Commit Graph

10 Commits

Author SHA1 Message Date
Evgeni Burovski
dc3d0caab3 BUG: fix np.ndarray.resize under dynamo (#113931)
Make sure ndarray.resize actually works in-place, so that dynamo does the right thing tracking the result.

Fixes #113539

Pull Request resolved: https://github.com/pytorch/pytorch/pull/113931
Approved by: https://github.com/lezcano
2023-11-17 18:12:17 +00:00
lezcano
6ce5de5275 Avoid calling as_tensor twice (#112866)
Sometimes doing so may copy and that's not good. We avoid that by
setting global flags.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/112866
Approved by: https://github.com/kit1980, https://github.com/ev-br
2023-11-07 16:10:59 +00:00
Evgeni Burovski
6a3922d523 BUG: compile np.array(list_of_arrays) (#112711)
Add a shortcut for a sequence of arrays only. This remove a graph break on a common pattern of
`np.array([np.cos(theta), np.sin(theta)])` and its ilk.

This PR is a simpified alternative to https://github.com/pytorch/pytorch/pull/112521 --- it still breaks on mixing arrays and scalars or array_likes (e.g.  `np.array([[1, 2], np.array[3, 4]])`) and instead adds a simple shortcut.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/112711
Approved by: https://github.com/lezcano
2023-11-02 20:18:16 +00:00
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
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
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
b5c90ba7e7 [dynamo] Fix ndarray.__pow__ (#107746)
As per title. Tests in the next PR

Pull Request resolved: https://github.com/pytorch/pytorch/pull/107746
Approved by: https://github.com/ezyang
ghstack dependencies: #107687, #107688, #107710, #107711
2023-08-23 13:55:36 +00:00
lezcano
2fc828312c Support negative indices in ndarray.__getitem__ (#107688)
In this case, we copy, but this is part of the set of divergences
described in https://github.com/Quansight-Labs/numpy_pytorch_interop/issues/73.

This does not work with dynamic shapes, but it's not clear to me what
would be the best fix

Pull Request resolved: https://github.com/pytorch/pytorch/pull/107688
Approved by: https://github.com/ezyang
ghstack dependencies: #107687
2023-08-23 01:21:23 +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