Add TFBartForConditionalGeneration
- adds `TFBartForConditionalGeneration`, which can generate summaries that are equivalent to pytorch.


#### TODO this PR:
- [x] fast tests besides two
- [x] reasonable xsum generations
- [x] tests passing
- [x] fix slow cnn test (tf needs to call `adjust_logits_during_generation`)
- [x] functional dropout
- [x] simplify torch and tf caching logic
- [x] docs
- [x] upload applicable tf/h5 weights.



#### Future PRs:

- [ ] blender/pegasus/mBART/marian etc.
- [ ] #7814
Awesome! This PR will leverage many pretrained weights and make them available for TF! 
I don't really think there is a workaround for  [supporting multiple input types](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_tf_t5.py#L946) especially to make it compatible with Keras at the moment. There was a discussion on Slack about it (also cc  @jplu ). Also, did you check that the model works in tf graph mode (corresponds to this test: https://github.com/huggingface/transformers/blob/316206c11466c9a4019a376843581bf519422369/tests/test_modeling_tf_common.py#L128 which is about to be added in another PR).<|||||>Sounds like I should wait until you start/for other changes to work more on this @jplu ?

Would be really good IMO if whatever XLA magic we use decides whether the functions should take tuples or dicts. I much prefer either to both.
<|||||>IMHO yes, and this will let you more time to polish your code :) After this is only mine, if everybody else prefer to have it merged I will not go against ^^ but I think that for now the more we add models, the more we add issues, and then the longer and harder it will be to fix everything.

I'm in favor to use only positional arguments and dicts, but this should be discussed with everybody, to see what they think about it.<|||||>Is this still blocked @jplu ?<|||||>Try to rebase + make the changes to pass the tests. And it should be ok :)<|||||>Thanks for the review @LysandreJik !

+ mBART, Pegasus and Blenderbot, and Marian will be in the next PR. (this is too big already for me to hold in my tiny brain).
+ Your 4 bullets:  Will do!