Generalize catArray for contiguous inputs and dim != 0 (#17032)
Summary:
I noticed that we were sinking a lot of time into `cat` operations in machine translation on CPU, and drilled down to us doing the cat element-by-element, even though all the inputs were contiguous. The reason was we were doing the cat along a dimension that was not 0, and that caused us to not use the fast `memcpy` branch. This PR generalizes that branch.
Quick benchmark script:
```
import torch, time
tensors = [torch.rand(6, 2, 1024) for i in range(5)]
NITER = 1000
s = time.time()
for i in range(NITER):
torch.cat(tensors, dim=1)
print('time per iter ', (time.time() - s) / NITER)
```
Before:
```
time per iter 8.089399337768554e-05
```
After:
```
time per iter 2.183413505554199e-05
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17032
Differential Revision: D14090038
Pulled By: jamesr66a
fbshipit-source-id: 2c733a84915896008ac95f2233f44894bd2573de
