quant: add QAT fused Linear-Bn1d [1/x]: prepared module (#72431)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72431
Adds support for a fused QAT observed module for `Linear` followed by
`BatchNorm1d`. In this PR, only the support for prepared module with
fake_quants in the right places is added.
A future PR will add support for `convert`, and tests for eager and FX
graph mode workflows.
Similar to conv-bn, we rescale the weight before applying the fake
quant, and undo the rescaling after the linear operation.
Test Plan:
```
python test/test_quantization.py TestQuantizeEagerQATNumerics.test_linear_bn
```
Imported from OSS
Reviewed By: jerryzh168, raghuramank10000
Differential Revision: D34044427
fbshipit-source-id: 47a519173939ca4824d2c6e6ea7a599764a8ed10
(cherry picked from commit bfc75fe0785e12b0fcc45d58bb04b6da347c1767)
