On Wed, 2019-05-22 at 08:52 -0700, Stephan Hoyer wrote:
> Thanks for raising these concerns.
> The full implications of my recent __skip_array_function__ proposal
> are only now becoming evident to me now, looking at it's use in GH-
> 13585. Guaranteeing that it does not expand NumPy's API surface
On Thu, 2019-05-23 at 10:19 -0700, Stephan Hoyer wrote:
> On Thu, May 23, 2019 at 2:43 AM Ralf Gommers
> wrote:
> > On Thu, May 23, 2019 at 3:02 AM Marten van Kerkwijk <
> > m.h.vankerkw...@gmail.com> wrote:
> > > > If we want to keep an "off" switch we might want to add some
> > > > sort of API f
On Thu, May 23, 2019 at 2:43 AM Ralf Gommers wrote:
>
>
> On Thu, May 23, 2019 at 3:02 AM Marten van Kerkwijk <
> m.h.vankerkw...@gmail.com> wrote:
>
>>
>> If we want to keep an "off" switch we might want to add some sort of API
>>> for exposing whether NumPy is using __array_function__ or not. M
On Thu, May 23, 2019 at 3:02 AM Marten van Kerkwijk <
m.h.vankerkw...@gmail.com> wrote:
>
> If we want to keep an "off" switch we might want to add some sort of API
>> for exposing whether NumPy is using __array_function__ or not. Maybe
>> numpy.__experimental_array_function_enabled__ = True, so y
> If we want to keep an "off" switch we might want to add some sort of API
> for exposing whether NumPy is using __array_function__ or not. Maybe
> numpy.__experimental_array_function_enabled__ = True, so you can just test
> `hasattr(numpy, '__experimental_array_function_enabled__')`? This is
> ass
On Wed, May 22, 2019 at 2:36 PM Ralf Gommers wrote:
> I would still like to turn on __array_function__ in NumPy 1.17. At least,
>>> let's try that for the release candidate and see how it goes.
>>>
>>
> I agree. I'd actually suggest flipping the switch asap and see if it
> causes any issues for p
On Wed, May 22, 2019 at 9:46 PM Marten van Kerkwijk <
m.h.vankerkw...@gmail.com> wrote:
> Hi Stephan,
>
> I'm quite happy with the idea of turning on __array_function__ but
> postponing any formal solution to getting into the wrapped routines (i.e.,
> one can use __wrapped__, but it is an implemen
Hi Stephan,
I'm quite happy with the idea of turning on __array_function__ but
postponing any formal solution to getting into the wrapped routines (i.e.,
one can use __wrapped__, but it is an implementation detail that is not
documented and comes with absolutely no guarantees).
That way, 1.17 wil
Thanks for raising these concerns.
The full implications of my recent __skip_array_function__ proposal are
only now becoming evident to me now, looking at it's use in GH-13585.
Guaranteeing that it does not expand NumPy's API surface seems hard to
achieve without pervasive use of __skip_array_func
I just want to express my general support for Marten's concerns. As an
"interested observer", I've been meaning to give `__array_function__` a try but
haven't had the chance yet. So from my anecdotal experience I expect that more
people need to play with this before setting the API in stone.
At
Hi All,
For 1.17, there has been a big effort, especially by Stephan, to make
__array_function__ sufficiently usable that it can be exposed. I think this
is great, and still like the idea very much, but its impact on the numpy
code base has gotten so big in the most recent PR (gh-13585) that I won
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