On Mon, Apr 22, 2019 at 11:13 PM Stephan Hoyer <sho...@gmail.com> wrote: > >> On Mon, Apr 22, 2019 at 9:26 PM Nathaniel Smith <n...@pobox.com> wrote: >>> >>> Your last email didn't really clarify anything for me. I get that >>> np.func.__numpy_implementation__ is intended to have the semantics of >>> numpy's implementation of func, but that doesn't tell me much :-). And >>> also, that's exactly the definition of np.func, isn't it? > > My understanding of the protocol we came up with in NEP-18 is that every > NumPy function (that takes array-like arguments) now has two parts to its > implementation: > 1. The NEP-18 part involving calling the dispatcher function, and checking > for/calling __array_function__ attributes on array-like arguments. This part > is documented in NEP-18. > 2. The original function definition, which is called if either (a) no > __array_function__ attributes exist, or (b) the only __array_function__ > attribute is numpy.ndarray.__array_function__. This part is documented in the > docstring of the NumPy function. > > "__numpy_implementation__" provides a short-cut to (2) without (1). That's it.
OK, so the semantics are: the same as the normal function, except we pretend that none of the arguments have an __array_function__ attribute? That's much clearer to me than how you were phrasing it before :-). Though now the name "__numpy_implementation__" doesn't seem very evocative of what it does... numpy's dispatch sequence has changed a lot in the past (mostly adding new coercion rules), and will probably change in the future, and "__numpy_implementation__" doesn't give much guidance about which parts of the dispatch sequence should be skipped as "dispatch" and which should be included as "implementation". Maybe something like __skipping_array_function__? -n -- Nathaniel J. Smith -- https://vorpus.org _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
