Adding Fast tokenizers for SentencePiece based tokenizers - Breaking: remove Transfo-XL fast tokenizer (#7141)

* [WIP] SP tokenizers

* fixing tests for T5

* WIP tokenizers

* serialization

* update T5

* WIP T5 tokenization

* slow to fast conversion script

* Refactoring to move tokenzier implementations inside transformers

* Adding gpt - refactoring - quality

* WIP adding several tokenizers to the fast world

* WIP Roberta - moving implementations

* update to dev4 switch file loading to in-memory loading

* Updating and fixing

* advancing on the tokenizers - updating do_lower_case

* style and quality

* moving forward with tokenizers conversion and tests

* MBart, T5

* dumping the fast version of transformer XL

* Adding to autotokenizers + style/quality

* update init and space_between_special_tokens

* style and quality

* bump up tokenizers version

* add protobuf

* fix pickle Bert JP with Mecab

* fix newly added tokenizers

* style and quality

* fix bert japanese

* fix funnel

* limite tokenizer warning to one occurence

* clean up file

* fix new tokenizers

* fast tokenizers deep tests

* WIP adding all the special fast tests on the new fast tokenizers

* quick fix

* adding more fast tokenizers in the fast tests

* all tokenizers in fast version tested

* Adding BertGenerationFast

* bump up setup.py for CI

* remove BertGenerationFast (too early)

* bump up tokenizers version

* Clean old docstrings

* Typo

* Update following Lysandre comments

Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

tests/test_tokenization_bert.py

@@ -35,7 +35,9 @@ from .test_tokenization_common import TokenizerTesterMixin
 class BertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
 
     tokenizer_class = BertTokenizer
+    rust_tokenizer_class = BertTokenizerFast
     test_rust_tokenizer = True
+    space_between_special_tokens = True
 
     def setUp(self):
         super().setUp()
@@ -61,9 +63,6 @@ class BertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
         with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer:
             vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
 
-    def get_rust_tokenizer(self, **kwargs):
-        return BertTokenizerFast.from_pretrained(self.tmpdirname, **kwargs)
-
     def get_input_output_texts(self, tokenizer):
         input_text = "UNwant\u00E9d,running"
         output_text = "unwanted, running"