Torch.cat throws error for tensor lists when used within torchscript.

Kindly let me know of a fix/workaround.

Here is a minimal example to reproduce the bug.

```
import torch
import torch.nn as nn
"""
Smallest working bug for torch.cat torchscript
"""
class Model(nn.Module):
"""dummy model for showing error"""
def __init__(self):
super(Model, self).__init__()
pass
def forward(self):
a = torch.rand([6, 1, 12])
b = torch.rand([6, 1, 12])
out = torch.cat([a, b], axis=2)
return out
if __name__ == '__main__':
model = Model()
print(model()) # works
torch.jit.script(model) # throws error
```

```
This code throws the following error:
File "/home/anil/.conda/envs/rnn/lib/python3.7/site-packages/torch/jit/__init__.py", line 1423, in _create_methods_from_stubs
self._c._create_methods(self, defs, rcbs, defaults)
RuntimeError:
Arguments for call are not valid.
The following operator variants are available:
aten::cat(Tensor[] tensors, int dim=0) -> (Tensor):
Keyword argument axis unknown.
aten::cat.out(Tensor[] tensors, int dim=0, *, Tensor(a!) out) -> (Tensor(a!)):
Argument out not provided.
The original call is:
at smallest_working_bug_torch_cat_torchscript.py:19:14
def forward(self):
a = torch.rand([6, 1, 12])
b = torch.rand([6, 1, 12])
out = torch.cat([a, b], axis=2)
~~~~~~~~~ <--- HERE
return out
```

Thank you for your consideration