[Numpy-discussion] Preliminary thoughts on implementing __matmul__
Charles R Harris
charlesr.harris at gmail.com
Wed Aug 6 20:00:52 EDT 2014
On Wed, Aug 6, 2014 at 5:51 PM, Nathaniel Smith <njs at pobox.com> wrote:
> On 7 Aug 2014 00:41, "Charles R Harris" <charlesr.harris at gmail.com> wrote:
> >
> > On Wed, Aug 6, 2014 at 5:33 PM, Nathaniel Smith <njs at pobox.com> wrote:
> >>
> >> On Thu, Aug 7, 2014 at 12:24 AM, Charles R Harris
> >> <charlesr.harris at gmail.com> wrote:
> >> >
> >> > On Wed, Aug 6, 2014 at 4:57 PM, Nathaniel Smith <njs at pobox.com>
> wrote:
> >> >>
> >> >> On Wed, Aug 6, 2014 at 4:32 PM, Charles R Harris
> >> >> <charlesr.harris at gmail.com> wrote:
> >> >> > Should also mention that we don't have the ability to operate on
> stacked
> >> >> > vectors because they can't be identified by dimension info. One
> >> >> > workaround
> >> >> > is to add dummy dimensions where needed, another is to add two
> flags,
> >> >> > row
> >> >> > and col, and set them appropriately. Two flags are needed for
> backward
> >> >> > compatibility, i.e., both false is a traditional array.
> >> >>
> >> >> It's possible I could be convinced to like this, but it would take a
> >> >> substantial amount of convincing :-). It seems like a pretty big
> >> >> violation of orthogonality/"one obvious way"/etc. to have two totally
> >> >> different ways of representing row/column vectors.
> >> >>
> >> >
> >> > The '@' operator supports matrix stacks, so it would seem we also
> need to
> >> > support vector stacks. The new addition would only be effective with
> the '@'
> >> > operator. The main problem I see with flags is that adding them would
> >> > require an extensive audit of the C code to make sure they were
> preserved.
> >> > Another option, already supported to a large extent, is to have row
> and col
> >> > classes inheriting from ndarray that add nothing, except for a
> possible new
> >> > transpose type function/method. I did mock up such a class just for
> fun, and
> >> > also added a 'dyad' function. If we really don't care to support
> stacked
> >> > vectors we can get by without adding anything.
> >>
> >> It's possible you could convince me that this is a good idea, but I'm
> >> starting at like -0.95 :-). Wouldn't it be vastly simpler to just have
> >> np.linalg.matvec, matmat, vecvec or something (each of which are
> >> single-liners in terms of @), rather than deal with two different ways
> >> of representing row/column vectors everywhere?
> >>
> >
> > Sure, but matvec and vecvec would not be supported by '@' except when
> vec was 1d because there is no way to distinguish a stack of vectors from a
> matrix or a stack of matrices.
>
> Yes. But @ can never be magic - either people will have to write something
> extra to flip these flags on their array objects, or they'll have to write
> something extra to describe which operation they want. @ was never intended
> to cover every case, just the simple-but-super-common ones that dot covers,
> plus a few more (simple broadcasting). We have np.add even though + exists
> too...
>
I don't expect stacked matrices/vectors to be used often, although there
are some areas that might make heavy use of them, so I think we could live
with the simple implementation, it's just a bit of a wart when there is
broadcasting of arrays. Just to be clear, the '@' broadcasting differs from
the dot broadcasting, agreed?
Chuck
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