Implement copysign (#46396)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/46396

Related #38349

[numpy](https://numpy.org/doc/stable/reference/generated/numpy.copysign.html?highlight=copysign#numpy.copysign)
- No in-place function
- No method
- Optional output
- Available: byte, char, bool, int, short, long, float, double, half
- Integral promoted to float
- Not available: float/double complex

`c = np.copysign(a, b)`
|  a |  b |  c | a.grad |
| -1 | -1 | -1 |   1  |
| -0 | -1 | -0 |   0  |
|  0 | -1 | -0 |  0  |
|  1 | -1 | -1 |  -1  |
| -1 | -0 |  -1 |  1  |
| -0 | -0 |  0 |  0  |
|  0 | -0 |  0 |   0  |
|  1 | -0 |  -1 |   -1  |
| -1 |  0 |  1 |  -1  |
| -0 |  0 |  0 |  0  |
|  0 |  0 |  0 |   0  |
|  1 |  0 |  1 |   1  |
| -1 |  1 |  1 |  -1  |
| -0 |  1 |  0 |  0  |
|  0 |  1 |  0 |   0  |
|  1 |  1 |  1 |   1  |

This function becomes **non-differentiable** at `a=0` for any `b`. So, in my opinion, we may set the gradient for `a=0` to 0.

TODO:
- [x] test (cpu/gpu)
- [x] doc
- [x] ~kernel_vec~

Test Plan: Imported from OSS

Reviewed By: mruberry

Differential Revision: D24401366

Pulled By: ejguan

fbshipit-source-id: 3621c5ff74b185376a3705589983bb5197ab896d

torch/_tensor_docs.py

@@ -939,6 +939,19 @@ conj() -> Tensor
 See :func:`torch.conj`
 """)
 
+add_docstr_all('copysign',
+               r"""
+copysign(other) -> Tensor
+
+See :func:`torch.copysign`
+""")
+
+add_docstr_all('copysign_', r"""
+copysign_(other) -> Tensor
+
+In-place version of :meth:`~Tensor.copysign`
+""")
+
 add_docstr_all('cos',
                r"""
 cos() -> Tensor