take() implementation
#96
Closed
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
ev-br
reviewed
Mar 30, 2023
| # [[1, 1], [0, 1]], [[1, 0], [0, 0]] | ||
| # >>> torch.unique(torch.as_tensor(x), dim=2) | ||
| # [[1, 1], [1, 0]], [[0, 1], [0, 0]] | ||
| # |
There was a problem hiding this comment.
Is this something we need to fix in our unique?
The Notes section in https://numpy.org/doc/stable/reference/generated/numpy.unique.html is probably relevant, if somewhat obscure.
WDYT @lezcano ?
There was a problem hiding this comment.
(unique against axis gave me a headache so I had left this xfail'd and documented incase you/Mario had an immediate answer 😅)
There was a problem hiding this comment.
Uf. This looks like a bit of a pain to implement. I'd say we don't touch it and leave it xfailed.
|
Rebased and merged in gh-98 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Rudimentary
take()implementations. Passes my Array APItest_takeat least (data-apis/array-api-tests#173, no means comprehensive for NumPy-propers semantics oftake()), and un-xfailing existing tests didn't uncover anything—I imagine however importing more tests we'll find a bug or two for sure though.It's kinda awkward to implement
ndarray.take()given the redundancies of handling the kwargs in_wrapper.take()too (which cannot be used due to circular import), so left it not implemented...Hopefully this is how I should be implementing things now? I really like
@normalizer!