Written with Stephan Hoyer after discussion with Stefan Van der Walt,
Charles Harris, Matti Picus, and Jaime Frio

mrocklin changed the title ~~Add first draft of NEP 0016: array function protocol~~ NEP: Array function protocol


		.. code-block:: python

		def __array_function__(self, func, types, args, *kwargs)

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		.. code:: python

		def broadcast_to(array, shape, subok=False):
		success, value = do_array_function_dance(

		2. Are all arguments of a type that we know how to handle?

		If these conditions hold, ``__array_function__`` should return
		implementation for ``func(args, *kwargs)``. Otherwise, it should

		``__array_function__`` attribute on those inputs, and call those
		methods appropriately until one succeeds.

		This is one additional function of moderate complexity.

		.. code:: python

		def broadcast_to(array, shape, subok=False):
		success, value = do_array_function_dance(

		(Autograd, Tangent), higher order array factorizations (TensorLy), etc.
		that add additional functionality on top of the Numpy API.

		We would like to be able to use these libraries together, for example we

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		``__array_function__``.

		This protocol is intended to be a catch-all for NumPy functionality that
		is not covered by existing protocols, like reductions (like ``np.sum``)

		would only include these as keyword arguments when they have changed
		from default values. This is similar to `what NumPy already has
		done <https://github.com/numpy/numpy/blob/v1.14.2/numpy/core/fromnumeric.py#L1865-L1867>`__,
		e.g., for the optional ``keepdims`` argument in ``sum``:

		.. code:: python

		def broadcast_to(array, shape, subok=False):
		success, value = do_array_function_dance(

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