[Numpy-discussion] Proposal: Chaining np.dot with mdot helper function
stefan.otte at gmail.com
Thu Feb 20 13:35:24 EST 2014
I quickly hacked together a prototype of the optimization step:
I think there is still room for improvements so feedback is welcome :)
I'll probably have some time to code on the weekend.
@Nathaniel, I'm still not sure about integrating it in dot. Don't a
lot of people use the optional out parameter of dot?
On Thu, Feb 20, 2014 at 4:02 PM, Nathaniel Smith <njs at pobox.com> wrote:
> If you send a patch that deprecates dot's current behaviour for ndim>2,
> we'll probably merge it. (We'd like it to function like you suggest, for
> consistency with other gufuncs. But to get there we have to deprecate the
> current behaviour first.)
> While I'm wishing for things I'll also mention that it would be really neat
> if binary gufuncs would have a .outer method like regular ufuncs do, so
> anyone currently using ndim>2 dot could just switch to that. But that's a
> lot more work than just deprecating something :-).
> On 20 Feb 2014 09:27, "Eric Moore" <ewm at redtetrahedron.org> wrote:
>> On Thursday, February 20, 2014, Eelco Hoogendoorn
>> <hoogendoorn.eelco at gmail.com> wrote:
>>> If the standard semantics are not affected, and the most common
>>> two-argument scenario does not take more than a single if-statement
>>> overhead, I don't see why it couldn't be a replacement for the existing
>>> np.dot; but others mileage may vary.
>>> On Thu, Feb 20, 2014 at 11:34 AM, Stefan Otte <stefan.otte at gmail.com>
>>>> so I propose the following. I'll implement a new function `mdot`.
>>>> Incorporating the changes in `dot` are unlikely. Later, one can still
>>>> the features in `dot` if desired.
>>>> `mdot` will have a default parameter `optimize`. If `optimize==True`
>>>> reordering of the multiplication is done. Otherwise it simply chains
>>>> I'll test and benchmark my implementation and create a pull request.
>>>> NumPy-Discussion mailing list
>>>> NumPy-Discussion at scipy.org
>> Another consideration here is that we need a better way to work with
>> stacked matrices such as np.linalg handles now. Ie I want to compute the
>> matrix product of two (k, n, n) arrays producing a (k,n,n) result. Near as
>> I can tell there isn't a way to do this right now that doesn't involve an
>> explicit loop. Since dot will return a (k, n, k, n) result. Yes this output
>> contains what I want but it also computes a lot of things that I don't want
>> It would also be nice to be able to do a matrix product reduction, (k, n,
>> n) -> (n, n) in a single line too.
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