code: 
  
  
  
  
  
  
  import os
  import unittest
  
  from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  
  
  
  class     __a						(					A__ ,     unittest.TestCase ):
   _lowerCAmelCase : Tuple 				=				BertweetTokenizer
   _lowerCAmelCase : List[Any] 				=				False
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Union[str, Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        super().setUp()
  
        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        UpperCamelCase__    :     Optional[Any]        =						["I", "m", "V@@", "R@@", "r", "e@@"]
        UpperCamelCase__    :     Union[str, Any]        =						dict(zip(SCREAMING_SNAKE_CASE							,     range(len(SCREAMING_SNAKE_CASE		)		)		)		)
        UpperCamelCase__    :     Union[str, Any]        =						["#version: 0.2", "a m</w>"]
        UpperCamelCase__    :     Any        =						{"unk_token": "<unk>"}
  
        UpperCamelCase__    :     List[Any]        =						os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES["vocab_file"]		)
        UpperCamelCase__    :     Optional[Any]        =						os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES["merges_file"]		)
        with open(self.vocab_file							,     "w"							,     encoding="utf-8"		) as fp:
             for token in vocab_tokens:
                  fp.write(F'{token} {vocab_tokens[token]}\n'		)
        with open(self.merges_file							,     "w"							,     encoding="utf-8"		) as fp:
             fp.write("\n".join(SCREAMING_SNAKE_CASE		)		)
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Optional[Any]							,     **SCREAMING_SNAKE_CASE      :     Any		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        kwargs.update(self.special_tokens_map		)
        return BertweetTokenizer.from_pretrained(self.tmpdirname							,     **SCREAMING_SNAKE_CASE		)
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     int							,     SCREAMING_SNAKE_CASE      :     Union[str, Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Any        =						"I am VinAI Research"
        UpperCamelCase__    :     Union[str, Any]        =						"I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"
        return input_text, output_text
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Union[str, Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     str        =						BertweetTokenizer(self.vocab_file							,     self.merges_file							,     **self.special_tokens_map		)
        UpperCamelCase__    :     Tuple        =						"I am VinAI Research"
        UpperCamelCase__    :     Any        =						"I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
        UpperCamelCase__    :     List[Any]        =						tokenizer.tokenize(SCREAMING_SNAKE_CASE		)
        self.assertListEqual(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE		)
  
        UpperCamelCase__    :     str        =						tokens + [tokenizer.unk_token]
  
        UpperCamelCase__    :     Dict        =						[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE		)							,     SCREAMING_SNAKE_CASE		)
style_context: 
  
  
  
  
  
  
  import os
  import unittest
  
  from transformers import MPNetTokenizerFast
  from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
  from transformers.testing_utils import require_tokenizers, slow
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  
  
  
  @require_tokenizers
  class     __a						(					A__ ,     unittest.TestCase ):
   _lowerCAmelCase : str 				=				MPNetTokenizer
   _lowerCAmelCase : List[str] 				=				MPNetTokenizerFast
   _lowerCAmelCase : List[Any] 				=				True
   _lowerCAmelCase : Union[str, Any] 				=				True
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     List[Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        super().setUp()
  
        UpperCamelCase__    :     List[Any]        =						[
            "[UNK]",
            "[CLS]",
            "[SEP]",
            "[PAD]",
            "[MASK]",
            "want",
            "##want",
            "##ed",
            "wa",
            "un",
            "runn",
            "##ing",
            ",",
            "low",
            "lowest",
        ]
        UpperCamelCase__    :     int        =						os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES["vocab_file"]		)
        with open(self.vocab_file							,     "w"							,     encoding="utf-8"		) as vocab_writer:
             vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Tuple							,     SCREAMING_SNAKE_CASE      :     List[str]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     List[str]        =						"UNwant\u00E9d,running"
        UpperCamelCase__    :     List[str]        =						"unwanted, running"
        return input_text, output_text
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Any		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     str        =						self.tokenizer_class(self.vocab_file		)
  
        UpperCamelCase__    :     Any        =						tokenizer.tokenize("UNwant\u00E9d,running"		)
        self.assertListEqual(SCREAMING_SNAKE_CASE							,     ["un", "##want", "##ed", ",", "runn", "##ing"]		)
        self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE		)							,     [9, 6, 7, 12, 10, 11]		)
  
  
  
  
  
  
  
   @slow
   def       __lowercase      (	self      :     str		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Union[str, Any]        =						self.tokenizer_class.from_pretrained("microsoft/mpnet-base"		)
  
        UpperCamelCase__    :     Optional[int]        =						tokenizer.encode("sequence builders"							,     add_special_tokens=SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     Optional[int]        =						tokenizer.encode("multi-sequence build"							,     add_special_tokens=SCREAMING_SNAKE_CASE		)
  
        UpperCamelCase__    :     Tuple        =						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     Optional[int]        =						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE		)
  
        assert encoded_sentence == [0] + text + [2]
        assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]