`ht.nonzero()` should return tuple of 1-D arrays instead of an n-D array

[ClaudiaComito]

Description
np.nonzero(a) returns a tuple of 1-D ndarrays with length a.ndim. This can be then used directly and without modifications for advanced indexing across dimensions.

>>> a
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])
>>> mask
array([[False,  True,  True],
       [False,  True,  True],
       [False,  True,  True]])
>>> a[mask].shape
(6,)
>>> a[np.nonzero(mask)].shape
(6,)
>>> a[mask] == a[np.nonzero(mask)]
array([ True,  True,  True,  True,  True,  True])

ht.nonzero returns the indices in torch.nonzero format, in the example above it returns a DNDarray with shape (6,2).

This is not what the users expect, and complicates our advanced indexing unnecessarily.

Will be addressed together with #914

Expected behavior
ht.nonzero should return a tuple of 1-D dndarrays, for API consistency and to simplify heat's advanced indexing implementation

Version Info
main

[Mystic-Slice]

@ClaudiaComito Can I try working on this issue?

[ClaudiaComito]

@ClaudiaComito Can I try working on this issue?

@Mystic-Slice good idea, go ahead. What time zone are you in?

[Mystic-Slice]

Thnkx.
I am from Tamilnadu, India (GMT+5.30).
Mind if I ask where you are from?

[ClaudiaComito]

Closed by #937.