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[Profiler] Update README #159816
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[Profiler] Update README #159816
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/159816
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (1 Unrelated Failure)As of commit d7f242a with merge base 289f62c ( UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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This pull request was exported from Phabricator. Differential Revision: D79604189 |
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Summary: Updated README with code structure and explanation of core features within profiler Test Plan: N/A Rollback Plan: Differential Revision: D79604189
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This pull request was exported from Phabricator. Differential Revision: D79604189 |
Summary: Updated README with code structure and explanation of core features within profiler Test Plan: N/A Rollback Plan: Differential Revision: D79604189
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c1f48d2
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This pull request was exported from Phabricator. Differential Revision: D79604189 |
Summary: Pull Request resolved: pytorch#159816 Updated README with code structure and explanation of core features within profiler Test Plan: N/A Rollback Plan: Differential Revision: D79604189
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Summary: Updated README with code structure and explanation of core features within profiler Test Plan: N/A Rollback Plan: Differential Revision: D79604189
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This pull request was exported from Phabricator. Differential Revision: D79604189 |
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LGTM. Pretty informative even for someone who works on the profiler.
| When a trace begins, the autograd/profiler backend calls into `profiler_kineto.cpp` to prepare, start, or stop collection. At the start of tracing, the `onFunctionEnter` and `onFunctionExit` callbacks defined in `profiler_kineto.cpp` are registered. | ||
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| Callback registration can be either global or local, depending on the `ExperimentalConfig` used: | ||
| - **Global:** The callback is registered to all threads throughout execution. |
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Can you give an example of when the profiler would need to use global callback in ExperimentalConfig. The thread local callback makes sense to me.
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I was thinking of adding this to a tutorial instead so I can add some visuals to the difference?
Summary: Updated README with code structure and explanation of core features within profiler Test Plan: N/A Rollback Plan: Reviewed By: aaronenyeshi Differential Revision: D79604189
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This pull request was exported from Phabricator. Differential Revision: D79604189 |
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@pytorchbot merge (Initiating merge automatically since Phabricator Diff has merged) |
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 |
Summary: Updated README with code structure and explanation of core features within profiler Test Plan: N/A Rollback Plan: Differential Revision: D79604189 Pull Request resolved: pytorch#159816 Approved by: https://github.com/sanrise, https://github.com/aaronenyeshi
Summary: Updated README with code structure and explanation of core features within profiler
Test Plan:
N/A
Rollback Plan:
Differential Revision: D79604189