ns for fx: change dtype cast from once per N node to once per node
Summary:
This PR ensures that when we do a dtype cast for a shadow module,
we insert N dtype casts for N nodes, instead of combining N nodes
into a single dtype cast.
An example where this occurs is `cat([x, y], dim=0)`
```
// original graph
[x, y] -> cat_b -> output
// shadow graph with a single dtype cast, before this PR
dtype_cast -> cat_a_shadow -> output_a_shadow
/
[x, y] -> cat_b -> output_b
// shadow graph with multiple dtype casts, after this PR
[dtype_cast_x, dtype_cast_y] -> cat_a_shadow -> output_a_shadow
/
[x, y] -> cat_b -> output_b
```
The reason things worked before this PR is because `torch.dequantize`
can take either a single tensor or a list of tensors. We are changing
this to make an upcoming addition of input loggers easier.
Test Plan:
```
python test/test_quantization.py TestFXNumericSuiteCoreAPIs.test_prepare_model_with_stubs_multiple_dtype_casts
```
Imported from OSS
Differential Revision: D26931226
Reviewed By: hx89
Pulled By: vkuzo
fbshipit-source-id: e9c7d4c7942e0f59c952094d2e446b1e2c838396
