[Generate] Make generate multi-modal
Author: patrickvonplaten
Pull request: yes

# What does this PR do?

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This PR makes `generate()` multi-modal by not assuming anymore that the input to the encoder is of type `input_ids`. 
While doing so some refactoring is done to make `generate()` cleaner.

To review the changes in detail it's probably best to take a look at the new `generate()` function as well as the diff.


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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
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Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

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Comments:
Also tested on slow tests of:
- T5
- BART
- GPT2
- RAG

@Narsil it would be amazing if you could take a closer look here

Also cc @ydshieh for info

Can we also take care of the 2 hacks that were included:

- remove `attention_mask` from `modeling_vit.py` and `modeling_deit.py` (this was added to make `VisionEncoderDecoderModel` work with `generate`)
- remove the hack in `Seq2SeqTrainer` [here](https://github.com/huggingface/transformers/blob/8010fda9bfbac3f4860e15bdb476c63c6cf2ce81/src/transformers/trainer_seq2seq.py#L164)

> Can we also take care of the 2 hacks that were included:
> 
> * remove `attention_mask` from `modeling_vit.py` and `modeling_deit.py` (this was added to make `VisionEncoderDecoderModel` work with `generate`)
> * remove the hack in `Seq2SeqTrainer` [here](https://github.com/huggingface/transformers/blob/8010fda9bfbac3f4860e15bdb476c63c6cf2ce81/src/transformers/trainer_seq2seq.py#L164)

We should tackle them in a follow-up PR:
- remove `attention_mask` is completely orthogonal to this PR 
- the `Seq2SeqTrainer` hack can be removed after this PR, but I don't want to touch both `generate` and `Trainer` here.

EDIT: BTW the remove `attention_mask` will be made trivial once we add `model_input_names` to the model architectures. So another reason to add those @sgugger ;-)

Merging this PR now! I will open two new PRs:

1.) Deprecate `imageGPT` input arg to `input_ids`
2.) Remove the Trainer hack

Once the `model_input_names` are added as a class variable to all model architectures (@sgugger - happy to take over this PR next week), we can remove the `attention_mask` hack in the image models as well