Hi Frédéric, The problem with any environment type variable is that when you disable the dispatch functionality, all other classes that rely on being able to override a numpy function stop working as well, i.e., the behaviour of everything from dask to astropy's Quantity would depend on that setting.
As another alternative, in any call where you *know* that the input is pure ndarray, you can already call `np.<function>.__wrapped__(...)` to call the original code. This is *not* guaranteed to remain in place between versions, but obviously for cases that the speed really matters, one can use it. Personally, though, I think it would make most sense to try to ensure the functions are as fast as possible including the dispatcher check, since that benefits all. My sense is that for quite a number of numpy functions, there is lower hanging fruit... All the best, Marten On Thu, Mar 7, 2019 at 1:25 PM Frederic Bastien <fbast...@nvidia.com> wrote: > I see speed changes vs behavior changes as different category of changes > in my mind. > > I understand that now importing library can slow down NumPy for small > arrays. > But I have the impression you tell this can also give behavior change. > > I do not understand why this could happen. A pure numpy script, that you > just import dask or other library without using them, would just cause a > slowdown. Not a behavior change. > > Behavior change's start to happen only when you start to use the new > library. > > Did I miss something? > > Frédéric > > -----Original Message----- > From: NumPy-Discussion <numpy-discussion-bounces+fbastien= > nvidia....@python.org> On Behalf Of Stefan van der Walt > Sent: Thursday, March 7, 2019 12:15 PM > To: Discussion of Numerical Python <numpy-discussion@python.org> > Cc: Matthew Rocklin <mrock...@gmail.com> > Subject: Re: [Numpy-discussion] NEP-18 comment > > Hi Sebastian, Frederic, > > On Thu, 07 Mar 2019 14:23:10 +0000, Frederic Bastien wrote: > > I like your idea Sebastian. This way it is enabled only when needed and > it is invisible to the user at the same time. > > > > Stefan, does it solve well enough the potential problem you raised? > > I don't think so. This means that NumPy suddenly behaves differently when > dask is imported, which again causes the problem mentioned earlier: > that identical NumPy code could behave differently depending on library > versions, imports, and the environment. > > That said, I think this is a better solution than an environment variable. > > Anyway, my opinion is just one of many: I'd like to hear what the other > developers think. > > Best regards, > Stéfan > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > > ----------------------------------------------------------------------------------- > This email message is for the sole use of the intended recipient(s) and > may contain > confidential information. Any unauthorized review, use, disclosure or > distribution > is prohibited. If you are not the intended recipient, please contact the > sender by > reply email and destroy all copies of the original message. > > ----------------------------------------------------------------------------------- > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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