add torch_np.linalg module #100
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ev-br
commented
Apr 2, 2023
lezcano
previously approved these changes
Apr 3, 2023
torch_np/linalg.py
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| def inv(a: ArrayLike): | ||
| a = _atleast_float_1(a) | ||
| try: | ||
| result = torch.linalg.inv(a) | ||
| except torch._C._LinAlgError as e: | ||
| raise LinAlgError(*e.args) | ||
| return result |
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If we want to do this, let's either do it in its own wrapper (separate from normalizer not to clutter it) and wrap all the functions with it, or let's just never do it. FWIW, all the linalg functions may throw this error if there was an error on the computation.
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If we go down this route, it'll be a great way to also implement the _atelast... behaviour generically looking at the number of inputs of the function that happen to be tensors.
We could also add support for 0-dim inputs generically this way.
lezcano
reviewed
Apr 3, 2023
lezcano
approved these changes
Apr 3, 2023
Added a line to the list at #73 (comment) |
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Implement linalg mappings. This PR does nearly all of linalg (sans einsum). So far this is not completely consistent on
torch._C._LinAlgErrors; we mostly pass the former through and convert the latter