Add diagflat complex support (#47564)
Summary:
Adds complex numbers support for `torch.diag`
``` python
>>> import torch
>>> a = torch.ones(2, dtype=torch.complex128)
>>> torch.diagflat(a)
tensor([[1.+0.j, 0.+0.j],
[0.+0.j, 1.+0.j]], dtype=torch.complex128)
>>> b = a.cuda()
>>> torch.diagflat(b)
tensor([[1.+0.j, 0.+0.j],
[0.+0.j, 1.+0.j]], device='cuda:0', dtype=torch.complex128)
```
Note that automatic differentiation isn't implemented:
``` python
>>> d = torch.ones(1, dtype=torch.complex128, requires_grad=True)
>>> torch.diagflat(d)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
RuntimeError: diag does not support automatic differentiation for outputs with complex dtype.
```
Fixes https://github.com/pytorch/pytorch/issues/47499
Pull Request resolved: https://github.com/pytorch/pytorch/pull/47564
Reviewed By: heitorschueroff
Differential Revision: D24844467
Pulled By: anjali411
fbshipit-source-id: 9c8cb795d52880b7dcffab0c059b0f6c2e5ef151
