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Add a custom profiler configuration option #151656
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/151656
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 4d47924 with merge base e2c9d8d ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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third_party/kineto
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please update to latest submodule
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will approve after submodule updated
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The submodule has been updated. Please review, thanks. @sraikund16 |
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@fwenguang can you fix the failures? |
@sraikund16 fixed |
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@pytorchbot merge |
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Pull workflow has not been scheduled for the PR yet. It could be because author doesn't have permissions to run those or skip-checks keywords were added to PR/commits, aborting merge. Please get/give approval for the workflows and/or remove skip ci decorators before next merge attempt. If you think this is a mistake, please contact PyTorch Dev Infra. |
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@sraikund16 kineto patch already upstream. I rebased main, please help handle the workflow. |
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@pytorchbot rebase |
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@pytorchbot started a rebase job onto refs/remotes/origin/viable/strict. Check the current status here |
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Successfully rebased |
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
We aim to pass some configuration options to our custom Kineto backend via ExperimentalConfig,, so we added a
custom_profiler_configparameter.Requires pytorch/kineto#1077 ,