pytorch

6a7ed56d - [ao] Added OutlierDetector observer insert implementation (#80880)

[ao] Added OutlierDetector observer insert implementation (#80880) Summary: This adds the implementation for observer insertion point selection for the OutlierDetector. For this detector, the insertion points are to insert a ModelReportObserver before any leaf level module to study the distribution of data that passes into the module to detect outliers. This commit contains the implementation of the observer insertion as well as the relavent test case. Some code from the InputWeightEqualization was abstracted and made more modular so the same helper function could be used for multiple outlier class tests. As a part of the work for this, there was testing done to determine what a good default ratio threshold and reference percentile would be, and the work to determine this (based on a normal distribution) was then analyzed to find good paramters. We still want to keep thresholds and reference percentile as something the user can input because these were based on a normal distribution, and it can definately vary depending on the type of data a user has. Test Plan: python test/test_quantization.py TestFxDetectOutliers Reviewers: Subscribers: Tasks: Tags: Pull Request resolved: https://github.com/pytorch/pytorch/pull/80880 Approved by: https://github.com/andrewor14