[Seq2seq] Add Support for TensorFlow
# What does this PR do?

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Adds seq2seq support for TensorFlow and its corresponding summarization training and evaluation script.


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
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      [documentation guidelines](https://github.com/huggingface/transformers/tree/master/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/master/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

@sgugger, @patrickvonplaten, @LysandreJik

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

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Hi! I'm the TF maintainer for 🤗 Transformers right now. Thanks for this, the code quality looks really good! There's one issue, though - we're currently trying to move away from `TFTrainer` and use more native, idiomatic TF code based on Keras. You can see an example of the kind of TFTrainer-free approach we're working on [here](https://github.com/huggingface/transformers/blob/master/examples/tensorflow/text-classification/run_text_classification.py).

As a result, we probably can't accept `Seq2SeqTFTrainer` in the main library right now, but we're definitely planning on adding a Seq2Seq TF example soon. If you'd like, you can try to convert this PR to a TFTrainer-free Seq2Seq example script and put it in /examples/tensorflow, but I understand if that's a lot of work and you don't want to bother right now! <|||||>Hi @Rocketknight1! Thanks for your feedback, I understand. This actually emerged as a side product from a project that I'm currently working on so I thought I'd share this. But it's good to know the direction you're heading. If you're planning to add some seq2seq examples for Keras in the next few weeks then it's fine to close this PR I guess. Otherwise I will probably rewrite this code in order to be aligned with the Huggingface library and its overall direction. Do you have any date on your mind for the seq2seq TF examples?<|||||>Hi, sorry for the delay! We are indeed planning to include those models, hopefully in a month or so. I don't have an exact date, but it's on my To Do list.<|||||>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.