MHA: Fix regression and apply bias flag to both in/out proj (#52537)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/52257
## Background
Reverts MHA behavior for `bias` flag to that of v1.5: flag enables or disables both in and out projection biases.
Updates type annotations for both in and out projections biases from `Tensor` to `Optional[Tensor]` for `torch.jit.script` usage.
Note: With this change, `_LinearWithBias` defined in `torch/nn/modules/linear.py` is no longer utilized. Completely removing it would require updates to quantization logic in the following files:
```
test/quantization/test_quantized_module.py
torch/nn/quantizable/modules/activation.py
torch/nn/quantized/dynamic/modules/linear.py
torch/nn/quantized/modules/linear.py
torch/quantization/quantization_mappings.py
```
This PR takes a conservative initial approach and leaves these files unchanged.
**Is it safe to fully remove `_LinearWithBias`?**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52537
Test Plan:
```
python test/test_nn.py TestNN.test_multihead_attn_no_bias
```
## BC-Breaking Note
In v1.6, the behavior of `MultiheadAttention`'s `bias` flag was incorrectly changed to affect only the in projection layer. That is, setting `bias=False` would fail to disable the bias for the out projection layer. This regression has been fixed, and the `bias` flag now correctly applies to both the in and out projection layers.
Reviewed By: bdhirsh
Differential Revision: D26583639
Pulled By: jbschlosser
fbshipit-source-id: b805f3a052628efb28b89377a41e06f71747ac5b
