TF BART models - Add `cross_attentions` to model output and fix cross-attention head masking
This PR fixes some missing and invalid things around `cross_attentions` for the TensorFlow implementation of BART models:

- `Bart`,
- `Blenderbot` / `Blenderbot_small`,
- `Marian`,
- `MBart`,
- `Pegasus`.

More specifically, this PR includes:
- Enable returning `cross_attentions`
- Add class `TFBaseModelOutputWithCrossAttentions` (according to the PyTorch counterpart) to support output containing `cross_attentions`
- Fix attention head masking for the cross-attention module (by the introduction of `cross_attn_head_mask` and `cross_attn_layer_head_mask`)
- Implement `test_head_masking` for `cross_attn_head_mask`
- Fix some little typos in docs
- Update model templates - implement `head_mask`, `decoder_head_mask`, `cross_attn_head_mask` and code around `cross_attentions` to the TF encoder-decoder models

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Partially fixes: #10698 

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**Reviewers:** @jplu @patrickvonplaten @LysandreJik @sgugger 
Currently, there are some Torch/TF equivalent tests failing but it should be settled down once #10605 be merged.<|||||>@jplu - I'm gonna run all slow tests today and will let you know if everything works or not.<|||||>@jplu - I ran all (slow) non-GPU tests and it seems to me everything is passing :) <|||||>Ok, if all the tests for the involved models, including the slow ones, are passing, it is fine to merge for me.<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.<|||||>still open <|||||>@jplu @patrickvonplaten After merging #10605 and rebasing the branch, all tests have passed now :)<|||||>Great, thanks @stancld! 

This looks good to merge for me.<|||||>Pinging @Rocketknight1 for a final review here. Seq2Seq models like BART should also return cross attentions in TF (not just in PT)<|||||>This is a big PR but LGTM! I haven't exhaustively checked everything but the changes seem correct and innocuous, so if it passes tests I'm happy to merge it.