[fx2trt][quant] Add lowering support for per channel quantization in fx2trt (#64787)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64787
This PR added support for lowering per channel quantization and dequantization operators
in fx2trt, this also extends TensorMeta with extra arguments corresponding to per channel quantized Tensors,
initially I was thinking of adding a qpram that can capture everything, but currently we still have some lowering support
for fbgemm ops (which has scale and zero_point in operator interface). I think we can move everything to qprams
after we deprecate lowering support for fbgemm ops in the future.
Test Plan:
Test for per channel weight:
```
python torch/fx/experimental/fx2trt/example/quantized_resnet_test.py
```
change BC compatibility test expect for TensorMeta
```
python test/test_fx.py TestFXAPIBackwardCompatibility.test_class_member_back_compat --accept
```
Imported from OSS
Reviewed By: jfix71, mrshenli, 842974287
Differential Revision: D30879848
fbshipit-source-id: 76c3804bb1d9343183ae53d9f02c1a3bf6c79e1c
