Add inspector numeric gap calculation between AOT and runtime intermediate outputs #11855
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…diate outputs Summary: This PR introduces a method to calculate the numeric gap between logged intermediate outputs from an exported graph and runtime outputs. The method currently supports MSE and L1 distance metrics for comparison. It maps corresponding intermediate outputs from both stages and computes the numerical gaps, returning the results in a pandas DataFrame. This enhancement aids in identifying discrepancies between AOT intermediate outputs and actual intermediate outputs during runtime. Reviewed By: Gasoonjia Differential Revision: D76831086
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/11855
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 0735510 with merge base 18e4240 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Jun 23, 2025
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Summary: This PR introduces a method to calculate the numeric gap between logged intermediate outputs from an exported graph and runtime outputs. The method currently supports MSE and L1 distance metrics for comparison. It maps corresponding intermediate outputs from both stages and computes the numerical gaps, returning the results in a pandas DataFrame. This enhancement aids in identifying discrepancies between AOT intermediate outputs and actual intermediate outputs during runtime.
Reviewed By: Gasoonjia
Differential Revision: D76831086