quant layer/group/instance norm: make weights and biases optional (#39203)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39203
Adds logic and test coverage for optional weights and biases for
the quantized normalization operators. This was broken before this
PR because the `TORCH_LIBRARY` registration had these as required parameters
- removed it, and cleaned up the callsites.
Note: consolidating the registrations in `native_functions.yaml` as opposed to `library.cpp`
after a discussion with ezyang .
Test Plan:
```
python test/test_quantization.py TestQuantizedOps.test_qlayer_norm
python test/test_quantization.py TestQuantizedOps.test_group_norm
python test/test_quantization.py TestQuantizedOps.test_instance_norm
python test/test_quantization.py TestStaticQuantizedModule.test_layer_norm
python test/test_quantization.py TestStaticQuantizedModule.test_group_norm
python test/test_quantization.py TestStaticQuantizedModule.test_instance_norm
python test/test_quantization.py TestQuantizeScriptPTSQOps.test_layer_norm
python test/test_quantization.py TestQuantizeScriptPTSQOps.test_group_norm
python test/test_quantization.py TestQuantizeScriptPTSQOps.test_instance_norm
```
Imported from OSS
Differential Revision: D21885259
fbshipit-source-id: 978c7b8bd6c11a03e9e5fdb68f154cb80cc43599
