Fixes https://github.com/pytorch/pytorch/issues/84365 and more
This PR addresses not only the issue above, but the entire family of issues related to `torch._C.Value.type()` parsing when `scalarType()` or `dtype()` is not available.
This issue exists before `JitScalarType` was introduced, but the new implementation refactored the bug in because the new api `from_name` and `from_dtype` requires parsing `torch._C.Value.type()` to get proper inputs, which is exactly the root cause for this family of bugs.
Therefore `from_name` and `from_dtype` must be called when the implementor knows the `name` and `dtype` without parsing a `torch._C.Value`. To handle the corner cases hidden within `torch._C.Value`, a new `from_value` API was introduced and it should be used in favor of the former ones for most cases. The new API is safer and doesn't require type parsing from user, triggering JIT asserts in the core of pytorch.
Although CI is passing for all tests, please review carefully all symbolics/helpers refactoring to make sure the meaning/intetion of the old call are not changed in the new call
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87245
Approved by: https://github.com/justinchuby, https://github.com/BowenBao
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- Remove the outdated unit test `test_symbolic_opset9.py`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
Enable runtime type checking for all torch.onnx public apis, symbolic functions and most helpers (minus two that does not have a checkable type: `_.JitType` does not exist) by adding the beartype decorator. Fix type annotations to makes unit tests green.
Profile:
export `torchvision.models.alexnet(pretrained=True)`
```
with runtime type checking: 21.314 / 10 passes
without runtime type checking: 20.797 / 10 passes
+ 2.48%
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84091
Approved by: https://github.com/BowenBao, https://github.com/thiagocrepaldi
Enable runtime type checking for all torch.onnx public apis, symbolic functions and most helpers (minus two that does not have a checkable type: `_.JitType` does not exist) by adding the beartype decorator. Fix type annotations to makes unit tests green.
Profile:
export `torchvision.models.alexnet(pretrained=True)`
```
with runtime type checking: 21.314 / 10 passes
without runtime type checking: 20.797 / 10 passes
+ 2.48%
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/84091
Approved by: https://github.com/BowenBao
Re-land #81953
Add `_type_utils` for handling data type conversion among JIT, torch and ONNX.
- Replace dictionary / list indexing with methods in ScalarType
- Breaking: **Remove ScalarType from `symbolic_helper`** and move it to `_type_utils`
- Deprecated: "cast_pytorch_to_onnx", "pytorch_name_to_type", "scalar_name_to_pytorch", "scalar_type_to_onnx", "scalar_type_to_pytorch_type" in `symbolic_helper`
- Deprecate the type mappings and lists. Remove all internal references
- Move _cast_func_template to opset 9 and remove its reference elsewhere (clean up). Added documentation for easy discovery
Why: List / dictionary indexing and lookup are error-prone and convoluted.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82995
Approved by: https://github.com/kit1980
Add `_type_utils` for handling data type conversion among JIT, torch and ONNX.
- Replace dictionary / list indexing with methods in ScalarType
- Breaking: **Remove ScalarType from `symbolic_helper`** and move it to `_type_utils`
- Breaking: **Remove "cast_pytorch_to_onnx", "pytorch_name_to_type", "scalar_name_to_pytorch", "scalar_type_to_onnx", "scalar_type_to_pytorch_type"** from `symbolic_helper`
- Deprecate the type mappings and lists. Remove all internal references
- Move _cast_func_template to opset 9 and remove its reference elsewhere (clean up). Added documentation for easy discovery
Why: List / dictionary indexing and lookup are error-prone and convoluted.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81953
Approved by: https://github.com/AllenTiTaiWang, https://github.com/BowenBao
Cleaning up onnx module imports to prepare for updating `__init__`.
- Simplify importing the `_C` and `_C._onnx` name spaces
- Remove alias of the symbolic_helper module in imports
- Remove any module level function imports. Import modules instead
- Alias `symbilic_opsetx` as `opsetx`
- Fix some docstrings
Requires:
- https://github.com/pytorch/pytorch/pull/77448
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77423
Approved by: https://github.com/BowenBao
