Disallow numeric scalar conversation for non-0D arrays

[vlad-perevezentsev]

This PR partially aligns usm_ndarray scalar conversion semantics with the Python Array API by allowing numeric scalar conversion only for 0D usm_ndarrays

Conversions to Python numeric scalars via int, float, complex and their corresponding methods (__int__, _float__, __complex__) now raise TypeError when applied to usm_ndarrays with ndim !=0

Note:
For full compliance with the Python Array API, the same check should be used for truth values __bool__ method and integer indexing index method
But these changes would impact dpnp compatibility with Numpy 2.4 which currently disallows only numeric scalar conversation (a minor behavioral difference I think)
In addition several dpctl tests rely on implicit truth conversion for non-0D arrays and must be updated accordingly

test_usm_ndarray_indexing.py::test_nonzero_f_contig
test_usm_ndarray_indexing.py::test_nonzero_compacting
test_usm_ndarray_manipulation.py::test_tile_size_1 
test_usm_ndarray_operators.py::test_comp_ops[dpctl.tensor]
test_usm_ndarray_operators.py::test_comp_ops[namespace1]
test_usm_ndarray_sorting.py::test_radix_sort_size_1_axis 
test_usm_ndarray_sorting.py::test_radix_argsort_size_1_axis 

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[github-actions]

View rendered docs @ https://intelpython.github.io/dpctl/pulls/2223/index.html

[github-actions]

Array API standard conformance tests for dpctl=0.22.0dev0=py310h93fe807_103 ran successfully.
Passed: 1114
Failed: 44
Skipped: 82

[coveralls]

coverage: 86.244% (-0.006%) from 86.25%
when pulling 33b2c8d on disallow_conv_to_scalar_ndim
into e041fca on master.

[antonwolfy]

Do we still need to check the size on that case?

[antonwolfy]

In-place modification of ndarray.shape is a pending deprecation based on NumPy changelog.
It is going to be deprecated in NumPy 2.5 release.