TST/BUG: run all tests on all backends; fix backend-specific bugs#88
TST/BUG: run all tests on all backends; fix backend-specific bugs#88lucascolley merged 2 commits intodata-apis:mainfrom
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| sar = xp.take(ar, order, axis=0) | ||
| if sar.size >= 1: | ||
| ar_size = _compat.size(sar) | ||
| assert ar_size is not None, "xp.unique*() on lazy backends raises" |
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Caveat: this is missing data-apis/array-api-compat#231
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| from .conftest import Library | ||
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| # mypy: disable-error-code=no-untyped-usage |
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The return type of xp.anything is untyped, because xp is a ModuleType
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I looked over everything apart from the changes under tests/ to start off with - seems like a good idea, thanks!
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could you detail how these functions deviate from the ones in scipy._lib._array_api? If we are going to expose these here, it would be good to be able to remove them from SciPy.
Also, consider #17 (comment). But given we have since changed the scope of array-api-extra to include paths specific to known backends, I think they probably are in-scope now.
EDIT: given
Note that I have no plans to use these in scipy, as there are enough extra nuances
there to warrant bespoke variants.
perhaps there is a way to make these extensible for library-specific nuances, to remove code-duplication somewhat?
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- no default_ctx context variable
- no ability to cherry-pick disabling shape, dtype, and/or namespace validation
- no special casing for 0d
All of these features could be catered for here, but I feel they're all severely overdesigned for ensuring the health of array-api-extra.
My goal was to write something that serves well array-api-extra, and as a nice bonus allows other people to use it.
I'm open to making the whole new module private if you'd prefer it that way.
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let's keep it private for now and explain the situation in gh-17. If there are requests for them to be made public in the future, we should reconsider.
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Also, see #72 for my vision of how I would like to include delegation to library-specific implementations more broadly. The testing introduced here should be enough to push that PR over the line too 🎉 |
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Made the functions private. |
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this is fantastic, thanks @crusaderky !
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create_diagonalon JAXkronon JAX, CuPy, and PyTorchpadon JAXin1don PyTorchpublicprivate functionsxp_assert_equalandxp_assert_close.Note that I have no plans to use these in scipy, as there are enough extra nuances
there to warrant bespoke variants.