Warning about too long input for fast tokenizers too
Author: Narsil
Pull request: yes

# What does this PR do?


If truncation is not set in tokenizers, but the tokenization is too long 
for the model (`model_max_length`), we used to trigger a warning that

The input would probably fail (which it most likely will).

This PR re-enables the warning for fast tokenizers too and uses common code
for the trigger to make sure it's consistent across.



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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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@LysandreJik
@thomwolf

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 albert, bert, XLM: @LysandreJik
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 tokenizers: @mfuntowicz
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 Benchmarks: @patrickvonplaten
 Model Cards: @julien-c
 examples/distillation: @VictorSanh
 nlp datasets: [different repo](https://github.com/huggingface/nlp)
 rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
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Comments:
Failing tests seem to come from some other code (seq2seq)

@thomwolf could you review this PR as you're the mastermind behind this code?

@LysandreJik May I merge (failing tests and quality is linked to unrelated `finetune.py` code, I tried to rebase but it does not seem to be enough)