[Numpy-discussion] matmul needs some clarification.
shoyer at gmail.com
Wed Jun 3 16:25:57 EDT 2015
On Sat, May 30, 2015 at 3:23 PM, Charles R Harris <charlesr.harris at gmail.com
> The problem arises when multiplying a stack of matrices times a vector.
> PEP465 defines this as appending a '1' to the dimensions of the vector and
> doing the defined stacked matrix multiply, then removing the last dimension
> from the result. Note that in the middle step we have a stack of matrices
> and after removing the last dimension we will still have a stack of
> matrices. What we want is a stack of vectors, but we can't have those with
> our conventions. This makes the result somewhat unexpected. How should we
> resolve this?
I'm afraid I don't quite understand the issue. Maybe a more specific
example of the shapes you have in mind would help? Here's my attempt.
Suppose we have two arrays:
a with shape (i, j, k)
b with shape (k,)
Following the logic you describe from PEP465, for a @ b we have shapes
transform like so:
(i, j, k,) @ (k, 1) -> (i, j, 1) -> (i, j)
This makes sense to me as a stack of vectors, as long as you are imagining
the original stack of matrices as along the first dimension. Which I'll
note is the default behavior for the new np.stack (
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