Follow recommendation on the interaction with numpy.ndarray in binary ops

[antonwolfy]

The PR proposes to follow NEP-13 recommendations on how to interact with numpy.ndarray in binary the operations.

It will set __array_ufunc__ = None which means that dpnp implements Python binary operations freely and so numpy.ufuncs called on this argument will raise TypeError:

a = numpy.ones(10)
b = dpnp.ones(10)
a += b
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[9], line 1
----> 1 a += b

TypeError: operand 'dpnp_array' does not support ufuncs (__array_ufunc__=None)

And an elementwise operation with numpy.ndarray will cause an explicit exception in dpnp:

a + b
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[4], line 1
----> 1 a + b

File ~/code/dpnp/dpnp/dpnp_array.py:518, in dpnp_array.__radd__(self, other)
    516 def __radd__(self, other):
    517     """Return ``value+self``."""
--> 518     return dpnp.add(other, self)

File ~/code/dpnp/dpnp/dpnp_algo/dpnp_elementwise_common.py:314, in DPNPBinaryFunc.__call__(self, x1, x2, out, where, order, dtype, subok, **kwargs)
    303 def __call__(
    304     self,
    305     x1,
   (...)
    312     **kwargs,
    313 ):
--> 314     dpnp.check_supported_arrays_type(
    315         x1, x2, scalar_type=True, all_scalars=False
    316     )
    317     if kwargs:
    318         raise NotImplementedError(
    319             f"Requested function={self.name_} with kwargs={kwargs} "
    320             "isn't currently supported."
    321         )

File ~/code/dpnp/dpnp/dpnp_iface.py:400, in check_supported_arrays_type(scalar_type, all_scalars, *arrays)
    397     if scalar_type and dpnp.isscalar(a):
    398         continue
--> 400     raise TypeError(
    401         f"An array must be any of supported type, but got {type(a)}"
    402     )
    404 if len(arrays) > 0 and not (all_scalars or any_is_array):
    405     raise TypeError(
    406         "At least one input must be of supported array type, "
    407         "but got all scalars."
    408     )

TypeError: An array must be any of supported type, but got <class 'numpy.ndarray'>

Previously it works as in a way:

a = numpy.ones(10)
b = dpnp.ones(10)

a + b
# Out:
# array([array(2.), array(2.), array(2.), array(2.), array(2.), array(2.),
#        array(2.), array(2.), array(2.), array(2.)], dtype=object)

Note, some updates in tests from #2260 have been mapped to that PR.

• Have you provided a meaningful PR description?
• Have you added a test, reproducer or referred to issue with a reproducer?
• Have you tested your changes locally for CPU and GPU devices?
• Have you made sure that new changes do not introduce compiler warnings?
• Have you checked performance impact of proposed changes?
• If this PR is a work in progress, are you filing the PR as a draft?

[coveralls]

coverage: 70.845% (+0.001%) from 70.844%
when pulling ede832e on follow-nep-13
into 7ce5219 on master.

[vlad-perevezentsev]

LGTM!
Thank you @antonwolfy

[github-actions]

Array API standard conformance tests for dpnp=0.17.0dev4=py312he4f9c94_17 ran successfully.
Passed: 950
Failed: 0
Skipped: 50