[Numpy-discussion] NEP: array API standard adoption (NEP 47)

[Ralf Gommers]

On Mon, Feb 22, 2021 at 7:49 PM Sebastian Berg <sebastian at sipsolutions.net>
wrote:

> On Sun, 2021-02-21 at 17:30 +0100, Ralf Gommers wrote:
> > Hi all,
> >
> > Here is a NEP, written together with Stephan Hoyer and Aaron Meurer,
> > for
> > discussion on adoption of the array API standard (
> > https://data-apis.github.io/array-api/latest/). This will add a new
> > numpy.array_api submodule containing that standardized API. The main
> > purpose of this API is to be able to write code that is portable to
> > other
> > array/tensor libraries like CuPy, PyTorch, JAX, TensorFlow, Dask, and
> > MXNet.
> >
> > We expect this NEP to remain in draft state for quite a while, while
> > we're
> > gaining experience with using it in downstream libraries, discuss
> > adding it
> > to other array libraries, and finishing some of the loose ends (e.g.,
> > specifications for linear algebra functions that aren't merged yet,
> > see
> > https://github.com/data-apis/array-api/pulls) in the API standard
> > itself.
>
>
> There is too much to unpack in a day, I hope I did not miss something
> particularly important while reading.
> Do you have plans to try some of this outside of NumPy, or maybe make a
> repo in the numpy org for it?
>

Sorry, I forgot to answer this question. That is what we're doing now, the
current prototype is at
https://github.com/data-apis/numpy/tree/array-api/numpy/_array_api. I do
expect that as soon we need any changes in C code, that becomes
impractical. I think merging as a private submodule (numpy._array_api)
makes sense. That will help with WIP PRs to other libraries - then we can
use the "test against master" CI for that, rather than having to make a
mess injecting things inside CI.

Also, there are a few parts of the NEP that are improvements outside of the
new submodule. Not only DLPack, but also consistency in "stacks of
matrices" in linalg functions, adding a missing keepdims keyword, the
never-copy mode for asarray, and improving the API for inspecting dtype
families (https://github.com/numpy/numpy/issues/17325). Those things can
all be pushed forward.

Cheers,
Ralf
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://mail.python.org/pipermail/numpy-discussion/attachments/20210223/3dbcafc2/attachment-0001.html>