Handle aten.to at submodule boundaries #153972
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/153972
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 76cfb7c with merge base bee93f9 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Summary: Pull Request resolved: #153972 #buildall Test Plan: CI Reviewed By: SherlockNoMad, avikchaudhuri Differential Revision: D74582970
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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 |
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Summary: #buildall Test Plan: CI Differential Revision: D74582970 When we decompose to inference IR, aten.to can sometimes disappear. As a result, export module call graph tree will start containing dead nodes because previous provenance tracking is insufficient. This PR fixes that. The caveat is that this won't work in general for tensor subclass inputs to submodule that user wants to preserve signature because we always desugar the tensor subclass into constituent tensors in inference IR making it impossible to preserve the original calling convention. Pull Request resolved: pytorch#153972 Approved by: https://github.com/avikchaudhuri
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Summary: #buildall
Test Plan: CI
Differential Revision: D74582970
When we decompose to inference IR, aten.to can sometimes disappear. As a result, export module call graph tree will start containing dead nodes because previous provenance tracking is insufficient. This PR fixes that. The caveat is that this won't work in general for tensor subclass inputs to submodule that user wants to preserve signature because we always desugar the tensor subclass into constituent tensors in inference IR making it impossible to preserve the original calling convention.
cc @ezyang @SherlockNoMad @EikanWang @jgong5 @wenzhe-nrv