4 Commits

Author	SHA1	Message	Date
Aaron Gokaslan	cb856b08b2	[BE]: Attach cause to some exceptions and enable RUFF TRY200 (#111496) ... Did some easy fixes from enabling TRY200. Most of these seem like oversights instead of intentional. The proper way to silence intentional errors is with `from None` to note that you thought about whether it should contain the cause and decided against it. Pull Request resolved: https://github.com/pytorch/pytorch/pull/111496 Approved by: https://github.com/malfet	2023-10-19 21:56:36 +00:00
Evgeni Burovski	48989bc820	trace frames with np.ndarray (#110512) ... 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	2023-10-15 00:56:10 +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	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