[Longformer] Better handling of global attention mask vs local attention mask
Author: patrickvonplaten
Pull request: yes

This PR extends Longformer's API to also take a `global_attention_mask` besides the usual `attention_mask` as an input as discussed with @thomwolf @ibeltagy. 

Docs are updated.

Comments:
Regarding the Multiple Choice `global_attention_mask`. Discussion taken from PR: https://github.com/huggingface/transformers/pull/4645#issuecomment-635429380

> @patil-suraj, we can leave it to the user, or we can just do as you suggested earlier, put global attention on the question and all choices, which should work.
> 
> @patrickvonplaten, what do you think?

Regarding the multiple choice, I think we usually have the following tensor:
```
[
[ context, choice_a],
[ context, choice_b],
[ context, choice_c], 
...
]
```

see here: https://github.com/huggingface/transformers/blob/9c17256447b91cf8483c856cb15e95ed30ace538/examples/multiple-choice/utils_multiple_choice.py#L529

So I'd suggest if no `global_attention_mask` is provided by the user, we initialize the `global_attention_mask` so that all choice contexts do global attention. If the user wants a different global attention he has now the possibility to define it himself.

@ibeltagy 

# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4672?src=pr&el=h1) Report
> Merging [#4672](https://codecov.io/gh/huggingface/transformers/pull/4672?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/9c17256447b91cf8483c856cb15e95ed30ace538&el=desc) will **decrease** coverage by `0.05%`.
> The diff coverage is `41.37%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/4672/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4672?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #4672      +/-   ##
==========================================
- Coverage   77.23%   77.17%   -0.06%     
==========================================
  Files         128      128              
  Lines       21050    21060      +10     
==========================================
- Hits        16257    16253       -4     
- Misses       4793     4807      +14     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4672?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_longformer.py](https://codecov.io/gh/huggingface/transformers/pull/4672/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19sb25nZm9ybWVyLnB5) | `93.52% <41.37%> (-3.53%)` | :arrow_down: |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4672/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.85% <0.00%> (+0.41%)` | :arrow_up: |

------

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Ok, checked the notebook: https://colab.research.google.com/drive/1m7eTGlPmLRgoPkkA7rkhQdZ9ydpmsdLE?usp=sharing  and results are the same as before so no breaking changes. 

Good to merge for me!

> Ok, checked the notebook: https://colab.research.google.com/drive/1m7eTGlPmLRgoPkkA7rkhQdZ9ydpmsdLE?usp=sharing and results are the same as before so no breaking changes.
> 
> Good to merge for me!

This is great !

Just noticed one typo in the first line
> This notebook shows how `nlp` can be leveraged `nlp` to evaluate Longformer on TriviaQA