Summary:
Some more clarifications for the arguments, including linking to object docs (QConfigMapping, BackendConfig) and adding types
in the doc
Test Plan:
```
cd docs
make html
```
and
visual inspection for the generated docs
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84587
Approved by: https://github.com/vkuzo
Fix use-dict-literal pylint suggestions by changing `dict()` to `{}`. This PR should do the change for every Python file except test/jit/test_list_dict.py, where I think the intent is to test the constructor.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/83718
Approved by: https://github.com/albanD
Summary:
This improves the documentation page for backend_config_dict to render
the configurations in a human readable format, such as
```
{
'pattern': torch.nn.modules.pooling.AdaptiveAvgPool1d,
'dtype_configs': [
{
'input_dtype': torch.quint8,
'output_dtype': torch.quint8,
},
{
'input_dtype': torch.float16,
'weight_dtype': torch.float16,
'bias_dtype': torch.float16,
'output_dtype': torch.float16,
},
],
'observation_type': ObservationType.OUTPUT_SHARE_OBSERVER_WITH_INPUT,
},
```
The results are also now sorted alphabetically by the normalized name of
the root op in the pattern.
A couple of utility functions are created to help with this. If in the future
we convert backend_config_dict to use typed objects, we can move this logic
to the objects at that time.
Test plan:
```
cd docs
make html
cd build
python -m server.http
// renders correctly, example: https://gist.github.com/vkuzo/76adfc7c89e119c59813a733fa2cd56f
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77535
Approved by: https://github.com/andrewor14
Summary:
Following https://github.com/pytorch/rfcs/blob/master/RFC-0019-Extending-PyTorch-Quantization-to-Custom-Backends.md we implemented
the backend configuration for fbgemm/qnnpack backend, currently it was under fx folder, but we'd like to use this for all different
workflows, including eager, fx graph and define by run quantization, this PR moves it to torch.ao.quantization namespace so that
it can be shared by different workflows
Also moves some utility functions specific to fx to fx/backend_config_utils.py and some files are kept in fx folder (quantize_handler.py and fuse_handler.py)
Test Plan:
python test/teset_quantization.py TestQuantizeFx
python test/teset_quantization.py TestQuantizeFxOps
python test/teset_quantization.py TestQuantizeFxModels
python test/test_quantization.py TestAOMigrationQuantization
python test/test_quantization.py TestAOMigrationQuantizationFx
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75823
Approved by: https://github.com/vkuzo
