[Numpy-discussion] Should unique types of all arguments be passed on in __array_function__?
Marten van Kerkwijk
m.h.vankerkwijk at gmail.com
Mon Nov 5 09:28:12 EST 2018
Another part of your reply worth considering, though slightly off topic for
the question here, of what to pass on in `types`:
On Sun, Nov 4, 2018 at 7:51 PM Stephan Hoyer <shoyer at gmail.com> wrote:
> On Sun, Nov 4, 2018 at 8:03 AM Marten van Kerkwijk <
> m.h.vankerkwijk at gmail.com> wrote:
>> I thought of this partially as I was wondering how an implementation for
>> ndarray itself would look like. For that, it is definitely useful to know
>> all unique types, since if it is only ndarray, no casting whatsoever needs
>> to be done, while if there are integers, lists, etc, an attempt has to be
>> made to turn these into arrays
> OK, so hypothetically we could invoke versions of each the numpy function
> that doesn't call `as[any]array`, and this would slightly speed-up
> subclasses that call super().__array_function__?
> A longer-term goal that I had in mind here was generally for the
implementations to just be able to assume their arguments are ndarray,
i.e., be free to assume there is a shape, dtype, etc. That is not
specifically useful for subclasses; for pure python code, it might also
mean array mimics could happily use the implementation. But perhaps more
importantly, the code would become substantially cleaner.
Anyway, really a longer-term goal...
All the best,
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