Summary: Until we add quant_{min, max} args to `torch.quantize_per_{channel, tensor}`, this patch will make sure we will honor observer's restrictions on quantized values.
Test Plan: Added new tests, run with - `buck run caffe2/test:quantization -- quantization.core.test_utils`
Differential Revision: D38624119
Pull Request resolved: https://github.com/pytorch/pytorch/pull/83438
Approved by: https://github.com/andrewor14
Summary:
After https://github.com/pytorch/pytorch/pull/77608 `example_inputs` is required input for `prepare_fx` and `prepare_qat_fx`.
This makes quantizing submodules harder, so we added this utility function to get a dictionary from fqn to submodule example_inputs
Example Call:
```
example_inputs = (tensor0,)
get_fqn_to_example_inputs(m, example_inputs)
```
Example output:
```
{
"linear1": (tensor1,),
"linear2": (tensor2,),
"sub": (tensor3,),
"sub.linear1": (tensor4,),
...
}
```
Test Plan:
python test/test_quantization.py TestUtils
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78286
Approved by: https://github.com/dzdang
Summary:
After https://github.com/pytorch/pytorch/pull/77608 `example_inputs` is required input for `prepare_fx` and `prepare_qat_fx`.
This makes quantizing submodules harder, so we added this utility function to get a dictionary from fqn to submodule example_inputs
Example Call:
```
example_inputs = (tensor0,)
get_fqn_to_example_inputs(m, example_inputs)
```
Example output:
```
{
"linear1": (tensor1,),
"linear2": (tensor2,),
"sub": (tensor3,),
"sub.linear1": (tensor4,),
...
}
```
Test Plan:
python test/test_quantization.py TestUtils
Reviewers:
Subscribers:
Tasks:
Tags:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78146
Approved by: https://github.com/vkuzo
