Stephan, good point about use cases. I think its still an odd fit. For example I think np.array_equal(np.zeros((3,3)), np.zeros((2,2))) or np.array_equal([1], ['foo']) would be difficult or impossible to replicate with a potential all_equal gufunc
On Thu, May 31, 2018 at 2:00 PM, Stephan Hoyer <sho...@gmail.com> wrote: > On Wed, May 30, 2018 at 5:01 PM Matthew Harrigan < > harrigan.matt...@gmail.com> wrote: > >> "short-cut to automatically return False if m != n", that seems like a >> silent bug >> > > I guess it depends on the use-cases. This is how np.array_equal() works: > https://docs.scipy.org/doc/numpy/reference/generated/ > numpy.array_equal.html > > We could even imagine incorporating this hypothetical "equality along some > axes with broadcasting" functionality into axis/axes arguments for > array_equal() if we choose this behavior. > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > >
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