Z running benchmark:  50% 15/30 [00:04<00:04,  3.16it/s]
2025-09-07T11:09:30.3080302Z running benchmark:  53% 16/30 [00:05<00:04,  2.96it/s]
2025-09-07T11:09:30.6220048Z running benchmark:  57% 17/30 [00:05<00:04,  3.02it/s]
2025-09-07T11:09:30.9388604Z running benchmark:  60% 18/30 [00:06<00:03,  3.07it/s]
2025-09-07T11:09:31.2534133Z running benchmark:  63% 19/30 [00:06<00:03,  3.09it/s]
2025-09-07T11:09:31.5704652Z running benchmark:  67% 20/30 [00:06<00:03,  3.12it/s]
2025-09-07T11:09:31.8851755Z running benchmark:  70% 21/30 [00:06<00:02,  3.13it/s]
2025-09-07T11:09:32.2024434Z running benchmark:  73% 22/30 [00:07<00:02,  3.14it/s]
2025-09-07T11:09:32.5167991Z running benchmark:  77% 23/30 [00:07<00:02,  3.15it/s]
2025-09-07T11:09:32.8322532Z running benchmark:  80% 24/30 [00:07<00:01,  3.16it/s]
2025-09-07T11:09:33.1464704Z running benchmark:  83% 25/30 [00:08<00:01,  3.16it/s]
2025-09-07T11:09:33.4627433Z running benchmark:  87% 26/30 [00:08<00:01,  3.17it/s]
2025-09-07T11:09:33.7785477Z running benchmark:  90% 27/30 [00:08<00:00,  3.17it/s]
2025-09-07T11:09:34.1658782Z running benchmark:  93% 28/30 [00:09<00:00,  3.17it/s]
2025-09-07T11:09:34.4803529Z running benchmark:  97% 29/30 [00:09<00:00,  2.96it/s]
2025-09-07T11:09:34.4807316Z running benchmark: 100% 30/30 [00:09<00:00,  3.03it/s]
2025-09-07T11:09:34.4807634Z running benchmark: 100% 30/30 [00:09<00:00,  3.04it/s]
2025-09-07T11:09:34.6353575Z 2.184x
2025-09-07T11:09:34.6356531Z WARNING:common:Trying to call the empty_gpu_cache for device: cpu, which is not in list [cuda, xpu]
2025-09-07T11:09:37.6658176Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:09:37.6659052Z   import pynvml  # type: ignore[import]
2025-09-07T11:09:39.6816680Z 
2025-09-07T11:09:39.9002702Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:09:39.9003124Z   what():  std::bad_array_new_length
2025-09-07T11:11:22.9533729Z Run failed with return code:  -6
2025-09-07T11:11:22.9533992Z Output:  None
2025-09-07T11:11:22.9534145Z Error:  None
2025-09-07T11:11:23.3654022Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:11:23.3655007Z   import pynvml  # type: ignore[import]
2025-09-07T11:11:25.3909283Z 
2025-09-07T11:11:25.6098902Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:11:25.6099318Z   what():  std::bad_array_new_length
2025-09-07T11:13:08.7512254Z Run failed with return code:  -6
2025-09-07T11:13:08.7512527Z Output:  None
2025-09-07T11:13:08.7512679Z Error:  None
2025-09-07T11:13:09.1646282Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:13:09.1647186Z   import pynvml  # type: ignore[import]
2025-09-07T11:13:11.2142706Z 
2025-09-07T11:13:11.4356618Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:13:11.4357380Z   what():  std::bad_array_new_length
2025-09-07T11:14:54.0476836Z Run failed with return code:  -6
2025-09-07T11:14:54.0477114Z Output:  None
2025-09-07T11:14:54.0477271Z Error:  None
2025-09-07T11:14:54.4583217Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:14:54.4584482Z   import pynvml  # type: ignore[import]
2025-09-07T11:14:56.4776908Z 
2025-09-07T11:14:56.6963043Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:14:56.6963422Z   what():  std::bad_array_new_length
2025-09-07T11:16:39.3970801Z Run failed with return code:  -6
2025-09-07T11:16:39.3971063Z Output:  None
2025-09-07T11:16:39.3971247Z Error:  None
2025-09-07T11:16:39.8072606Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:16:39.8073926Z   import pynvml  # type: ignore[import]
2025-09-07T11:16:41.8248892Z 
2025-09-07T11:16:42.0431034Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:16:42.0431423Z   what():  std::bad_array_new_length
2025-09-07T11:18:24.7449672Z Run failed with return code:  -6
2025-09-07T11:18:24.7449941Z Output:  None
2025-09-07T11:18:24.7450092Z Error:  None
2025-09-07T11:18:25.1588619Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:18:25.1589514Z   import pynvml  # type: ignore[import]
2025-09-07T11:18:27.1815278Z 
2025-09-07T11:18:27.4013430Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:18:27.4013855Z   what():  std::bad_array_new_length
2025-09-07T11:20:09.4931712Z Run failed with return code:  -6
2025-09-07T11:20:09.4931977Z Output:  None
2025-09-07T11:20:09.4932133Z Error:  None
2025-09-07T11:20:09.9022604Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:20:09.9023593Z   import pynvml  # type: ignore[import]
2025-09-07T11:20:11.9288854Z 
2025-09-07T11:20:12.1482166Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:20:12.1482570Z   what():  std::bad_array_new_length
2025-09-07T11:21:54.1921444Z Run failed with return code:  -6
2025-09-07T11:21:54.1921717Z Output:  None
2025-09-07T11:21:54.1921873Z Error:  None
2025-09-07T11:21:54.6050151Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:21:54.6051053Z   import pynvml  # type: ignore[import]
2025-09-07T11:21:56.6263816Z 
2025-09-07T11:21:56.8451715Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:21:56.8452123Z   what():  std::bad_array_new_length
2025-09-07T11:23:39.4942370Z Run failed with return code:  -6
2025-09-07T11:23:39.4942643Z Output:  None
2025-09-07T11:23:39.4942834Z Error:  None
2025-09-07T11:23:39.9058772Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:23:39.9059682Z   import pynvml  # type: ignore[import]
2025-09-07T11:23:41.9219323Z 
2025-09-07T11:23:42.1408861Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:25:24.5429559Z   what():  std::bad_array_new_length
2025-09-07T11:25:24.5430319Z Run failed with return code:  -6
2025-09-07T11:25:24.5430519Z Output:  None
2025-09-07T11:25:24.5430661Z Error:  None
2025-09-07T11:25:24.9576320Z /opt/conda/envs/py_3.9/lib/python3.9/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml directly, please report this to the maintainers of the package that installed pynvml for you.
2025-09-07T11:25:24.9577281Z   import pynvml  # type: ignore[import]
2025-09-07T11:25:26.9810826Z 
2025-09-07T11:25:27.2003756Z loading model: 0it [00:00, ?it/s]terminate called after throwing an instance of 'std::bad_array_new_length'
2025-09-07T11:25:27.2004156Z   what():  std::bad_array_new_length
2025-09-07T11:27:09.6923944Z Run failed with return code:  -6
2025-09-07T11:27:09.6925968Z Output:  None
2025-09-07T11:27:09.6926163Z Error:  None
2025-09-07T11:27:09.6970103Z speedup             gmean=1.21x mean=1.259x
2025-09-07T11:27:09.6972500Z abs_latency         gmean=41.45x mean=78.150x
2025-09-07T11:27:09.6973113Z compilation_latency mean=16.676 seconds
2025-09-07T11:27:09.6973616Z compression_ratio   mean=0.873x
2025-09-07T11:27:09.6975905Z eager_peak_mem      gmean=149.25x mean=195.454x
2025-09-07T11:27:09.6978156Z dynamo_peak_mem     gmean=172.69x mean=229.891x
2025-09-07T11:27:09.6980717Z calls_captured      gmean=0.00x mean=0.000x
2025-09-07T11:27:09.6982507Z unique_graphs       gmean=0.00x mean=0.000x
2025-09-07T11:27:09.6984548Z graph_breaks        gmean=0.00x mean=0.000x
2025-09-07T11:27:09.6986679Z unique_graph_breaks gmean=0.00x mean=0.000x
2025-09-07T11:27:09.6988756Z autograd_captures   gmean=0.00x mean=0.000x
2025-09-07T11:27:09.6990877Z autograd_compiles   gmean=0.00x mean=0.000x
2025-09-07T11:27:09.6992971Z cudagraph_skips     gmean=0.00x mean=0.000x
2025-09-07T11:27:10.4404267Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *maxautotune-true* ]]
2025-09-07T11:27:10.4405069Z + [[ training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true == *cudagraphs_low_precision-true* ]]
2025-09-07T11:27:10.4405570Z + sccache_epilogue
2025-09-07T11:27:10.4405787Z + echo '::group::Sccache Compilation Log'
2025-09-07T11:27:10.4406307Z ##[group]Sccache Compilation Log
2025-09-07T11:27:10.4406557Z + echo '=================== sccache compilation log ==================='
2025-09-07T11:27:10.4406810Z =================== sccache compilation log ===================
2025-09-07T11:27:10.4407206Z + python /var/lib/jenkins/workspace/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log
2025-09-07T11:27:10.4665252Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ==========='
2025-09-07T11:27:10.4665717Z =========== If your build fails, please take a look at the log above for possible reasons ===========
2025-09-07T11:27:10.4666027Z + sccache --show-stats
2025-09-07T11:27:10.4721219Z Compile requests                   1340
2025-09-07T11:27:10.4721455Z Compile requests executed           109
2025-09-07T11:27:10.4721649Z Cache hits                           42
2025-09-07T11:27:10.4721833Z Cache hits (C/C++)                   42
2025-09-07T11:27:10.4722021Z Cache misses                         67
2025-09-07T11:27:10.4722200Z Cache misses (C/C++)                 67
2025-09-07T11:27:10.4722400Z Cache hits rate                   38.53 %
2025-09-07T11:27:10.4722603Z Cache hits rate (C/C++)           38.53 %
2025-09-07T11:27:10.4723142Z Cache timeouts                        0
2025-09-07T11:27:10.4723334Z Cache read errors                     0
2025-09-07T11:27:10.4723523Z Forced recaches                       0
2025-09-07T11:27:10.4723714Z Cache write errors                    0
2025-09-07T11:27:10.4723898Z Cache errors                          0
2025-09-07T11:27:10.4724081Z Compilations                         67
2025-09-07T11:27:10.4724276Z Compilation failures                  0
2025-09-07T11:27:10.4724474Z Non-cacheable compilations            0
2025-09-07T11:27:10.4724778Z Non-cacheable calls                 139
2025-09-07T11:27:10.4724967Z Non-compilation calls              1092
2025-09-07T11:27:10.4725158Z Unsupported compiler calls            0
2025-09-07T11:27:10.4725360Z Average cache write               0.042 s
2025-09-07T11:27:10.4725563Z Average compiler                  7.014 s
2025-09-07T11:27:10.4725756Z Average cache read hit            0.049 s
2025-09-07T11:27:10.4725957Z Failed distributed compilations       0
2025-09-07T11:27:10.4726105Z 
2025-09-07T11:27:10.4726172Z Non-cacheable reasons:
2025-09-07T11:27:10.4726341Z -E                                  116
2025-09-07T11:27:10.4726544Z unknown source language              23
2025-09-07T11:27:10.4726762Z 
2025-09-07T11:27:10.4726914Z Cache location                  s3, name: ossci-compiler-cache-circleci-v2, prefix: /
2025-09-07T11:27:10.4727202Z Version (client)                0.10.0
2025-09-07T11:27:10.4727401Z + sccache --stop-server
2025-09-07T11:27:10.4760867Z Stopping sccache server...
2025-09-07T11:27:10.4764453Z Compile requests                   1340
2025-09-07T11:27:10.4764678Z Compile requests executed           109
2025-09-07T11:27:10.4764873Z Cache hits                           42
2025-09-07T11:27:10.4765057Z Cache hits (C/C++)                   42
2025-09-07T11:27:10.4765254Z Cache misses                         67
2025-09-07T11:27:10.4765553Z Cache misses (C/C++)                 67
2025-09-07T11:27:10.4765746Z Cache hits rate                   38.53 %
2025-09-07T11:27:10.4765947Z Cache hits rate (C/C++)           38.53 %
2025-09-07T11:27:10.4766131Z Cache timeouts                        0
2025-09-07T11:27:10.4766320Z Cache read errors                     0
2025-09-07T11:27:10.4766513Z Forced recaches                       0
2025-09-07T11:27:10.4766695Z Cache write errors                    0
2025-09-07T11:27:10.4766878Z Cache errors                          0
2025-09-07T11:27:10.4767064Z Compilations                         67
2025-09-07T11:27:10.4767253Z Compilation failures                  0
2025-09-07T11:27:10.4767452Z Non-cacheable compilations            0
2025-09-07T11:27:10.4767647Z Non-cacheable calls                 139
2025-09-07T11:27:10.4767848Z Non-compilation calls              1092
2025-09-07T11:27:10.4768043Z Unsupported compiler calls            0
2025-09-07T11:27:10.4768243Z Average cache write               0.042 s
2025-09-07T11:27:10.4768446Z Average compiler                  7.014 s
2025-09-07T11:27:10.4768639Z Average cache read hit            0.049 s
2025-09-07T11:27:10.4768839Z Failed distributed compilations       0
2025-09-07T11:27:10.4768974Z 
2025-09-07T11:27:10.4769042Z Non-cacheable reasons:
2025-09-07T11:27:10.4769211Z -E                                  116
2025-09-07T11:27:10.4769398Z unknown source language              23
2025-09-07T11:27:10.4769529Z 
2025-09-07T11:27:10.4769676Z Cache location                  s3, name: ossci-compiler-cache-circleci-v2, prefix: /
2025-09-07T11:27:10.4769958Z Version (client)                0.10.0
2025-09-07T11:27:10.4770489Z + echo ::endgroup::
2025-09-07T11:27:10.4770790Z ##[endgroup]
2025-09-07T11:27:10.4770944Z + cleanup_workspace
2025-09-07T11:27:10.4771244Z + echo 'sudo may print the following warning message that can be ignored. The chown command will still run.'
2025-09-07T11:27:10.4771719Z sudo may print the following warning message that can be ignored. The chown command will still run.
2025-09-07T11:27:10.4772110Z + echo '    sudo: setrlimit(RLIMIT_STACK): Operation not permitted'
2025-09-07T11:27:10.4772442Z     sudo: setrlimit(RLIMIT_STACK): Operation not permitted
2025-09-07T11:27:10.4772786Z + echo 'For more details refer to https://github.com/sudo-project/sudo/issues/42'
2025-09-07T11:27:10.4773151Z For more details refer to https://github.com/sudo-project/sudo/issues/42
2025-09-07T11:27:10.4773452Z + sudo chown -R 1000 /var/lib/jenkins/workspace
2025-09-07T11:27:11.3102483Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main
2025-09-07T11:27:11.3102897Z with:
2025-09-07T11:27:11.3103435Z   benchmark-results-dir: test/test-reports
2025-09-07T11:27:11.3103653Z   dry-run: false
2025-09-07T11:27:11.3103819Z   schema-version: v3
2025-09-07T11:27:11.3104181Z   github-token: ***
2025-09-07T11:27:11.3104344Z env:
2025-09-07T11:27:11.3104496Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:11.3104798Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:11.3105109Z ##[endgroup]
2025-09-07T11:27:11.3128912Z ##[group]Run set -eux
2025-09-07T11:27:11.3129102Z set -eux
2025-09-07T11:27:11.3129256Z 
2025-09-07T11:27:11.3129420Z if [[ -n "" ]]; then
2025-09-07T11:27:11.3129599Z   source ""
2025-09-07T11:27:11.3129864Z fi
2025-09-07T11:27:11.3130099Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0
2025-09-07T11:27:11.3130397Z 
2025-09-07T11:27:11.3130552Z DEVICE_NAME=""
2025-09-07T11:27:11.3130722Z DEVICE_TYPE=""
2025-09-07T11:27:11.3130892Z 
2025-09-07T11:27:11.3131044Z if command -v nvidia-smi; then
2025-09-07T11:27:11.3131329Z   # NB: I'm using PyTorch here to get the device name, however, it needs to
2025-09-07T11:27:11.3131681Z   # install the correct version of PyTorch manually for now. Any PyTorch
2025-09-07T11:27:11.3132012Z   # version is fine, I just use 2.7.1 to satify PYPIDEP linter
2025-09-07T11:27:11.3132288Z   python3 -mpip install torch==2.7.1
2025-09-07T11:27:11.3132501Z elif command -v rocminfo; then
2025-09-07T11:27:11.3132771Z   # NB: Installing torch on ROCm runner with pip here causes CI to fail
2025-09-07T11:27:11.3133115Z   # with a memoryview is too large error only on MI300 runners. Is pip
2025-09-07T11:27:11.3133457Z   # version on ROCm runner there too old? As a workaround, let's use the
2025-09-07T11:27:11.3133758Z   # GPU device name coming from rocminfo instead
2025-09-07T11:27:11.3133979Z   DEVICE_NAME=rocm
2025-09-07T11:27:11.3134279Z   DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs)
2025-09-07T11:27:11.3134584Z fi
2025-09-07T11:27:11.3134726Z 
2025-09-07T11:27:11.3134896Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV
2025-09-07T11:27:11.3135151Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV
2025-09-07T11:27:11.3146227Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:11.3146464Z env:
2025-09-07T11:27:11.3146623Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:11.3146911Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:11.3147223Z ##[endgroup]
2025-09-07T11:27:11.3182470Z + [[ -n '' ]]
2025-09-07T11:27:11.3182720Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0
2025-09-07T11:27:11.4954660Z Defaulting to user installation because normal site-packages is not writeable
2025-09-07T11:27:12.2791052Z Collecting boto3==1.35.33
2025-09-07T11:27:12.2919062Z   Downloading boto3-1.35.33-py3-none-any.whl (139 kB)
2025-09-07T11:27:12.5088212Z Collecting psutil==7.0.0
2025-09-07T11:27:12.5120358Z   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)
2025-09-07T11:27:12.5407695Z Collecting pynvml==12.0.0
2025-09-07T11:27:12.5433774Z   Downloading pynvml-12.0.0-py3-none-any.whl (26 kB)
2025-09-07T11:27:12.5840752Z Collecting s3transfer<0.11.0,>=0.10.0
2025-09-07T11:27:12.5867036Z   Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB)
2025-09-07T11:27:12.5916362Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.33) (0.10.0)
2025-09-07T11:27:13.3967576Z Collecting botocore<1.36.0,>=1.35.33
2025-09-07T11:27:13.3998005Z   Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB)
2025-09-07T11:27:13.5406124Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0
2025-09-07T11:27:13.5437492Z   Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB)
2025-09-07T11:27:13.5504746Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.25.10)
2025-09-07T11:27:13.5508797Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.8.1)
2025-09-07T11:27:13.6857771Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.15.0)
2025-09-07T11:27:13.7795523Z Installing collected packages: botocore, s3transfer, nvidia-ml-py, pynvml, psutil, boto3
2025-09-07T11:27:14.1853877Z   Attempting uninstall: nvidia-ml-py
2025-09-07T11:27:14.1854456Z     Found existing installation: nvidia-ml-py 11.525.84
2025-09-07T11:27:14.1865461Z     Uninstalling nvidia-ml-py-11.525.84:
2025-09-07T11:27:14.2049093Z       Successfully uninstalled nvidia-ml-py-11.525.84
2025-09-07T11:27:14.2484531Z   Attempting uninstall: psutil
2025-09-07T11:27:14.2485320Z     Found existing installation: psutil 5.9.8
2025-09-07T11:27:14.2546452Z     Uninstalling psutil-5.9.8:
2025-09-07T11:27:14.2551793Z       Successfully uninstalled psutil-5.9.8
2025-09-07T11:27:14.3820815Z Successfully installed boto3-1.35.33 botocore-1.35.99 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 s3transfer-0.10.4
2025-09-07T11:27:14.4730473Z + DEVICE_NAME=
2025-09-07T11:27:14.4730674Z + DEVICE_TYPE=
2025-09-07T11:27:14.4730847Z + command -v nvidia-smi
2025-09-07T11:27:14.4731025Z + command -v rocminfo
2025-09-07T11:27:14.4731195Z + echo DEVICE_NAME=
2025-09-07T11:27:14.4731486Z + echo DEVICE_TYPE=
2025-09-07T11:27:14.4754672Z ##[group]Run set -eux
2025-09-07T11:27:14.4754867Z set -eux
2025-09-07T11:27:14.4755038Z 
2025-09-07T11:27:14.4755211Z if [[ -z "${GITHUB_TOKEN}" ]]; then
2025-09-07T11:27:14.4755441Z   echo "Missing github-token input"
2025-09-07T11:27:14.4755658Z   exit 1
2025-09-07T11:27:14.4755805Z fi
2025-09-07T11:27:14.4764474Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:14.4764716Z env:
2025-09-07T11:27:14.4764869Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:14.4765165Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:14.4765468Z   DEVICE_NAME: 
2025-09-07T11:27:14.4765626Z   DEVICE_TYPE: 
2025-09-07T11:27:14.4766001Z   GITHUB_TOKEN: ***
2025-09-07T11:27:14.4766172Z ##[endgroup]
2025-09-07T11:27:14.4795447Z + [[ -z *** ]]
2025-09-07T11:27:14.4828780Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main
2025-09-07T11:27:14.4829080Z with:
2025-09-07T11:27:14.4829341Z   github-token: ***
2025-09-07T11:27:14.4829503Z env:
2025-09-07T11:27:14.4829666Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:14.4829957Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:14.4830282Z   DEVICE_NAME: 
2025-09-07T11:27:14.4830433Z   DEVICE_TYPE: 
2025-09-07T11:27:14.4830581Z ##[endgroup]
2025-09-07T11:27:14.4841307Z ##[group]Run set -eux
2025-09-07T11:27:14.4841495Z set -eux
2025-09-07T11:27:14.4841647Z 
2025-09-07T11:27:14.4841943Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}"
2025-09-07T11:27:14.4848973Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:14.4849213Z env:
2025-09-07T11:27:14.4849369Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:14.4849665Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:14.4849972Z   DEVICE_NAME: 
2025-09-07T11:27:14.4850121Z   DEVICE_TYPE: 
2025-09-07T11:27:14.4850377Z   GITHUB_TOKEN: ***
2025-09-07T11:27:14.4851457Z ##[endgroup]
2025-09-07T11:27:14.4878807Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17525294857 i-04e43c8796a0bfd2e
2025-09-07T11:27:14.9648438Z setting job-id=49775530523
2025-09-07T11:27:14.9648893Z setting job-name=inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T11:27:14.9744616Z ##[group]Run set -eux
2025-09-07T11:27:14.9744816Z set -eux
2025-09-07T11:27:14.9744972Z 
2025-09-07T11:27:14.9745118Z if [[ -n "" ]]; then
2025-09-07T11:27:14.9745294Z   source ""
2025-09-07T11:27:14.9745444Z fi
2025-09-07T11:27:14.9745661Z 
2025-09-07T11:27:14.9745911Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \
2025-09-07T11:27:14.9746357Z   --schema-version "${SCHEMA_VERSION}" \
2025-09-07T11:27:14.9746578Z   --repo "${REPO}" \
2025-09-07T11:27:14.9746791Z   --head-branch "${HEAD_BRANCH}" \
2025-09-07T11:27:14.9747006Z   --head-sha "${HEAD_SHA}" \
2025-09-07T11:27:14.9747229Z   --workflow-id "${WORKFLOW_RUN_ID}" \
2025-09-07T11:27:14.9747445Z   --run-attempt "${RUN_ATTEMPT}" \
2025-09-07T11:27:14.9747648Z   --job-id "${JOB_ID}" \
2025-09-07T11:27:14.9747840Z   --job-name "${JOB_NAME}"
2025-09-07T11:27:14.9755042Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:14.9755282Z env:
2025-09-07T11:27:14.9755426Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:14.9755716Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:14.9756013Z   DEVICE_NAME: 
2025-09-07T11:27:14.9756164Z   DEVICE_TYPE: 
2025-09-07T11:27:14.9756307Z   SCHEMA_VERSION: v3
2025-09-07T11:27:14.9756478Z   REPO: pytorch/pytorch
2025-09-07T11:27:14.9756650Z   HEAD_BRANCH: refs/heads/main
2025-09-07T11:27:14.9756858Z   HEAD_SHA: 93fb23d6fae7c4e82c4239a1033e522088742634
2025-09-07T11:27:14.9757071Z   WORKFLOW_RUN_ID: 17525294857
2025-09-07T11:27:14.9757237Z   RUN_ATTEMPT: 1
2025-09-07T11:27:14.9757391Z   JOB_ID: 49775530523
2025-09-07T11:27:14.9757709Z   JOB_NAME: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T11:27:14.9758041Z ##[endgroup]
2025-09-07T11:27:14.9789342Z + [[ -n '' ]]
2025-09-07T11:27:14.9790606Z + python3 /home/ec2-user/actions-runner/_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 17525294857 --run-attempt 1 --job-id 49775530523 --job-name 'inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)'
2025-09-07T11:27:15.0059416Z ##[group]Run set -eux
2025-09-07T11:27:15.0059598Z set -eux
2025-09-07T11:27:15.0059755Z 
2025-09-07T11:27:15.0059906Z if [[ -n "" ]]; then
2025-09-07T11:27:15.0060089Z   source ""
2025-09-07T11:27:15.0060256Z fi
2025-09-07T11:27:15.0060389Z 
2025-09-07T11:27:15.0060637Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py"
2025-09-07T11:27:15.0067197Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:15.0067437Z env:
2025-09-07T11:27:15.0067585Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:15.0067875Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:15.0068182Z   DEVICE_NAME: 
2025-09-07T11:27:15.0068331Z   DEVICE_TYPE: 
2025-09-07T11:27:15.0068473Z ##[endgroup]
2025-09-07T11:27:15.0094022Z + [[ -n '' ]]
2025-09-07T11:27:15.0095119Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py
2025-09-07T11:27:15.0420321Z INFO:root:Fail to import torch to get the device name
2025-09-07T11:27:15.0534974Z ##[group]Run set -eux
2025-09-07T11:27:15.0535271Z set -eux
2025-09-07T11:27:15.0535426Z 
2025-09-07T11:27:15.0535594Z # TODO (huydhn): Implement this part
2025-09-07T11:27:15.0535840Z echo "dependencies={}" >> "${GITHUB_OUTPUT}"
2025-09-07T11:27:15.0542955Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:15.0543194Z env:
2025-09-07T11:27:15.0543350Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:15.0543645Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:15.0543948Z   DEVICE_NAME: 
2025-09-07T11:27:15.0544105Z   DEVICE_TYPE: 
2025-09-07T11:27:15.0544252Z ##[endgroup]
2025-09-07T11:27:15.0571218Z + echo 'dependencies={}'
2025-09-07T11:27:15.0590374Z ##[group]Run set -eux
2025-09-07T11:27:15.0590699Z set -eux
2025-09-07T11:27:15.0590854Z 
2025-09-07T11:27:15.0591020Z if [[ -n "" ]]; then
2025-09-07T11:27:15.0591201Z   source ""
2025-09-07T11:27:15.0591370Z fi
2025-09-07T11:27:15.0591527Z 
2025-09-07T11:27:15.0591702Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then
2025-09-07T11:27:15.0591977Z   echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping"
2025-09-07T11:27:15.0592280Z   # We don't want the job to fail if the directory doesn't exist
2025-09-07T11:27:15.0592520Z   exit 0
2025-09-07T11:27:15.0592670Z fi
2025-09-07T11:27:15.0592802Z 
2025-09-07T11:27:15.0592956Z if [[ "${DRY_RUN}" == "true" ]]; then
2025-09-07T11:27:15.0593254Z   python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \
2025-09-07T11:27:15.0593596Z     --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \
2025-09-07T11:27:15.0593866Z     --metadata "${BENCHMARK_METADATA}" \
2025-09-07T11:27:15.0594083Z     --runners "${RUNNER_INFO}" \
2025-09-07T11:27:15.0594317Z     --dependencies "${DEPENDENCIES}" \
2025-09-07T11:27:15.0594529Z     --dry-run
2025-09-07T11:27:15.0594698Z else
2025-09-07T11:27:15.0594927Z   python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \
2025-09-07T11:27:15.0595267Z     --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \
2025-09-07T11:27:15.0595524Z     --metadata "${BENCHMARK_METADATA}" \
2025-09-07T11:27:15.0595741Z     --runners "${RUNNER_INFO}" \
2025-09-07T11:27:15.0595955Z     --dependencies "${DEPENDENCIES}"
2025-09-07T11:27:15.0596156Z fi
2025-09-07T11:27:15.0603552Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:15.0603793Z env:
2025-09-07T11:27:15.0603937Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:15.0604235Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:15.0604545Z   DEVICE_NAME: 
2025-09-07T11:27:15.0604705Z   DEVICE_TYPE: 
2025-09-07T11:27:15.0604874Z   BENCHMARK_RESULTS_DIR: test/test-reports
2025-09-07T11:27:15.0605074Z   DRY_RUN: false
2025-09-07T11:27:15.0605891Z   BENCHMARK_METADATA: {"timestamp": 1757244435, "schema_version": "v3", "name": "inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525294857, "run_attempt": 1, "job_id": 49775530523}
2025-09-07T11:27:15.0606927Z   RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 369, "extra_info": {"hostname": "ip-10-0-74-111.ec2.internal"}, "name": "", "type": ""}]
2025-09-07T11:27:15.0607313Z   DEPENDENCIES: {}
2025-09-07T11:27:15.0607474Z ##[endgroup]
2025-09-07T11:27:15.0634264Z + [[ -n '' ]]
2025-09-07T11:27:15.0634463Z + [[ ! -d test/test-reports ]]
2025-09-07T11:27:15.0634656Z + [[ false == \t\r\u\e ]]
2025-09-07T11:27:15.0636503Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1757244435, "schema_version": "v3", "name": "inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "93fb23d6fae7c4e82c4239a1033e522088742634", "workflow_id": 17525294857, "run_attempt": 1, "job_id": 49775530523}' --runners '[{"cpu_info": "x86_64", "cpu_count": 96, "avail_mem_in_gb": 369, "extra_info": {"hostname": "ip-10-0-74-111.ec2.internal"}, "name": "", "type": ""}]' --dependencies '{}'
2025-09-07T11:27:15.1712474Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json
2025-09-07T11:27:15.1962465Z INFO:botocore.credentials:Found credentials from IAM Role: gh-ci-github-action-runners-runner-role
2025-09-07T11:27:15.3746431Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json
2025-09-07T11:27:15.4612221Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json
2025-09-07T11:27:15.5419121Z INFO:root:Upload test/test-reports/inductor_export_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_export_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json
2025-09-07T11:27:15.6141258Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json
2025-09-07T11:27:15.6892072Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance.json
2025-09-07T11:27:15.7877327Z INFO:root:Upload test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json
2025-09-07T11:27:15.8867149Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance.json
2025-09-07T11:27:15.9835297Z INFO:root:Upload test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json
2025-09-07T11:27:16.0803117Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance.json
2025-09-07T11:27:16.1707080Z INFO:root:Upload test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json
2025-09-07T11:27:16.2585305Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance.json
2025-09-07T11:27:16.3350275Z INFO:root:Upload test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json to s3://ossci-benchmarks/v3/pytorch/pytorch/17525294857/49775530523/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json
2025-09-07T11:27:16.4720350Z ##[group]Run cat test/**/*_toprint.log || true
2025-09-07T11:27:16.4720635Z cat test/**/*_toprint.log || true
2025-09-07T11:27:16.4727730Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:16.4728094Z env:
2025-09-07T11:27:16.4728246Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:16.4728530Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:16.4728831Z   DEVICE_NAME: 
2025-09-07T11:27:16.4728992Z   DEVICE_TYPE: 
2025-09-07T11:27:16.4729134Z ##[endgroup]
2025-09-07T11:27:16.4815760Z cat: 'test/**/*_toprint.log': No such file or directory
2025-09-07T11:27:16.4840967Z ##[group]Run kill "$MONITOR_SCRIPT_PID"
2025-09-07T11:27:16.4841231Z kill "$MONITOR_SCRIPT_PID"
2025-09-07T11:27:16.4848130Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:16.4848369Z env:
2025-09-07T11:27:16.4848526Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:16.4848825Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:16.4849134Z   DEVICE_NAME: 
2025-09-07T11:27:16.4849279Z   DEVICE_TYPE: 
2025-09-07T11:27:16.4849438Z   MONITOR_SCRIPT_PID: 57293
2025-09-07T11:27:16.4849628Z ##[endgroup]
2025-09-07T11:27:16.4954254Z Prepare all required actions
2025-09-07T11:27:16.4954675Z Getting action download info
2025-09-07T11:27:16.6422001Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a)
2025-09-07T11:27:16.8278298Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02)
2025-09-07T11:27:17.1733527Z ##[group]Run ./.github/actions/upload-test-artifacts
2025-09-07T11:27:17.1733772Z with:
2025-09-07T11:27:17.1734054Z   file-suffix: test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T11:27:17.1734378Z   s3-bucket: gha-artifacts
2025-09-07T11:27:17.1734558Z env:
2025-09-07T11:27:17.1734705Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.1734994Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.1735301Z   DEVICE_NAME: 
2025-09-07T11:27:17.1735449Z   DEVICE_TYPE: 
2025-09-07T11:27:17.1735614Z ##[endgroup]
2025-09-07T11:27:17.1779056Z ##[group]Run # Remove any previous test jsons if they exist
2025-09-07T11:27:17.1779352Z # Remove any previous test jsons if they exist
2025-09-07T11:27:17.1779586Z rm -f test-jsons-*.zip
2025-09-07T11:27:17.1779866Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json'
2025-09-07T11:27:17.1787069Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:17.1787314Z env:
2025-09-07T11:27:17.1787461Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.1787762Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.1788075Z   DEVICE_NAME: 
2025-09-07T11:27:17.1788232Z   DEVICE_TYPE: 
2025-09-07T11:27:17.1788507Z   FILE_SUFFIX: test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T11:27:17.1788811Z ##[endgroup]
2025-09-07T11:27:17.1935428Z   adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json (deflated 99%)
2025-09-07T11:27:17.1949782Z   adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json (deflated 99%)
2025-09-07T11:27:17.1964712Z   adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json (deflated 99%)
2025-09-07T11:27:17.1979423Z   adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json (deflated 99%)
2025-09-07T11:27:17.1994144Z   adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.json (deflated 99%)
2025-09-07T11:27:17.2016778Z   adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance.json (deflated 99%)
2025-09-07T11:27:17.2066843Z   adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json (deflated 99%)
2025-09-07T11:27:17.2089545Z   adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance.json (deflated 99%)
2025-09-07T11:27:17.2140573Z   adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json (deflated 99%)
2025-09-07T11:27:17.2163000Z   adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance.json (deflated 99%)
2025-09-07T11:27:17.2213260Z   adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json (deflated 99%)
2025-09-07T11:27:17.2235277Z   adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance.json (deflated 99%)
2025-09-07T11:27:17.2267724Z   adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.json (deflated 99%)
2025-09-07T11:27:17.2315472Z ##[group]Run # Remove any previous test reports if they exist
2025-09-07T11:27:17.2316006Z # Remove any previous test reports if they exist
2025-09-07T11:27:17.2316261Z rm -f test-reports-*.zip
2025-09-07T11:27:17.2316562Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv'
2025-09-07T11:27:17.2329670Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:17.2329907Z env:
2025-09-07T11:27:17.2330052Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.2330337Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.2330636Z   DEVICE_NAME: 
2025-09-07T11:27:17.2330785Z   DEVICE_TYPE: 
2025-09-07T11:27:17.2331106Z   FILE_SUFFIX: test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T11:27:17.2331408Z ##[endgroup]
2025-09-07T11:27:17.2451337Z   adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv (deflated 53%)
2025-09-07T11:27:17.2451938Z   adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv (deflated 52%)
2025-09-07T11:27:17.2452507Z   adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv (deflated 53%)
2025-09-07T11:27:17.2453049Z   adding: test/test-reports/inductor_export_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv (deflated 55%)
2025-09-07T11:27:17.2453593Z   adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_accuracy.csv (deflated 65%)
2025-09-07T11:27:17.2454163Z   adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv (deflated 47%)
2025-09-07T11:27:17.2454785Z   adding: test/test-reports/inductor_no_cudagraphs_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.csv (deflated 50%)
2025-09-07T11:27:17.2455393Z   adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv (deflated 47%)
2025-09-07T11:27:17.2456318Z   adding: test/test-reports/inductor_dynamic_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.csv (deflated 50%)
2025-09-07T11:27:17.2456926Z   adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv (deflated 48%)
2025-09-07T11:27:17.2458155Z   adding: test/test-reports/inductor_cpp_wrapper_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.csv (deflated 51%)
2025-09-07T11:27:17.2458799Z   adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance.csv (deflated 49%)
2025-09-07T11:27:17.2459610Z   adding: test/test-reports/inductor_aot_inductor_torchbench_bfloat16_inference_cpu_x86_zen_performance_compilation_metrics.csv (deflated 49%)
2025-09-07T11:27:17.2489105Z ##[group]Run # Remove any previous usage logs if they exist
2025-09-07T11:27:17.2489425Z # Remove any previous usage logs if they exist
2025-09-07T11:27:17.2489668Z rm -f logs-*.zip
2025-09-07T11:27:17.2490025Z zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true
2025-09-07T11:27:17.2490357Z zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true
2025-09-07T11:27:17.2497366Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:17.2497617Z env:
2025-09-07T11:27:17.2497785Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.2498095Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.2498398Z   DEVICE_NAME: 
2025-09-07T11:27:17.2498550Z   DEVICE_TYPE: 
2025-09-07T11:27:17.2499018Z   FILE_SUFFIX: test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T11:27:17.2499340Z ##[endgroup]
2025-09-07T11:27:17.2605114Z   adding: usage_log.txt (deflated 97%)
2025-09-07T11:27:17.2620388Z 
2025-09-07T11:27:17.2620735Z zip error: Nothing to do! (logs-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip)
2025-09-07T11:27:17.2652686Z ##[group]Run # Remove any previous debugging artifacts if they exist
2025-09-07T11:27:17.2653045Z # Remove any previous debugging artifacts if they exist
2025-09-07T11:27:17.2653303Z rm -f debug-*.zip
2025-09-07T11:27:17.2653491Z if [ -d 'test/debug' ]; then
2025-09-07T11:27:17.2653739Z   zip -r "debug-${FILE_SUFFIX}.zip" test/debug
2025-09-07T11:27:17.2653962Z fi
2025-09-07T11:27:17.2660922Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:17.2661166Z env:
2025-09-07T11:27:17.2661312Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.2661624Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.2661944Z   DEVICE_NAME: 
2025-09-07T11:27:17.2662096Z   DEVICE_TYPE: 
2025-09-07T11:27:17.2662380Z   FILE_SUFFIX: test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523
2025-09-07T11:27:17.2662692Z ##[endgroup]
2025-09-07T11:27:17.2753613Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-09-07T11:27:17.2753875Z with:
2025-09-07T11:27:17.2754032Z   s3-bucket: gha-artifacts
2025-09-07T11:27:17.2754240Z   s3-prefix: pytorch/pytorch/17525294857/1/artifact

2025-09-07T11:27:17.2754479Z   retention-days: 14
2025-09-07T11:27:17.2754645Z   if-no-files-found: warn
2025-09-07T11:27:17.2754839Z   path: test-jsons-*.zip
2025-09-07T11:27:17.2755015Z   name: artifact
2025-09-07T11:27:17.2755183Z   region: us-east-1
2025-09-07T11:27:17.2755335Z env:
2025-09-07T11:27:17.2755478Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.2755768Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.2756083Z   DEVICE_NAME: 
2025-09-07T11:27:17.2756237Z   DEVICE_TYPE: 
2025-09-07T11:27:17.2756396Z ##[endgroup]
2025-09-07T11:27:17.5717704Z NOTE: s3-prefix specified, ignoring name parameter
2025-09-07T11:27:17.5718018Z With the provided path, there will be 1 file uploaded
2025-09-07T11:27:17.5718315Z Uploading to s3 prefix: pytorch/pytorch/17525294857/1/artifact
2025-09-07T11:27:17.5775679Z Starting upload of test-jsons-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:17.7270471Z Finished upload of test-jsons-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:17.7480165Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-09-07T11:27:17.7480382Z with:
2025-09-07T11:27:17.7480540Z   s3-bucket: gha-artifacts
2025-09-07T11:27:17.7480756Z   s3-prefix: pytorch/pytorch/17525294857/1/artifact

2025-09-07T11:27:17.7480978Z   retention-days: 14
2025-09-07T11:27:17.7481137Z   if-no-files-found: error
2025-09-07T11:27:17.7481321Z   path: test-reports-*.zip
2025-09-07T11:27:17.7481493Z   name: artifact
2025-09-07T11:27:17.7481648Z   region: us-east-1
2025-09-07T11:27:17.7481794Z env:
2025-09-07T11:27:17.7481936Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:17.7482228Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:17.7482646Z   DEVICE_NAME: 
2025-09-07T11:27:17.7482806Z   DEVICE_TYPE: 
2025-09-07T11:27:17.7482953Z ##[endgroup]
2025-09-07T11:27:18.0152638Z NOTE: s3-prefix specified, ignoring name parameter
2025-09-07T11:27:18.0152947Z With the provided path, there will be 1 file uploaded
2025-09-07T11:27:18.0153246Z Uploading to s3 prefix: pytorch/pytorch/17525294857/1/artifact
2025-09-07T11:27:18.0210247Z Starting upload of test-reports-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:18.1249131Z Finished upload of test-reports-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:18.1460139Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-09-07T11:27:18.1460359Z with:
2025-09-07T11:27:18.1460511Z   s3-bucket: gha-artifacts
2025-09-07T11:27:18.1460728Z   s3-prefix: pytorch/pytorch/17525294857/1/artifact

2025-09-07T11:27:18.1460954Z   retention-days: 14
2025-09-07T11:27:18.1461123Z   if-no-files-found: ignore
2025-09-07T11:27:18.1461326Z   path: logs-*.zip
2025-09-07T11:27:18.1461659Z   name: artifact
2025-09-07T11:27:18.1461819Z   region: us-east-1
2025-09-07T11:27:18.1461967Z env:
2025-09-07T11:27:18.1462115Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:18.1462415Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:18.1462744Z   DEVICE_NAME: 
2025-09-07T11:27:18.1462894Z   DEVICE_TYPE: 
2025-09-07T11:27:18.1463038Z ##[endgroup]
2025-09-07T11:27:18.4119359Z NOTE: s3-prefix specified, ignoring name parameter
2025-09-07T11:27:18.4119703Z With the provided path, there will be 1 file uploaded
2025-09-07T11:27:18.4119994Z Uploading to s3 prefix: pytorch/pytorch/17525294857/1/artifact
2025-09-07T11:27:18.4174938Z Starting upload of logs-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:18.5249479Z Finished upload of logs-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:18.5456423Z ##[group]Run seemethere/upload-artifact-s3@v5
2025-09-07T11:27:18.5456671Z with:
2025-09-07T11:27:18.5456828Z   s3-bucket: gha-artifacts
2025-09-07T11:27:18.5457047Z   s3-prefix: pytorch/pytorch/17525294857/1/artifact

2025-09-07T11:27:18.5457267Z   retention-days: 14
2025-09-07T11:27:18.5457439Z   if-no-files-found: ignore
2025-09-07T11:27:18.5457621Z   path: debug-*.zip
2025-09-07T11:27:18.5457778Z   name: artifact
2025-09-07T11:27:18.5457927Z   region: us-east-1
2025-09-07T11:27:18.5458076Z env:
2025-09-07T11:27:18.5458219Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:18.5458515Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:18.5458826Z   DEVICE_NAME: 
2025-09-07T11:27:18.5458972Z   DEVICE_TYPE: 
2025-09-07T11:27:18.5459123Z ##[endgroup]
2025-09-07T11:27:18.8143063Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded.
2025-09-07T11:27:18.8371162Z ##[group]Run # shellcheck disable=SC2156
2025-09-07T11:27:18.8371431Z # shellcheck disable=SC2156
2025-09-07T11:27:18.8371813Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \;
2025-09-07T11:27:18.8378942Z shell: /usr/bin/bash -e {0}
2025-09-07T11:27:18.8379122Z env:
2025-09-07T11:27:18.8379371Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:18.8379665Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:18.8379976Z   DEVICE_NAME: 
2025-09-07T11:27:18.8380127Z   DEVICE_TYPE: 
2025-09-07T11:27:18.8380296Z ##[endgroup]
2025-09-07T11:27:19.1483265Z Prepare all required actions
2025-09-07T11:27:19.1483555Z Getting action download info
2025-09-07T11:27:19.2675134Z ##[group]Run ./.github/actions/upload-utilization-stats
2025-09-07T11:27:19.2675376Z with:
2025-09-07T11:27:19.2675530Z   job_id: 49775530523
2025-09-07T11:27:19.2675861Z   job_name: inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T11:27:19.2676354Z   workflow_name: inductor-perf-nightly-x86-zen
2025-09-07T11:27:19.2676573Z   workflow_run_id: 17525294857
2025-09-07T11:27:19.2676761Z   workflow_attempt: 1
2025-09-07T11:27:19.2676919Z env:
2025-09-07T11:27:19.2677068Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:19.2677365Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:19.2677677Z   DEVICE_NAME: 
2025-09-07T11:27:19.2677828Z   DEVICE_TYPE: 
2025-09-07T11:27:19.2677974Z ##[endgroup]
2025-09-07T11:27:19.2691267Z ##[group]Run echo "workflow_id: 17525294857"
2025-09-07T11:27:19.2691546Z echo "workflow_id: 17525294857"
2025-09-07T11:27:19.2691763Z echo "workflow_attempt: 1"
2025-09-07T11:27:19.2692017Z echo "workflow_Name: inductor-perf-nightly-x86-zen"
2025-09-07T11:27:19.2692275Z echo "job_id: 49775530523"
2025-09-07T11:27:19.2692647Z echo "job_name:  inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)"
2025-09-07T11:27:19.2693025Z echo "artifact_prefix: "
2025-09-07T11:27:19.2693229Z python3 --version
2025-09-07T11:27:19.2700500Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:19.2700737Z env:
2025-09-07T11:27:19.2700891Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:19.2701185Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:19.2701488Z   DEVICE_NAME: 
2025-09-07T11:27:19.2701643Z   DEVICE_TYPE: 
2025-09-07T11:27:19.2701795Z ##[endgroup]
2025-09-07T11:27:19.2727856Z workflow_id: 17525294857
2025-09-07T11:27:19.2728041Z workflow_attempt: 1
2025-09-07T11:27:19.2728241Z workflow_Name: inductor-perf-nightly-x86-zen
2025-09-07T11:27:19.2728462Z job_id: 49775530523
2025-09-07T11:27:19.2728773Z job_name:  inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)
2025-09-07T11:27:19.2729122Z artifact_prefix: 
2025-09-07T11:27:19.2743679Z Python 3.9.23
2025-09-07T11:27:19.2775054Z ##[group]Run nick-fields/retry@v3.0.0
2025-09-07T11:27:19.2775269Z with:
2025-09-07T11:27:19.2775426Z   shell: bash
2025-09-07T11:27:19.2775579Z   timeout_minutes: 5
2025-09-07T11:27:19.2775751Z   max_attempts: 5
2025-09-07T11:27:19.2775907Z   retry_wait_seconds: 30
2025-09-07T11:27:19.2776281Z   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

2025-09-07T11:27:19.2776648Z   polling_interval_seconds: 1
2025-09-07T11:27:19.2776840Z   warning_on_retry: true
2025-09-07T11:27:19.2777032Z   continue_on_error: false
2025-09-07T11:27:19.2777195Z env:
2025-09-07T11:27:19.2777340Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:19.2777635Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:19.2777939Z   DEVICE_NAME: 
2025-09-07T11:27:19.2778082Z   DEVICE_TYPE: 
2025-09-07T11:27:19.2778230Z ##[endgroup]
2025-09-07T11:27:19.5382441Z Defaulting to user installation because normal site-packages is not writeable
2025-09-07T11:27:19.5990802Z Collecting python-dateutil==2.8.2
2025-09-07T11:27:19.6283465Z   Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB)
2025-09-07T11:27:20.3011255Z Collecting boto3==1.35.42
2025-09-07T11:27:20.3100811Z   Downloading boto3-1.35.42-py3-none-any.whl (139 kB)
2025-09-07T11:27:20.6664027Z Collecting pandas==2.1.3
2025-09-07T11:27:20.6775600Z   Downloading pandas-2.1.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB)
2025-09-07T11:27:20.7910721Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/ec2-user/.local/lib/python3.9/site-packages (0.6.7)
2025-09-07T11:27:20.7921135Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil==2.8.2) (1.15.0)
2025-09-07T11:27:20.7952844Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.4)
2025-09-07T11:27:20.7956408Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.0)
2025-09-07T11:27:20.7958802Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (1.35.99)
2025-09-07T11:27:20.8373903Z Requirement already satisfied: pytz>=2020.1 in /usr/lib/python3.9/site-packages (from pandas==2.1.3) (2022.7.1)
2025-09-07T11:27:21.4047251Z Collecting numpy<2,>=1.22.4
2025-09-07T11:27:21.4135436Z   Downloading numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)
2025-09-07T11:27:21.5735809Z Collecting tzdata>=2022.1
2025-09-07T11:27:21.5820472Z   Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB)
2025-09-07T11:27:21.5916060Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (3.26.1)
2025-09-07T11:27:21.5918793Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (0.9.0)
2025-09-07T11:27:21.5959343Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.42->boto3==1.35.42) (1.25.10)
2025-09-07T11:27:21.6041937Z Requirement already satisfied: packaging>=17.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0)
2025-09-07T11:27:21.6112987Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0)
2025-09-07T11:27:21.6115547Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0)
2025-09-07T11:27:21.7215511Z Installing collected packages: python-dateutil, tzdata, numpy, pandas, boto3
2025-09-07T11:27:25.5232636Z   Attempting uninstall: boto3
2025-09-07T11:27:25.5233139Z     Found existing installation: boto3 1.35.33
2025-09-07T11:27:25.5325164Z     Uninstalling boto3-1.35.33:
2025-09-07T11:27:25.5337233Z       Successfully uninstalled boto3-1.35.33
2025-09-07T11:27:25.5792285Z Successfully installed boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 tzdata-2025.2
2025-09-07T11:27:26.3433734Z Command completed after 1 attempt(s).
2025-09-07T11:27:26.3489555Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
2025-09-07T11:27:26.3490016Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
2025-09-07T11:27:26.3490345Z   --workflow-run-id "17525294857" \
2025-09-07T11:27:26.3490625Z   --workflow-name "inductor-perf-nightly-x86-zen" \
2025-09-07T11:27:26.3490906Z   --workflow-run-attempt "1" \
2025-09-07T11:27:26.3491126Z   --job-id "49775530523" \
2025-09-07T11:27:26.3491504Z   --job-name "inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)" \
2025-09-07T11:27:26.3491886Z   --local-path "" \
2025-09-07T11:27:26.3492092Z   --artifact-prefix ""
2025-09-07T11:27:26.3499409Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:26.3499652Z env:
2025-09-07T11:27:26.3499887Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:26.3500183Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:26.3500491Z   DEVICE_NAME: 
2025-09-07T11:27:26.3500647Z   DEVICE_TYPE: 
2025-09-07T11:27:26.3500805Z ##[endgroup]
2025-09-07T11:27:27.4341084Z repo: pytorch/pytorch
2025-09-07T11:27:27.4341401Z Search for test log in s3 bucket: ossci-utilization
2025-09-07T11:27:27.4341815Z Downloading logs-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:27.4342354Z extracting usage_log.txt from zip file logs-test-inductor_torchbench_perf_cpu_x86_zen-1-4-linux.24xlarge.amd_49775530523.zip
2025-09-07T11:27:27.4342763Z Converted Log Model: UtilizationMetadata:
2025-09-07T11:27:27.4343809Z  UtilizationMetadata(level='metadata', workflow_id='17525294857', job_id='49775530523', workflow_name='inductor-perf-nightly-x86-zen', job_name='inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)', usage_collect_interval=4.0, data_model_version=1.5, start_at=1757231030, gpu_count=0, cpu_count=96, gpu_type=None, error=None)
2025-09-07T11:27:27.4344805Z [Db Segments] detected pytest cmd: 15, generated segments: 15
2025-09-07T11:27:27.4345064Z [db model] Peek db timeseries 
2025-09-07T11:27:27.4345249Z :{
2025-09-07T11:27:27.4345384Z     "created_at": 1757244447,
2025-09-07T11:27:27.4345644Z     "type": "utilization",
2025-09-07T11:27:27.4345817Z     "tags": [
2025-09-07T11:27:27.4345956Z         "record"
2025-09-07T11:27:27.4346098Z     ],
2025-09-07T11:27:27.4346243Z     "time_stamp": 1757231030,
2025-09-07T11:27:27.4346431Z     "repo": "pytorch/pytorch",
2025-09-07T11:27:27.4346615Z     "workflow_id": 17525294857,
2025-09-07T11:27:27.4346814Z     "run_attempt": 1,
2025-09-07T11:27:27.4346976Z     "job_id": 49775530523,
2025-09-07T11:27:27.4347187Z     "workflow_name": "inductor-perf-nightly-x86-zen",
2025-09-07T11:27:27.4347590Z     "job_name": "inductor-test-nightly / test (inductor_torchbench_perf_cpu_x86_zen, 1, 4, linux.24xlarge.amd)",
2025-09-07T11:27:27.4347932Z     "json_data": "{}"
2025-09-07T11:27:27.4348087Z }
2025-09-07T11:27:27.4348407Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525294857/1/49775530523/metadata
2025-09-07T11:27:27.4348982Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17525294857/1/49775530523/metadata 
2025-09-07T11:27:27.4349556Z Writing 887 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525294857/1/49775530523/time_series
2025-09-07T11:27:27.4350142Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17525294857/1/49775530523/time_series 
2025-09-07T11:27:27.5253349Z ##[group]Run pytorch/test-infra/.github/actions/teardown-linux@main
2025-09-07T11:27:27.5253674Z with:
2025-09-07T11:27:27.5253821Z env:
2025-09-07T11:27:27.5253958Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:27.5254256Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:27.5254580Z   DEVICE_NAME: 
2025-09-07T11:27:27.5254728Z   DEVICE_TYPE: 
2025-09-07T11:27:27.5254865Z ##[endgroup]
2025-09-07T11:27:27.5268449Z ##[group]Run set -eou pipefail
2025-09-07T11:27:27.5268719Z set -eou pipefail
2025-09-07T11:27:27.5268889Z 
2025-09-07T11:27:27.5269124Z echo "Holding runner for 2 hours until all ssh sessions have logged out"
2025-09-07T11:27:27.5269406Z for _ in $(seq 1440); do
2025-09-07T11:27:27.5269627Z     # Break if no ssh session exists anymore
2025-09-07T11:27:27.5269848Z     if [ "$(who)" = "" ]; then
2025-09-07T11:27:27.5270037Z       break
2025-09-07T11:27:27.5270221Z     fi
2025-09-07T11:27:27.5270374Z     echo "."
2025-09-07T11:27:27.5270527Z     sleep 5
2025-09-07T11:27:27.5270677Z done
2025-09-07T11:27:27.5277692Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:27.5278024Z env:
2025-09-07T11:27:27.5278165Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:27.5278462Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:27.5278773Z   DEVICE_NAME: 
2025-09-07T11:27:27.5278926Z   DEVICE_TYPE: 
2025-09-07T11:27:27.5279068Z ##[endgroup]
2025-09-07T11:27:27.5305335Z Holding runner for 2 hours until all ssh sessions have logged out
2025-09-07T11:27:27.5381986Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty
2025-09-07T11:27:27.5393177Z # ignore expansion of "docker ps -q" since it could be empty
2025-09-07T11:27:27.5393462Z # shellcheck disable=SC2046
2025-09-07T11:27:27.5393724Z docker stop $(docker ps -q) || true
2025-09-07T11:27:27.5394100Z # Prune all of the docker images
2025-09-07T11:27:27.5394324Z docker system prune -af
2025-09-07T11:27:27.5401567Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:27.5401830Z env:
2025-09-07T11:27:27.5401984Z   GIT_DEFAULT_BRANCH: main
2025-09-07T11:27:27.5402284Z   DOCKER_CONTAINER_ID: 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:27.5402592Z   DEVICE_NAME: 
2025-09-07T11:27:27.5402741Z   DEVICE_TYPE: 
2025-09-07T11:27:27.5402886Z ##[endgroup]
2025-09-07T11:27:38.5327838Z 79fc4b4803c2
2025-09-07T11:27:39.5440960Z Deleted Containers:
2025-09-07T11:27:39.5441284Z 79fc4b4803c27b53615decdce8d1e9358b50ef299304d01a1837181567de81a8
2025-09-07T11:27:39.5441491Z 
2025-09-07T11:27:55.3814676Z Deleted Images:
2025-09-07T11:27:55.3815338Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks-ae53c6842aa4c2407d0ad976491ca941c2635c77
2025-09-07T11:27:55.3816196Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image@sha256:383efb45082f20b8c808cb0ba4df693a01359592233f641f1f486911ac320a9a
2025-09-07T11:27:55.3816757Z deleted: sha256:662d8c9dfc7db2f5d004293de4f2b7647941dee4c916479ef082d17fcdfd9c47
2025-09-07T11:27:55.3817161Z deleted: sha256:ea5ad443c754124b3a5a209c2663376b4c156947edef1b982a336148bbf9114d
2025-09-07T11:27:55.3817570Z deleted: sha256:284be7504f072e0c04da4e2190e8d0e1de73835ed67be81f3ddd7eafd5d06a3a
2025-09-07T11:27:55.3817976Z deleted: sha256:2f49ff4be65f7ca55de8d7028fb3df7d08232a9f043aa7ba27d9393724286281
2025-09-07T11:27:55.3818382Z deleted: sha256:f63b503fdd1cca198aecefb9eef7ffbeb5fbc723f2a8462f50316e56cd403cbc
2025-09-07T11:27:55.3818779Z deleted: sha256:f9d46e08457013f0e71d608ac3dd95b79c41120060a80baefa684048cc15574e
2025-09-07T11:27:55.3819169Z deleted: sha256:cab76e28615751b6d6a703103b1da790a67cb3a4ee2e8814de51de18ff8b595d
2025-09-07T11:27:55.3820157Z deleted: sha256:0b2d09aa482371591a32563a5db71472822abd096a347967a9bd2a177737109f
2025-09-07T11:27:55.3820561Z deleted: sha256:d306d346d5da05e9fd04284304b1637a0bf01ee97397c688d19d783d5e133de9
2025-09-07T11:27:55.3820955Z deleted: sha256:bb3381a916d410a6e304540bb0796099dc780cd11f5829e734b337e0e79acfe4
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2025-09-07T11:27:55.3847447Z Total reclaimed space: 56.56GB
2025-09-07T11:27:55.3925101Z Post job cleanup.
2025-09-07T11:27:55.3955838Z Post job cleanup.
2025-09-07T11:27:55.4703147Z [command]/usr/bin/git version
2025-09-07T11:27:55.4747805Z git version 2.47.1
2025-09-07T11:27:55.4777965Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/dc027324-f61f-4837-9375-c50506192bbd/.gitconfig'
2025-09-07T11:27:55.4786145Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/dc027324-f61f-4837-9375-c50506192bbd' before making global git config changes
2025-09-07T11:27:55.4786881Z Adding repository directory to the temporary git global config as a safe directory
2025-09-07T11:27:55.4790549Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch
2025-09-07T11:27:55.4831298Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand
2025-09-07T11:27:55.4873764Z [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' || :"
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2025-09-07T11:27:55.9024200Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
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2025-09-07T11:27:55.9154579Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T11:27:55.9219789Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
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2025-09-07T11:27:55.9351091Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
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2025-09-07T11:27:55.9771568Z Entering 'third_party/psimd'
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2025-09-07T11:27:56.0424592Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T11:27:56.0516094Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader
2025-09-07T11:27:56.0540293Z http.https://github.com/.extraheader
2025-09-07T11:27:56.0550645Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader
2025-09-07T11:27:56.0581157Z [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' || :"
2025-09-07T11:27:56.0934604Z Entering 'android/libs/fbjni'
2025-09-07T11:27:56.0979770Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.1552737Z Entering 'third_party/aiter'
2025-09-07T11:27:56.1597239Z http.https://github.com/.extraheader
2025-09-07T11:27:56.1640207Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-09-07T11:27:56.1684116Z http.https://github.com/.extraheader
2025-09-07T11:27:56.1735567Z Entering 'third_party/benchmark'
2025-09-07T11:27:56.1781877Z http.https://github.com/.extraheader
2025-09-07T11:27:56.1825530Z Entering 'third_party/composable_kernel'
2025-09-07T11:27:56.1871709Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.1964470Z http.https://github.com/.extraheader
2025-09-07T11:27:56.2006218Z Entering 'third_party/cpuinfo'
2025-09-07T11:27:56.2050415Z http.https://github.com/.extraheader
2025-09-07T11:27:56.2093184Z Entering 'third_party/cudnn_frontend'
2025-09-07T11:27:56.2138196Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.2224627Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.2317608Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.2400320Z http.https://github.com/.extraheader
2025-09-07T11:27:56.2440529Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-09-07T11:27:56.2486755Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.2580299Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.2759151Z http.https://github.com/.extraheader
2025-09-07T11:27:56.2801600Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-09-07T11:27:56.2845525Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.3113992Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.3950550Z Entering 'third_party/kineto'
2025-09-07T11:27:56.3993531Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4035895Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-09-07T11:27:56.4076915Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4117377Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-09-07T11:27:56.4161171Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4204615Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-09-07T11:27:56.4248704Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4289524Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-09-07T11:27:56.4332547Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4375306Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-09-07T11:27:56.4422164Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4462155Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
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2025-09-07T11:27:56.4552307Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-09-07T11:27:56.4599323Z http.https://github.com/.extraheader
2025-09-07T11:27:56.4641533Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
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2025-09-07T11:27:56.4724814Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
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2025-09-07T11:27:56.4807625Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
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2025-09-07T11:27:56.4937116Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.5022595Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5066904Z Entering 'third_party/kleidiai'
2025-09-07T11:27:56.5114427Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5153669Z Entering 'third_party/mimalloc'
2025-09-07T11:27:56.5197808Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5237972Z Entering 'third_party/nlohmann'
2025-09-07T11:27:56.5282304Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5323637Z Entering 'third_party/onnx'
2025-09-07T11:27:56.5367564Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.5471432Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5517807Z Entering 'third_party/opentelemetry-cpp'
2025-09-07T11:27:56.5562725Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5607356Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-09-07T11:27:56.5649189Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5688123Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-09-07T11:27:56.5730980Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5770770Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-09-07T11:27:56.5812815Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5853625Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-09-07T11:27:56.5895561Z http.https://github.com/.extraheader
2025-09-07T11:27:56.5939645Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-09-07T11:27:56.5984587Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6027354Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-09-07T11:27:56.6069181Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6112076Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-09-07T11:27:56.6154979Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6196641Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-09-07T11:27:56.6241827Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6284848Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-09-07T11:27:56.6328879Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6372870Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-09-07T11:27:56.6417942Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6475654Z Entering 'third_party/pocketfft'
2025-09-07T11:27:56.6519194Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6559123Z Entering 'third_party/protobuf'
2025-09-07T11:27:56.6602524Z http.https://github.com/.extraheader
2025-09-07T11:27:56.6644299Z Entering 'third_party/protobuf/third_party/benchmark'
2025-09-07T11:27:56.6689621Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.6819430Z Entering 'third_party/psimd'
2025-09-07T11:27:56.6864073Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.6950298Z http.https://github.com/.extraheader
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2025-09-07T11:27:56.7039079Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7082012Z Entering 'third_party/python-peachpy'
2025-09-07T11:27:56.7127363Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7168205Z Entering 'third_party/sleef'
2025-09-07T11:27:56.7212290Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7253139Z Entering 'third_party/tensorpipe'
2025-09-07T11:27:56.7298684Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7337022Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-09-07T11:27:56.7378869Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7418246Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-09-07T11:27:56.7461095Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7505273Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-09-07T11:27:56.7549250Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7589994Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-09-07T11:27:56.7637896Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7678635Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-09-07T11:27:56.7720666Z http.https://github.com/.extraheader
2025-09-07T11:27:56.7860025Z A job completed hook has been configured by the self-hosted runner administrator
2025-09-07T11:27:56.7876095Z ##[group]Run '/home/ec2-user/runner-scripts/after_job.sh'
2025-09-07T11:27:56.7881888Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0}
2025-09-07T11:27:56.7882153Z ##[endgroup]
2025-09-07T11:27:56.7987308Z [!ALERT!] Swap in detected! [!ALERT!]
2025-09-07T11:28:05.5633381Z [!ALERT!] Swap out detected [!ALERT!]
2025-09-07T11:28:20.8391128Z Cleaning up orphan processes