Add TF<>PT and Flax<>PT everywhere
Author: patrickvonplaten
Pull request: yes

# What does this PR do?

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This PR adds the PT<>TF and PT<>Flax equivalence tests to the common PyTorch tests so that the equivalence tests are also fetched when just the PyTorch files are changed. The PR also uncovered a couple of smaller bugs in TFHuBERT and FlaxAlbert.


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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)

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Comments:
> Thanks for adding those. The only downside is that they will be run twice when we do the full suite, but I don't think it's a big issue.

Yes, but I think it's much more important to be sure that if one changes PyTorch's CLIP that both PT<>Flax and PT<>TF is run with the test fetcher. 

Also, the tests are actually slighly different in a sense that the ones that I added:
- Use the dummy model config of the PyTorch test suite
- Use the model inputs created in the PyTorch tests 

where as the previous tests used Flax's or TF's config and inputs. So I think having those tests also forces us to be consistent with the testing configs and inputs across frameworks