pytorch

6e22b600 - [MLF] Allow for computing prune quantile thresholds on absolute value of indicators in distributed-inference-compatible embedding LUT pruning (#46789)

[MLF] Allow for computing prune quantile thresholds on absolute value of indicators in distributed-inference-compatible embedding LUT pruning (#46789) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/46789 1. Now `SelfBinningHistogram` can calculate the binning histogram using the absolute values from the given an array of values. 2. Update the invocation of `SelfBinningHistogram` in `post_training_prune`. Test Plan: 1. [buck test caffe2/caffe2/python/operator_test:self_binning_histogram_test](https://www.internalfb.com/intern/testinfra/testconsole/testrun/6473924488326108/) 2. [buck test dper3/dper3_backend/delivery/tests:post_training_prune_test](https://www.internalfb.com/intern/testinfra/testconsole/testrun/2251799854023163/) Reviewed By: hwangjeff Differential Revision: D24494097 fbshipit-source-id: 95e47137b25746e686ef9baa9409560af5d58fc1