On Wed, May 22, 2019 at 2:36 PM Ralf Gommers <ralf.gommers@gmail.com> 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 projects that test against numpy master in their CI, and the people that like to live on the bleeding edge by installing master into their environment.
The switch actually has already been done on master for several months now, until for a period in the 1.16 release cycle before we added the off switch. Doing so did turn up a few bugs, e.g., https://github.com/numpy/numpy/issues/12263 We will actually need to re-add in the code that does the environment variable to allow for turning it off, but this isn't a big deal. My main concern is that this adds some complexity for third-party projects in detecting whether __array_function__ is enabled or not. They can't just use the NumPy version and will need to check the environment variable as well, or actually try using it on an example object. 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 assuming that we are OK with adding an underscore attribute to NumPy's namespace semi-indefinitely.
Cheers, Ralf
The "all in" nature of __array_function__ without __skip_array_function__
will both limit its use to cases where it is strongly motivated, and also limits the API implications for NumPy. There is still plenty of room for expanding the protocol, but it's really hard to see what is necessary (and prudent!) without actual use.
[1] e.g., see https://github.com/google/jax/blob/62473351643cecb6c248a50601af163646ba7be6/... [2] https://github.com/numpy/numpy/pull/13305
On Tue, May 21, 2019 at 11:44 PM Juan Nunez-Iglesias <jni.soma@gmail.com> wrote:
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 scikit-image we place a very strong emphasis on code simplicity and readability, so I also share Marten's concerns about code getting too complex. My impression reading the NEP was "whoa, this is hard, I'm glad smarter people than me are working on this, I'm sure it'll get simpler in time". But I haven't seen the simplicity materialise...
On Wed, 22 May 2019, at 11:31 AM, Marten van Kerkwijk wrote:
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 wonder if we shouldn't reconsider the approach, and at least for 1.17 stick with the status quo. Since that seems to be a bigger question than can be usefully addressed in the PR, I thought I would raise it here.
Specifically, now not only does every numpy function have its dispatcher function, but also internally all numpy function calls are being done via the new `__skip_array_function__` attribute, to avoid further overrides. I think both changes make the code significantly less readable, thus, e.g., making it even harder than it is already to attract new contributors.
I think with this it is probably time to step back and check whether the implementation is in fact the right one. For instance, among the alternatives we originally considered was one that had the overridable versions of functions in the regular `numpy` namespace, and the once that would not themselves check in a different one. Alternatively, for some of the benefits provided by `__skip_array_function__`, there was a different suggestion to have a special return value, of `NotImplementedButCoercible`. Might these be better after all?
More generally, I think we're suffering from the fact that several of us seem to have rather different final goals in mind In particular, I'd like to move to a state where as much of the code as possible makes use of the simplest possible implementation, with only a few true base functions, so that all but those simplest functions will generally work on any type of array. Others, however, worry much more about making implementations (even more) part of the API.
All the best,
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