Add specification for computing the matrix product (linalg: matmul) #134
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Should we require that 0-dimensional arrays give an error? Note that the PEP says they should. |
rgommers
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Mar 2, 2021
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@asmeurer Thanks for the suggestion. I have documented the exceptions in accordance with the PEP (0d) and NumPy (nd). |
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Latest merge resolves build failures. CI is now passing. |
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This PR has been open for some time without comment and has been discussed/approved during meetings. Will merge, and we can submit follow-up PRs should any issues/concerns arise. |
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This PR
Notes
NumPy supports
gufunckeyword arguments:out,casting,dtype,subok,order, etc.NumPy, CuPy, Torch, MXNet support providing an output array.
JAX supports specifying a
precisionkeyword argument.TF supports various keywords for transposing array arguments (
transpose_a,transpose_b), conjugating array arguments (adjoint_a,adjoint_b), and indicating whether an array argument is sparse (a_is_sparse,b_is_sparse). TF is alone in supporting these arguments.This PR follows PEP 465 and the semantics of the built-in
@operator.