On Fri, Apr 10, 2020 at 5:17 AM Sebastian Berg <sebast...@sipsolutions.net> wrote:
> On Thu, 2020-04-09 at 13:52 +0200, Ralf Gommers wrote: > > On Thu, Apr 9, 2020 at 12:02 AM Sebastian Berg < > > sebast...@sipsolutions.net> > > wrote: > > > <snip> > > > > > > > I think it would be nice to have a separate NEP 37 implementation > > outside > > of NumPy to play with. Unlike __array_function__, I don't think it > > has to > > go into NumPy immediately. This avoids the whole "experimental API" > > issue, > > Fair enough, I have created a hopefully working start here: > > https://github.com/seberg/numpy_dispatch > > (this is not tested much at all yet, so it could be very buggy). > Thanks! > There are a couple of additional features that I added. > > 1. A global opt-in (it is impossible to opt-out once opted in!) > 2. A local opt-in (to guarantee opt-in if global flag is not set) > 3. I added features to allow transitioning:: > > get_array_module(*arrays, modules="numpy", > future_modules=("dask.array", "cupy"), fallback="warn") > > Will give FutureWarning/DeprecationWarning where necessary, in the > above "numpy" is supported, dask and cupy are supported but not > enabled by default. `None` works to say "all modules". > Once the transition is done, just move dask and cupy into `modules` > and remove `fallback=None`. > So future_modules explicitly excludes compatible libraries that are not listed. Why would you want anyone to do that? I don't understand "supported but not enabled", and it looks undesirable to me to special-case any library in this mechanism. Cheers, Ralf 4. If there are FutureWarnings/DeprecationWarnigs the user needs to be > able to opt-in to future behaviour. Opting out can be done by > casting inputs. Opting-in is done using:: > > with future_dispatch_behavior(): > call_library_function() > > Obviously, we may not want these features, but I was curious how we > could provide the tools to allow clean transitions. > > Both context managers should be thread-safe, but I did not test that. > > The best try would probably be cupy and sklearn again, so I will give a > ping on the sklearn PR. To make that easier, I tried to hack a bit of a > "util" to allow testing (please scroll down on the readme on github). > > Best, > > Sebastian > > > > > it would be quite useful to test this with, e.g., CuPy + scikit-learn > > without being stuck with any decisions in a released NumPy version. > > Also > > makes switching on/off very easy for users, just (don't) `pip install > > numpy-array-module`. > > > > Cheers, > > Ralf > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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