Add `torch` exception for `sort` to math's `single_dispatch.py`.

Feature details

Update handling of sort in qml.math such that the return values are the same across all interfaces.

The current behaviour is as follows. For numpy, jax, and tf,

>>> a = np.array([1, 3, 4, 2])
>>> qml.math.sort(a)
tensor([1, 2, 3, 4], requires_grad=True)

But for torch, the argument indices are also returned:

>>> a = torch.tensor([1, 3, 4, 2])
>>> qml.math.sort(a)
torch.return_types.sort(
values=tensor([1, 2, 3, 4]),
indices=tensor([0, 3, 1, 2]))

Implementation

It should be possible to just add a custom implementation in math/single_dispatch.py and then register the new function. For example (taken from the current implementation of _take_torch):

def _sort_torch(tensor):
    # Do the sort 
    # return only the sorted array 

ar.register_function("torch", "sort", _sort_torch)

How important would you say this feature is?

1: Not important. Would be nice to have.

Additional information

No response

[RubidgeCarrie]

Hi @glassnotes I am new to the open source community and wanted to ask if it is alright if I try this as my first issue?

[glassnotes]

Great thanks @RubidgeCarrie , we’ll give that a review as soon as possible!