[Lazy init] Force fall back to slow init for composite models
Author: patrickvonplaten
Pull request: yes

# What does this PR do?

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Thanks to the great issue #11704 it was discovered that fast initialization currently breaks for all models whose `XXXPreTrainedModel` does not implement a `_init_weights` function and for which parts of the weights are missing when using `.from_pretrained(...)`. This includes essentially all composite models, being `Rag` and `EncoderDecoder`.

This PR does the vanilla fix of forcing those models to fall back on `_slow_init` since a better fix requires a careful re-design which is left for a future PR.

## Future PR
- [ ] Remove hacky `from_pretrained(...)` methods in RAG and EncoderDecoder
- [ ] Refactor the way "fast_init" calls `model._init_weights` for composite models. For Composite models, each part has to be called directly => 

```python
model.encoder._init_weigths(all_missing_keys_of_encoder)
model.decoder._init_weigths(all_missing_keys_of_decoder)
```

- [ ] Add more tests for RAG & EncoderDecoder

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] 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.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [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?

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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