human
Here's a good function header given the following:
I wrote the below code

    def make_composite_space(image_space):
        '\n                                Returns    a    compsite    space    with    a    particular    tree    structure.\n                                '
        return CompositeSpace((CompositeSpace(((image_space,) * 2)), VectorSpace(dim=1)))
    shape = np.array([8, 11])
    channels = 3
    datum_size = (channels * shape.prod())
    composite_topo = make_composite_space(Conv2DSpace(shape=shape, num_channels=channels))
    composite_flat = make_composite_space(VectorSpace(dim=datum_size))
    def make_vector_data(batch_size, space):
        '\n                                Returns    a    batch    of    synthetic    data    appropriate    to    the    provided    space.\n                                Supports    VectorSpaces,    and    CompositeSpaces    of    VectorSpaces.        synthetic\n                                data.\n\n                                '
        if isinstance(space, CompositeSpace):
            return tuple((make_vector_data(batch_size, subspace) for subspace in space.components))
        else:
            assert isinstance(space, VectorSpace)
            result = np.random.rand(batch_size, space.dim)
            if (space.dtype is not None):
                return np.asarray(result, dtype=space.dtype)
            else:
                return result
    batch_size = 5
    flat_data = make_vector_data(batch_size, composite_flat)
    composite_flat.np_validate(flat_data)
    topo_data = composite_flat.np_format_as(flat_data, composite_topo)
    composite_topo.np_validate(topo_data)
    new_flat_data = composite_topo.np_format_as(topo_data, composite_flat)
    def get_shape(batch):
        '\n                                Returns    the    (nested)    shape(s)    of    a    (nested)    batch.\n                                '
        if isinstance(batch, np.ndarray):
            return batch.shape
        else:
            return tuple((get_shape(b) for b in batch))
    def batch_equals(batch_0, batch_1):
        '\n          ...

What's a good function header?
assistant
#Here's a good function header.

def test_np_format_as_composite_composite():