[Numpy-discussion] start of an array (tensor) and dataframe API standardization initiative

[Ralf Gommers]

On Thu, Nov 12, 2020 at 1:54 PM Matti Picus <matti.picus at gmail.com> wrote:

>
> On 11/10/20 8:19 PM, Ralf Gommers wrote:
> > Hi all,
> >
> > I'd like to share an update on this topic. The draft array API
> > standard is now ready for wider review:
> >
> > - Blog post: https://data-apis.org/blog/array_api_standard_release
> > <https://data-apis.org/blog/array_api_standard_release/>
> > - Array API standard document:
> > https://data-apis.github.io/array-api/latest/
> > - Repo: https://github.com/data-apis/array-api/
> >
> > It would be great if people - and in particular, NumPy maintainers -
> > could have a look at it and see if that looks sensible from a NumPy
> > perspective and whether the goals and benefits of adopting it are
> > described clearly enough and are compelling.
> >
>
> I think it is compelling for a first version. The test suite and
> benchmark suite will be valuable tools. I hope future versions
> standardize complex numbers as a dtype.


Yes, that's definitely a desire - when implementations are there/ready. At
the moment most libraries have very incomplete support for complex dtypes,
largely because they're not very important for deep learning. Also NumPy's
implementations/choices are shaky in places, and that's being turned up by
the PyTorch effort that's ongoing now to implement complex dtype support in
a NumPy-compatible way.

I realize there is a limit to
> the breadth of the scope of functions to be covered. Is there a page
> that lists them in one place? For instance I tried to look up what the
> standard has to say on issue https://github.com/numpy/numpy/issues/17760
> about using bincount on unt64 arrays. It took me a while to figure out
> that bincount was not in the API (although unique(..., return_counts) is).
>

That's a good idea and still missing, thanks for asking. The test suite
that's in development has a complete list [1]. In the document itself
Sphinx search works, but it should be easier to get a complete overview
perhaps (although it requires some thought - the NumPy docs don't have
everything on one page either).

[1]
https://github.com/data-apis/array-api-tests/tree/master/array_api_tests/function_stubs

Cheers,
Ralf



>
> Matti
>
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