pytorch

836b2431 - [quant] Input-Weight Equalization - selective equalization (#61916)

[quant] Input-Weight Equalization - selective equalization (#61916) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/61916 Functions used to run selective equalization based on the SQNR obtained from running the Numeric Suite. After running the Numeric Suite between the equalized and float model, we will get the SQNR between the two models and construct an equalization_qconfig_dict that specifies to only equalize the layers with the highest quantization errors. How to run: ``` layer_to_sqnr_dict = get_layer_sqnr_dict(float_model, equalized_model, input) eq_qconfig_dict = get_equalization_qconfig_dict(layer_to_sqnr_dict, equalized_model, num_layers_to_equalize) prepared = prepare_fx(float_model, qconfig_dict, eq_qconfig_dict) ... ``` Test Plan: `python test/test_quantization.py TestEqualizeFx.test_selective_equalization` Imported from OSS Reviewed By: supriyar Differential Revision: D29796950 fbshipit-source-id: 91f0f8427d751beaea32d8ffc2f3b8aa8ef7ea95