The problem:
- The new CustomOp API depends on torchgen.model
- torchgen.model imports `yaml`
- `yaml` is not a PyTorch runtime dependency
To unblock myself, because I'm not sure how long it'll take to
convince people yaml should be a PyTorch runtime dependency
(unless one of you wants to approve #100166), this PR removes the
yaml dependency from torchgen.model.
It does so by splitting torchgen.utils (the offender) into
torchgen.utils (no yaml) and torchgen.yaml (which uses yaml).
Test Plan:
- CI
Pull Request resolved: https://github.com/pytorch/pytorch/pull/100203
Approved by: https://github.com/ezyang, https://github.com/Skylion007
Preferring dash over underscore in command-line options. Add `--command-arg-name` to the argument parser. The old arguments with underscores `--command_arg_name` are kept for backward compatibility.
Both dashes and underscores are used in the PyTorch codebase. Some argument parsers only have dashes or only have underscores in arguments. For example, the `torchrun` utility for distributed training only accepts underscore arguments (e.g., `--master_port`). The dashes are more common in other command-line tools. And it looks to be the default choice in the Python standard library:
`argparse.BooleanOptionalAction`: 4a9dff0e5a/Lib/argparse.py (L893-L895)
```python
class BooleanOptionalAction(Action):
def __init__(...):
if option_string.startswith('--'):
option_string = '--no-' + option_string[2:]
_option_strings.append(option_string)
```
It adds `--no-argname`, not `--no_argname`. Also typing `_` need to press the shift or the caps-lock key than `-`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94505
Approved by: https://github.com/ezyang, https://github.com/seemethere
Changes:
1. `typing_extensions -> typing-extentions` in dependency. Use dash rather than underline to fit the [PEP 503: Normalized Names](https://peps.python.org/pep-0503/#normalized-names) convention.
```python
import re
def normalize(name):
return re.sub(r"[-_.]+", "-", name).lower()
```
2. Import `Literal`, `Protocal`, and `Final` from standard library as of Python 3.8+
3. Replace `Union[Literal[XXX], Literal[YYY]]` to `Literal[XXX, YYY]`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94490
Approved by: https://github.com/ezyang, https://github.com/albanD
* Reflect required arguments in method signature for each diagnostic rule. Previous design accepts arbitrary sized tuple which is hard to use and prone to error.
* Removed `DiagnosticTool` to keep things compact.
* Removed specifying supported rule set for tool(context) and checking if rule of reported diagnostic falls inside the set, to keep things compact.
* Initial overview markdown file.
* Change `full_description` definition. Now `text` field should not be empty. And its markdown should be stored in `markdown` field.
* Change `message_default_template` to allow only named fields (excluding numeric fields). `field_name` provides clarity on what argument is expected.
* Added `diagnose` api to `torch.onnx._internal.diagnostics`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/87830
Approved by: https://github.com/abock
This PR updates the `tools/onnx/update_default_opset_version.py` script to ensure files are edited correctly to prepare for the opset 17 support in torch.onnx.
- (clean up) Move script to `main()`
- Add an `--skip_build` option to avoid building pytorch if we want to rerun the process due to errors after compilation is done
- Update to edit the correct files now that the onnx files were refactored
Pull Request resolved: https://github.com/pytorch/pytorch/pull/83283
Approved by: https://github.com/thiagocrepaldi, https://github.com/AllenTiTaiWang, https://github.com/abock
Reduce circular dependencies
- Lift constants and flags from `symbolic_helper` to `_constants` and `_globals`
- Standardized constant naming to make it consistant
- Make `utils` strictly dependent on `symbolic_helper`, removing inline imports from symbolic_helper
- Move side effects from `utils` to `_patch_torch`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77142
Approved by: https://github.com/garymm, https://github.com/BowenBao
Summary:
And add a new tool to update it in the future, which follows the policy
of using "latest as of 18 months ago". This policy is meant to balance:
* recent enough to increase the odds of being able to successfully
export
* old enough to increase the odds of exported model being runnable by
different ONNX implementations
Related changes:
* test_models.py: explicitly fix opset_version to 9 rather than relying on default. Caffe2 doesn't support newer versions.
* symbolic_helper.py:
* Remove a misleading comment
* Remove unnecessary check in `_set_opset_version`
* Use a range to define `_onnx_stable_opsets`
* test_pytorch_common.py:
* Rename a variable from min -> max. I think it was a copy-paste error.
* Make skip test messages more informative.
* Remove unused `skipIfONNXShapeInference`. More on that below.
* test_pytorch_onnx_onnxruntime.py:
* Make all the `TestCase` classes explicitly specify opset version.
* Make `test_unsupported_pad` respect `opset_version` by using `run_test`
* Unrelated simplification: make it obvious that all tests run with `onnx_shape_inference=True`. AFAICT this was already the case.
* There was one test that was entirely disabled (test_tolist) because it was asking to be skipped whenever `onnx_shape_inference=True`, but it was always True. I changed the model being tested so as to preserve the intended test coverage but still have the test actually pass.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73898
Reviewed By: msaroufim
Differential Revision: D35264615
Pulled By: malfet
fbshipit-source-id: cda8fbdffe4cc8210d8d96e659e3a9adf1b5f1d2
(cherry picked from commit b5e639e88828d34442282d0b50c977e610a2ba3a)
