[Retry] Log chromium events to scuba #134118
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/134118
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 5d368b3 with merge base 2db28a9 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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This pull request was exported from Phabricator. Differential Revision: D61603243 |
oulgen
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Summary: X-link: pytorch/pytorch#134118 For some reason exporting D61392607 is just not working, so I'm resubmitting this. This diff implements a bunch of views for internal scuba viewing. TODOS that I might punt to another diff: - Saving cache stats via counter is definitely sus here, but there's not really a good way to track "fx graph cache hit for this compile phase" right now. Will think about this more. - We should definitely log frame id, compile id, etc - We should definitely be logging configs. That way, we can A/B test based on whether a config is turned on. - idk what I'm doing with compile_uuid yet, but it's useful when you want to look at samples for a single run. I think if we had mast job info this field is not needed, but it's nice to be able to drill down to a single run and get its chrome trace view or icicle view, so idk Reviewed By: oulgen Differential Revision: D61603243
Summary: X-link: pytorch/benchmark#2429 Pull Request resolved: #134118 For some reason exporting D61392607 is just not working, so I'm resubmitting this. This diff implements a bunch of views for internal scuba viewing. TODOS that I might punt to another diff: - Saving cache stats via counter is definitely sus here, but there's not really a good way to track "fx graph cache hit for this compile phase" right now. Will think about this more. - We should definitely log frame id, compile id, etc - We should definitely be logging configs. That way, we can A/B test based on whether a config is turned on. - idk what I'm doing with compile_uuid yet, but it's useful when you want to look at samples for a single run. I think if we had mast job info this field is not needed, but it's nice to be able to drill down to a single run and get its chrome trace view or icicle view, so idk Test Plan: All of the above views are run with nanogpt benchmark: ``` buck run mode/opt caffe2/benchmarks/dynamo:torchbench -- --training --backend=inductor --only nanogpt --performance ``` Reviewed By: oulgen Differential Revision: D61603243
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This pull request was exported from Phabricator. Differential Revision: D61603243 |
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Summary: Pull Request resolved: pytorch#2429 X-link: pytorch/pytorch#134118 For some reason exporting D61392607 is just not working, so I'm resubmitting this. This diff implements a bunch of views for internal scuba viewing. TODOS that I might punt to another diff: - Saving cache stats via counter is definitely sus here, but there's not really a good way to track "fx graph cache hit for this compile phase" right now. Will think about this more. - We should definitely log frame id, compile id, etc - We should definitely be logging configs. That way, we can A/B test based on whether a config is turned on. - idk what I'm doing with compile_uuid yet, but it's useful when you want to look at samples for a single run. I think if we had mast job info this field is not needed, but it's nice to be able to drill down to a single run and get its chrome trace view or icicle view, so idk Reviewed By: oulgen Differential Revision: D61603243
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Summary: Pull Request resolved: #2429 X-link: pytorch/pytorch#134118 For some reason exporting D61392607 is just not working, so I'm resubmitting this. This diff implements a bunch of views for internal scuba viewing. TODOS that I might punt to another diff: - Saving cache stats via counter is definitely sus here, but there's not really a good way to track "fx graph cache hit for this compile phase" right now. Will think about this more. - We should definitely log frame id, compile id, etc - We should definitely be logging configs. That way, we can A/B test based on whether a config is turned on. - idk what I'm doing with compile_uuid yet, but it's useful when you want to look at samples for a single run. I think if we had mast job info this field is not needed, but it's nice to be able to drill down to a single run and get its chrome trace view or icicle view, so idk Reviewed By: oulgen Differential Revision: D61603243 fbshipit-source-id: cf467e75ba16365010f34e9e104039246778c8df
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@pytorchbot merge -f 'Landed internally' (Initiating merge automatically since Phabricator Diff has merged, using force because this PR might not pass merge_rules.json but landed internally) |
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Summary: This diff implements a bunch of views for internal scuba viewing. TODOS that I might punt to another diff: - Saving cache stats via counter is definitely sus here, but there's not really a good way to track "fx graph cache hit for this compile phase" right now. Will think about this more. - We should definitely log frame id, compile id, etc - We should definitely be logging configs. That way, we can A/B test based on whether a config is turned on. - idk what I'm doing with compile_uuid yet, but it's useful when you want to look at samples for a single run. I think if we had mast job info this field is not needed, but it's nice to be able to drill down to a single run and get its chrome trace view or icicle view, so idk Test Plan: All of the above views are run with nanogpt benchmark: ``` buck run mode/opt caffe2/benchmarks/dynamo:torchbench -- --training --backend=inductor --only nanogpt --performance ``` Differential Revision: D61603243 Pull Request resolved: pytorch#134118 Approved by: https://github.com/oulgen
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Summary:
This diff implements a bunch of views for internal scuba viewing.
TODOS that I might punt to another diff:
Test Plan:
All of the above views are run with nanogpt benchmark:
Differential Revision: D61603243
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @rec