[Numpy-discussion] Scipy dot

[Nicolas SCHEFFER]

Well, hinted by what Fabien said, I looked at the C level dot function.
Quite verbose!

But starting line 757, we can see that it shouldn't be too much work
to fix that bug (well there is even a comment there that states just
that)
https://github.com/numpy/numpy/blob/master/numpy/core/blasdot/_dotblas.c#L757
I now think that should be the cleanest.

This would only work for gemm though. I don't know what the benefit is
for gemv for instance, but we should make that kind of changes
everywhere we can.
The evil PyArray_Copy is there twice and that's what we want to get rid of.

I'm not sure, but it looks to me that removing the copy and doing the
following would do the work:
Order = CblasRowMajor;
Trans1 = CblasNoTrans;
Trans2 = CblasNoTrans;
if (!PyArray_ISCONTIGUOUS(ap1)) {
    Trans1 = CblasTrans;
}
if (!PyArray_ISCONTIGUOUS(ap2)) {
    Trans2 = CblasTrans;
}
might be too easy to be true.



On Thu, Nov 8, 2012 at 12:06 PM, Nicolas SCHEFFER
<scheffer.nicolas at gmail.com> wrote:
> I've made the necessary changes to get the proper order for the output array.
> Also, a pass of pep8 and some tests (fixmes are in failing tests)
> http://pastebin.com/M8TfbURi
>
> -n
>
> On Thu, Nov 8, 2012 at 11:38 AM, Nicolas SCHEFFER
> <scheffer.nicolas at gmail.com> wrote:
>> Thanks for all the responses folks. This is indeed a nice problem to solve.
>>
>> Few points:
>> I. Change the order from 'F' to 'C': I'll look into it.
>> II. Integration with scipy / numpy: opinions are diverging here.
>> Let's wait a bit to get more responses on what people think.
>> One thing though: I'd need the same functionality as get_blas_funcs in numpy.
>> Since numpy does not require lapack, what functions can I get?
>> III. Complex arrays
>> I unfortunately don't have enough knowledge here. If someone could
>> propose a fix, that'd be great.
>> IV. C
>> Writing this in C sounds like a good idea. I'm not sure I'd be the
>> right person to this though.
>> V. Patch in numpy
>> I'd love to do that and learn to do it as a byproduct.
>> Let's make sure we agree this can go in numpy first and that all FIXME
>> can be fixed.
>> Although I guess we can resolve fixmes using git.
>>
>> Let me know how you'd like to proceed,
>>
>> Thanks!
>>
>> FIXMEs:
>> - Fix for ndim != 2
>> - Fix for dtype == np.complex*
>> - Fix order of output array
>>
>> On Thu, Nov 8, 2012 at 9:42 AM, Frédéric Bastien <nouiz at nouiz.org> wrote:
>>> Hi,
>>>
>>> I also think it should go into numpy.dot and that the output order should
>>> not be changed.
>>>
>>> A new point, what about the additional overhead for small ndarray? To remove
>>> this, I would suggest to put this code into the C function that do the
>>> actual work (at least, from memory it is a c function, not a python one).
>>>
>>> HTH
>>>
>>> Fred
>>>
>>>
>>>
>>> On Thu, Nov 8, 2012 at 12:29 PM, Anthony Scopatz <scopatz at gmail.com> wrote:
>>>>
>>>> On Thu, Nov 8, 2012 at 7:06 AM, David Cournapeau <cournape at gmail.com>
>>>> wrote:
>>>>>
>>>>> On Thu, Nov 8, 2012 at 12:12 PM, Dag Sverre Seljebotn
>>>>> <d.s.seljebotn at astro.uio.no> wrote:
>>>>> > On 11/08/2012 01:07 PM, Gael Varoquaux wrote:
>>>>> >> On Thu, Nov 08, 2012 at 11:28:21AM +0000, Nathaniel Smith wrote:
>>>>> >>> I think everyone would be very happy to see numpy.dot modified to do
>>>>> >>> this automatically. But adding a scipy.dot IMHO would be fixing
>>>>> >>> things
>>>>> >>> in the wrong place and just create extra confusion.
>>>>> >>
>>>>> >> I am not sure I agree: numpy is often compiled without lapack support,
>>>>> >> as
>>>>> >> it is not necessary. On the other hand scipy is always compiled with
>>>>> >> lapack. Thus this makes more sens in scipy.
>>>>> >
>>>>> > Well, numpy.dot already contains multiple fallback cases for when it is
>>>>> > compiled with BLAS and not. So I'm +1 on just making this an
>>>>> > improvement
>>>>> > on numpy.dot. I don't think there's a time when you would not want to
>>>>> > use this (provided the output order issue is fixed), and it doesn't
>>>>> > make
>>>>> > sense to not have old codes take advantage of the speed improvement.
>>>>>
>>>>> Indeed, there is no reason not to make this available in NumPy.
>>>>>
>>>>> Nicolas, can you prepare a patch for numpy ?
>>>>
>>>>
>>>> +1, I agree, this should be a fix in numpy, not scipy.
>>>>
>>>> Be Well
>>>> Anthony
>>>>
>>>>>
>>>>>
>>>>> David
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>>>>
>>>>
>>>>
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