TracerWarning on modeling_gpt2.py:147 when using Torchscript
The following script:
```
    model = GPT2LMHeadModel.from_pretrained('gpt2-medium')
    model.eval()
    example = torch.randn(100, 50).abs().mul(1000).type(torch.int64)
    traced_model = torch.jit.trace(model, example)
```
I

It's returning the following Warning:
```
python3.7/site-packages/transformers/modeling_gpt2.py:147: TracerWarning: Converting a tensor to a Python index might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
  mask = self.bias[:, :, ns - nd : ns, :ns]
```

Is this something to worry about? I see there was a similar issue with sqrt in  https://github.com/huggingface/transformers/issues/3954 

Additionally, if I wanted to use Torchscript with past, then I should still trace the model in such way so that the past is being recorded in the model. Is that correct?

- `transformers` version: 2.9.0
- Platform: macos
- Python version: 3.7
- PyTorch version: 1.5.0 cpu
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
