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Fix the torch.take() wrapper to make axis optional for ndim = 1 #47

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asmeurer merged 1 commit into from
Jul 19, 2023
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Fix the torch.take() wrapper to make axis optional for ndim = 1 #47

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6 changes: 5 additions & 1 deletion array_api_compat/torch/_aliases.py
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Original file line number Diff line number Diff line change
Expand Up @@ -681,7 +681,11 @@ def isdtype(
else:
return dtype == kind

def take(x: array, indices: array, /, *, axis: int, **kwargs) -> array:
def take(x: array, indices: array, /, *, axis: Optional[int] = None, **kwargs) -> array:
if axis is None:
if x.ndim != 1:
raise ValueError("axis must be specified when ndim > 1")
axis = 0

@lezcano lezcano Jul 15, 2023

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Or you can dispatch to torch.take, either should be alright.

@asmeurer asmeurer Jul 15, 2023

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torch.take doesn't support an axis argument.

@lezcano lezcano Jul 15, 2023

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exactly :D torch.take() == numpy.take(axis=None)

@lezcano lezcano Jul 15, 2023

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it's a bit more general, as it sees the whole tensor as a 0dim tensor and indexes into it, so it also works for ndim > 1.

@asmeurer asmeurer Jul 15, 2023

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Right. The flattening behavior is also there in NumPy, but I think we wanted to avoid that with the array API take. I'm not sure to what degree we should try to avoid that for the compat library, though (c.f. #34 (comment))

return torch.index_select(x, axis, indices, **kwargs)

__all__ = ['result_type', 'can_cast', 'permute_dims', 'bitwise_invert', 'add',
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