Add boolean mask validation when slicing

[ndgrigorian]

This PR proposes the addition of validation for the shape of masks when slicing tensor.usm_ndarrays and dpnp_arrays.

This aligns with NumPy for specific edge cases, such as:

import dpnp.tensor as dpt

x = dpt.reshape(dpt.arange(3**5, dtype="i4"), (3,) * 5)
ii = dpt.asarray(1)
i0 = dpt.asarray(0, dtype='?')
i1 = dpt.asarray(0, dtype='?')

x[ii, i0[dpt.newaxis], ii, i1[dpt.newaxis], :]

which previously would give usm_ndarray([], dtype=int32), but now raises an error, which aligns with NumPy.

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[github-actions]

View rendered docs @ https://intelpython.github.io/dpnp/pull/2929/index.html

[github-actions]

Array API standard conformance tests for dpnp=0.21.0dev0=py313h509198e_45 ran successfully.
Passed: 1357
Failed: 3
Skipped: 16

[coveralls]

coverage: 78.242% (+0.003%) from 78.239% — resolve-indexing-bugs-with-boolean-masks into master