5 Commits

Author	SHA1	Message	Date
Evgeni Burovski	5ed4a423de	WIP / TST: allow testing torch._numpy under Dynamo (#110401) ... 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	2023-10-25 16:02:16 +00:00
Kazuaki Ishizaki	19ce68a45c	Fix typo under torch/_numpy directory (#110782) ... This PR fixes typo of comments in files under torch/_numpy directory. Pull Request resolved: https://github.com/pytorch/pytorch/pull/110782 Approved by: https://github.com/Skylion007	2023-10-07 17:42:35 +00:00
Evgeni Burovski	1f20531939	fall back to eager on NotImplementedError (#107863) ... Follow-up to https://github.com/pytorch/pytorch/pull/107710: Help dynamo fall back to eager when compiling unimplemented numpy constructs: - arrays of strings - (arg){min, max} for complex types - various arguments typed as NotImplemented (`np.ones(4, order="F")` etc) - numpy functions which torch._numpy does not implement To test, run (we do not implement arrays of strings) ``` import torch import numpy as np @torch.compile(fullgraph=False) def fn(): return np.asarray(["L", "U"]) ``` and observe it compiles with fullgraph=False and fails with fullgraph=True Fixes https://github.com/pytorch/pytorch/issues/107970 Pull Request resolved: https://github.com/pytorch/pytorch/pull/107863 Approved by: https://github.com/ezyang, https://github.com/lezcano	2023-09-07 21:22:20 +00:00
lezcano	2a6ef9b04d	[dynamo] Avoid recompilation when the PyTorch function accepts scalars (#108162) ... Before, it would create a 0D tensor with the input, which would incur in a guard and specialisation. It's not clear whether the guard and specialisation is the right behaviour when we create 0D tensors, but that's a story for another day. Pull Request resolved: https://github.com/pytorch/pytorch/pull/108162 Approved by: https://github.com/ev-br, https://github.com/peterbell10	2023-09-01 14:35:42 +00:00
lezcano	a9dca53438	NumPy support in torch.compile (#106211) ... 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	2023-08-11 00:39:32 +00:00