Using `@skipifTorchDynamo` is wrong, the correct usage is
`@skipIfTorchDynamo()` or `@skipIfTorchDynamo("msg")`. This would cause
tests to stop existing.
Added an assertion for this and fixed the incorrect callsites.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/117114
Approved by: https://github.com/voznesenskym
Enables some tests that were incorrectly not being run and enables PIE794 globally. This rule checks if a classvar is defined twice as flags it as it is likely a bug. In fact, we found several cases where it was a bug. It does have a couple of false positives which I flagged upstream and replaced with noqas: https://github.com/astral-sh/ruff/issues/8497
Pull Request resolved: https://github.com/pytorch/pytorch/pull/112989
Approved by: https://github.com/malfet
Use conditional imports: when running under dynamo, import the original NumPy not torch._numpy. This is what we want to trace, not our implementation.
With this, the test suite passes with and without `PYTORCH_TEST_WITH_DYNAMO=1` (modulo a couple of test modules which are not meant to be compiled, e.g. `test_nep50_examples`). There are two new decorators, `x{fail,pass}ifTorchDynamo`, the `xpass` in most cases indicates a graph break and a fallback to eager for things we do not implement.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110401
Approved by: https://github.com/lezcano
Fixes#109604
Resubmit gh-109715 + several skips and small fixes to make tests pass.
The main fix here is by @ysiraichi : previously, dynamo did not resume tracing numpy ndarrays after a graph break.
While at it, fix several small issues Yukio's fix uncovers:
- graph break gracefully on numpy dtypes which do not map to torch.dtypes (uint16 etc)
- recognize array scalars in dynamo, treat them as 0D ndarrays
- make sure that iterating over torch.ndarray generates arrays not bare tensors
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110512
Approved by: https://github.com/lezcano
1. Inherit from TestCase
2. Use pytorch parametrization
3. Use unittest.expectedFailure to mark xfails
All this to make pytest-less invocation work:
$ python test/torch_np/test_basic.py
Furthermor, tests can now be run under dynamo, and we see first errors:
```
$ PYTORCH_TEST_WITH_DYNAMO=1 python test/torch_np/test_basic.py -k test_toscalar_list_func
.E.
======================================================================
ERROR: test_toscalar_list_func_<function shape at 0x7f9b83a4fc10>_np_func_<function shape at 0x7f9a8dd38af0> (__main__.TestOneArrToScalar)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/ev-br/repos/pytorch/torch/testing/_internal/common_utils.py", line 356, in instantiated_test
test(self, **param_kwargs)
File "test/torch_np/test_basic.py", line 232, in test_toscalar_list
@parametrize("func, np_func", one_arg_scalar_funcs)
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1519, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1528, in _call_impl
return forward_call(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/_dynamo/eval_frame.py", line 406, in _fn
return fn(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/fx/graph_module.py", line 726, in call_wrapped
return self._wrapped_call(self, *args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/fx/graph_module.py", line 305, in __call__
raise e
File "/home/ev-br/repos/pytorch/torch/fx/graph_module.py", line 292, in __call__
return super(self.cls, obj).__call__(*args, **kwargs) # type: ignore[misc]
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1519, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/ev-br/repos/pytorch/torch/nn/modules/module.py", line 1528, in _call_impl
return forward_call(*args, **kwargs)
File "<eval_with_key>.2", line 5, in forward
shape = torch._numpy._funcs_impl.shape([[1, 2, 3], [4, 5, 6]])
File "/home/ev-br/repos/pytorch/torch/_numpy/_funcs_impl.py", line 655, in shape
return tuple(a.shape)
AttributeError: 'list' object has no attribute 'shape'
----------------------------------------------------------------------
Ran 3 tests in 0.915s
FAILED (errors=1)
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/109593
Approved by: https://github.com/lezcano
- Add `if __name__ == "__main__": run_tests()` stanzas to test files in `torch_np` folder so that these tests run on CI
- Skip / xfail things smoked out by this change
- remove a stray python file which should not have been added to tests in the first place.
- fix einsum if opt_einsum is present
- add skips for older numpies
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108762
Approved by: https://github.com/lezcano
- Add `if __name__ == "__main__": run_tests()` stanzas to test files in `torch_np` folder so that these tests run on CI
- Skip / xfail things smoked out by this change
- remove a stray python file which should not have been added to tests in the first place.
- fix einsum if opt_einsum is present
- add skips for older numpies
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108762
Approved by: https://github.com/lezcano
RFC: https://github.com/pytorch/rfcs/pull/54
First commit is the contents of https://github.com/Quansight-Labs/numpy_pytorch_interop/
We have already been using this in core for the last few months as a external dependency. This PR pulls all these into core.
In the next commits, I do a number of things in this order
- Fix a few small issues
- Make the tests that this PR adds pass
- Bend backwards until lintrunner passes
- Remove the optional dependency on `torch_np` and simply rely on the upstreamed code
- Fix a number dynamo tests that were passing before (they were not tasting anything I think) and are not passing now.
Missing from this PR (but not blocking):
- Have a flag that deactivates tracing NumPy functions and simply breaks. There used to be one but after the merge stopped working and I removed it. @lezcano to investigate.
- https://github.com/pytorch/pytorch/pull/106431#issuecomment-1667079543. @voznesenskym to submit a fix after we merge.
All the tests in `tests/torch_np` take about 75s to run.
This was a work by @ev-br, @rgommers @honno and I. I did not create this PR via ghstack (which would have been convenient) as this is a collaboration, and ghstack doesn't allow for shared contributions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/106211
Approved by: https://github.com/ezyang
