Refactor torchscript based exporter logic to move them to a single (private) location for better code management. Original public module and method apis are preserved.
- Updated module paths in `torch/csrc/autograd/python_function.cpp` accordingly
- Removed `check_onnx_broadcast` from `torch/autograd/_functions/utils.py` because it is private&unused
@albanD / @soulitzer could you review changes in `torch/csrc/autograd/python_function.cpp` and
`torch/autograd/_functions/utils.py`? Thanks!
## BC Breaking
- **Deprecated members in `torch.onnx.verification` are removed**
Differential Revision: [D81236421](https://our.internmc.facebook.com/intern/diff/D81236421)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/161323
Approved by: https://github.com/titaiwangms, https://github.com/angelayi
beartype has served us well in identifying type errors and ensuring we call internal functions with the correct arguments (thanks!). However, the value of having beartype is diminished because of the following:
1. When beartype improves support for better Dict[] type checking, it discovered typing mistakes in some functions that were previously uncaught. This caused the exporter to fail with newer versions beartype when it used to succeed. Since we cannot fix PyTorch and release a new version just because of this, it creates confusion for users that have beartype in their environment from using torch.onnx
2. beartype adds an additional call line in the traceback, which makes the already thick dynamo stack even larger, affecting readability when users diagnose errors with the traceback.
3. Since the typing annotations need to be evaluated, we cannot use new syntaxes like `|` because we need to maintain compatibility with Python 3.8. We don't want to wait for PyTorch take py310 as the lowest supported Python before using the new typing syntaxes.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130484
Approved by: https://github.com/titaiwangms
beartype has served us well in identifying type errors and ensuring we call internal functions with the correct arguments (thanks!). However, the value of having beartype is diminished because of the following:
1. When beartype improves support for better Dict[] type checking, it discovered typing mistakes in some functions that were previously uncaught. This caused the exporter to fail with newer versions beartype when it used to succeed. Since we cannot fix PyTorch and release a new version just because of this, it creates confusion for users that have beartype in their environment from using torch.onnx
2. beartype adds an additional call line in the traceback, which makes the already thick dynamo stack even larger, affecting readability when users diagnose errors with the traceback.
3. Since the typing annotations need to be evaluated, we cannot use new syntaxes like `|` because we need to maintain compatibility with Python 3.8. We don't want to wait for PyTorch take py310 as the lowest supported Python before using the new typing syntaxes.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130484
Approved by: https://github.com/titaiwangms
beartype has served us well in identifying type errors and ensuring we call internal functions with the correct arguments (thanks!). However, the value of having beartype is diminished because of the following:
1. When beartype improves support for better Dict[] type checking, it discovered typing mistakes in some functions that were previously uncaught. This caused the exporter to fail with newer versions beartype when it used to succeed. Since we cannot fix PyTorch and release a new version just because of this, it creates confusion for users that have beartype in their environment from using torch.onnx
2. beartype adds an additional call line in the traceback, which makes the already thick dynamo stack even larger, affecting readability when users diagnose errors with the traceback.
3. Since the typing annotations need to be evaluated, we cannot use new syntaxes like `|` because we need to maintain compatibility with Python 3.8. We don't want to wait for PyTorch take py310 as the lowest supported Python before using the new typing syntaxes.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/130484
Approved by: https://github.com/titaiwangms
This is the 4th PR in the series of #83787. It enables the use of `@onnx_symbolic` across `torch.onnx`.
- **Backward breaking**: Removed some symbolic functions from `__all__` because of the use of `@onnx_symbolic` for registering the same function on multiple aten names.
- Decorate all symbolic functions with `@onnx_symbolic`
- Move Quantized and Prim ops out from classes to functions defined in the modules. Eliminate the need for `isfunction` checking, speeding up the registration process by 60%.
- Remove the outdated unit test `test_symbolic_opset9.py`
- Symbolic function registration moved from the first call to `_run_symbolic_function` to init time.
- Registration is fast:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84448
Approved by: https://github.com/AllenTiTaiWang, https://github.com/BowenBao
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69550
Fix the wiki URL.
Also minor reorganization in onnx.rst.
Test Plan: Imported from OSS
Reviewed By: msaroufim
Differential Revision: D32994269
Pulled By: malfet
fbshipit-source-id: 112acfe8b7c778d7e3c2cef684023fdaf2c6ec9c
(cherry picked from commit f0787fabde)
Fix the wiki URL.
Also minor reorganization in onnx.rst.
[ONNX] restore documentation of public functions (#69623)
The build-docs check requires all public functions to be documented.
These should really not be public, but we'll fix that later.'
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71609
