code: 
  
  
  '''simple docstring'''
  
  
  
  
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from ...tokenization_utils import AddedToken
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  				from .tokenization_xlm_roberta import XLMRobertaTokenizer
  else:
  				__lowercase  :      Dict      		=				None
  
  
  __lowercase  :      Dict      		=				logging.get_logger(__name__)
  
  __lowercase  :      List[Any]      		=				{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}
  
  __lowercase  :      List[Any]      		=				{
      """vocab_file""": {
          """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
          """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
          """xlm-roberta-large-finetuned-conll02-dutch""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
          ),
          """xlm-roberta-large-finetuned-conll02-spanish""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
          ),
          """xlm-roberta-large-finetuned-conll03-english""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
          ),
          """xlm-roberta-large-finetuned-conll03-german""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
          ),
      },
      """tokenizer_file""": {
          """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json""",
          """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json""",
          """xlm-roberta-large-finetuned-conll02-dutch""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json"""
          ),
          """xlm-roberta-large-finetuned-conll02-spanish""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json"""
          ),
          """xlm-roberta-large-finetuned-conll03-english""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json"""
          ),
          """xlm-roberta-large-finetuned-conll03-german""": (
              """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json"""
          ),
      },
  }
  
  __lowercase  :      List[str]      		=				{
      """xlm-roberta-base""": 5_12,
      """xlm-roberta-large""": 5_12,
      """xlm-roberta-large-finetuned-conll02-dutch""": 5_12,
      """xlm-roberta-large-finetuned-conll02-spanish""": 5_12,
      """xlm-roberta-large-finetuned-conll03-english""": 5_12,
      """xlm-roberta-large-finetuned-conll03-german""": 5_12,
  }
  
  
  
  
  
  class _snake_case   ( lowerCamelCase__   ):
  							__a												=     VOCAB_FILES_NAMES
  							__a												=     PRETRAINED_VOCAB_FILES_MAP
  							__a												=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  							__a												=     ['''input_ids''', '''attention_mask''']
  							__a												=     XLMRobertaTokenizer
  
  
  
  
  
  
  
  							def __init__(   self			,				__A=None			,				__A=None			,				__A="<s>"			,				__A="</s>"			,				__A="</s>"			,				__A="<s>"			,				__A="<unk>"			,				__A="<pad>"			,				__A="<mask>"			,				**__A			,				)     ->Tuple:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Optional[Any]											=					AddedToken(SCREAMING_SNAKE_CASE_			,				lstrip=SCREAMING_SNAKE_CASE_			,				rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_	) else mask_token
  
  											super().__init__(
  											    SCREAMING_SNAKE_CASE_			,				tokenizer_file=SCREAMING_SNAKE_CASE_			,				bos_token=SCREAMING_SNAKE_CASE_			,				eos_token=SCREAMING_SNAKE_CASE_			,				sep_token=SCREAMING_SNAKE_CASE_			,				cls_token=SCREAMING_SNAKE_CASE_			,				unk_token=SCREAMING_SNAKE_CASE_			,				pad_token=SCREAMING_SNAKE_CASE_			,				mask_token=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			,				)
  
  											__lowerCamelCase		:      str											=					vocab_file
  											__lowerCamelCase		:      str											=					False if not self.vocab_file else True
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A = None	)     ->str:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											if token_ids_a is None:
  															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  											__lowerCamelCase		:      Optional[int]											=					[self.cls_token_id]
  											__lowerCamelCase		:      Optional[Any]											=					[self.sep_token_id]
  											return cls + token_ids_a + sep + sep + token_ids_a + sep
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A = None	)     ->str:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Tuple											=					[self.sep_token_id]
  											__lowerCamelCase		:      Tuple											=					[self.cls_token_id]
  
  											if token_ids_a is None:
  															return len(cls + token_ids_a + sep	) * [0]
  											return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A = None	)     ->List[Any]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											if not self.can_save_slow_tokenizer:
  															raise ValueError(
  															    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
  															    "tokenizer."	)
  
  											if not os.path.isdir(SCREAMING_SNAKE_CASE_	):
  															logger.error(f'Vocabulary path ({save_directory}) should be a directory.'	)
  															return
  											__lowerCamelCase		:      Optional[Any]											=					os.path.join(
  											    SCREAMING_SNAKE_CASE_			,				(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)
  
  											if os.path.abspath(self.vocab_file	) != os.path.abspath(SCREAMING_SNAKE_CASE_	):
  															copyfile(self.vocab_file			,				SCREAMING_SNAKE_CASE_	)
  
  											return (out_vocab_file,)
  
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  
  def 							a_       (						lowercase    )			->str:
  
  
  
  
  
  
  				'''simple docstring'''
  
  				return " ".join(sorted(set(sentence.split()    )    )    )
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  
  
  
  
  
  