[MPS] Fix embedding backward with scalar index (#82809)
### Description
Previously the embedding backward always expands `-1` dim to indices, resulting in the following error when the indices is a scalar:
```
error: Rank of data array must equal number of outer dimensions in indices array + rank of slice to update, 2 != 1 + 0
-:8:10: note: see current operation: %5 = "mps.scatter_nd"(%0, %arg1, %4) {batch_dims = 0 : ui32, mode = 0 : i32} : (tensor<10x5xf16>,
```
Now makes it conditional.
Reproducer:
```python
def repro():
w = torch.tensor([[-2.6465, 2.5859, 0.4688, 1.7949, 3.2676],
[-3.1641, 8.9375, 5.7578, -2.9453, -6.5469],
[ 2.0469, 1.3516, -8.7344, 6.0000, 1.3906],
[ 6.5781, 7.8438, 6.9766, 3.2891, -5.1172],
[-7.9414, 7.7344, 4.1875, 2.8574, 2.9531],
[-0.4844, -5.6328, -6.8359, -4.5156, 3.7891],
[ 4.9375, 6.6094, 6.7031, 0.6719, -6.4219],
[ 7.0469, 8.2031, 4.4453, 1.7129, -2.4688],
[ 1.2207, -3.3750, -2.4531, 7.4062, -6.0469],
[-8.9688, 2.2656, 2.4160, -1.0176, 8.4531]], dtype=torch.float32, requires_grad=True)
x = torch.tensor(5)
out = torch.nn.functional.embedding(x, w)
out.sum().backward()
w_mps = w.detach().clone().to("mps").requires_grad_()
x_mps = x.to("mps")
out = torch.nn.functional.embedding(x_mps, w_mps)
out.sum().backward() # error
```
### Issue
<!-- Link to Issue ticket or RFP -->
### Testing
<!-- How did you test your change? -->
Pull Request resolved: https://github.com/pytorch/pytorch/pull/82809
Approved by: https://github.com/malfet
