Add BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese
# What does this PR do?


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- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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- [X] Did you write any new necessary tests?


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Please help have a look: @patrickvonplaten, @patil-suraj Thanks.



Thanks, @patil-suraj and @sgugger 
I fixed the pull request based on you guys' comments.

The same comment I get from both of you is regarding the vocab_file. Here is a summary:

I did not train a sentencepiece for Vietnamese.
`bartpho-syllable` employs the existing pre-trained "sentencepiece" model from XLMRoBERTaTokenizer, and this pre-trained "sentencepiece" model is referred to as a `vocab_file` of 250K types.
`reduced_vocab_file` is a vocab containing 40K Vietnamese-specificized types extracted from the XLMRoBERTaTokenizer vocab of 250K types.

Usecase of BartphoTokenizer: Other languages can thus simply reuse BartphoTokenizer with their own `reduced_vocab_file`. The goal here is to reduce model sizes of existing pre-trained XLM-RoBERTa/mBART models when applying to a smaller set of languages instead of the whole 50/100 languages.<|||||>@sgugger , @LysandreJik, @patil-suraj , @SaulLu  and @patrickvonplaten
Please could you have a look and provide your feedback for my recent changes? Thanks.<|||||>Thanks @LysandreJik 

My pull request suddenly failed the check `run_tests_torch_and_flax`:

`FAILED tests/test_modeling_flax_clip.py::FlaxCLIPModelTest::test_equivalence_flax_to_pt`
`FAILED tests/test_modeling_flax_clip.py::FlaxCLIPModelTest::test_equivalence_pt_to_flax`

They are out of my control, not relating to BartphoTokenizer.
<|||||>Yes this is a problem unrelated to this PR so you can ignore those failures. They should be fixed tomorrow :-)<|||||>@sgugger I made a revision following your last comment. Thanks.
FYI, two failed tests are not related to BartphoTokenizer.<|||||>Thanks a gain for your contribution!