`insert_quant_dequant` pass support shared class types (#31408)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31408
We'll error out when a graph is quantized with different QSchemes.
This only occurs when we have two modules that have same types (e.g. two Conv2d modules initialized with
same arguments) and quantized with two configs that would produce different quantized graphs, for example
per tensor affine and per channel affine. This is a rare case, so it should be OK to skip for now.
Actual support will come later.
Test Plan:
test_jit.py, test_quantization.py
Imported from OSS
Differential Revision: D19162366
fbshipit-source-id: 798f06d0ddef0c8458237ce88b62159cc77eec8b
