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:
        SCREAMING_SNAKE_CASE       = None
  
  
  SCREAMING_SNAKE_CASE       = logging.get_logger(__name__)
  
  SCREAMING_SNAKE_CASE       = {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}
  
  SCREAMING_SNAKE_CASE       = {
      "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"
          ),
      },
  }
  
  SCREAMING_SNAKE_CASE       = {
      "xlm-roberta-base": 512,
      "xlm-roberta-large": 512,
      "xlm-roberta-large-finetuned-conll02-dutch": 512,
      "xlm-roberta-large-finetuned-conll02-spanish": 512,
      "xlm-roberta-large-finetuned-conll03-english": 512,
      "xlm-roberta-large-finetuned-conll03-german": 512,
  }
  
  
  
  
  class 			UpperCAmelCase_						(		A_							):
      lowercase__		      =   VOCAB_FILES_NAMES
      lowercase__		      =   PRETRAINED_VOCAB_FILES_MAP
      lowercase__		      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowercase__		      =   ['''input_ids''', '''attention_mask''']
      lowercase__		      =   XLMRobertaTokenizer
  
  
  
  
      def __init__(					self		: List[Any]			,				snake_case_		: Any=None			,				snake_case_		: str=None			,				snake_case_		: Union[str, Any]="<s>"			,				snake_case_		: Union[str, Any]="</s>"			,				snake_case_		: List[str]="</s>"			,				snake_case_		: Optional[int]="<s>"			,				snake_case_		: str="<unk>"			,				snake_case_		: Tuple="<pad>"			,				snake_case_		: List[str]="<mask>"			,				**snake_case_		: Optional[Any]			,				)   ->							int:
  
  
  
  
       '''simple docstring'''
  
       A__ =       AddedToken(snake_case_			,				lstrip=snake_case_			,				rstrip=snake_case_   ) if isinstance(snake_case_			,				snake_case_   ) else mask_token
  
       super().__init__(
           snake_case_			,				tokenizer_file=snake_case_			,				bos_token=snake_case_			,				eos_token=snake_case_			,				sep_token=snake_case_			,				cls_token=snake_case_			,				unk_token=snake_case_			,				pad_token=snake_case_			,				mask_token=snake_case_			,				**snake_case_			,				)
  
       A__ =       vocab_file
       A__ =       False if not self.vocab_file else True
  
  
  
  
      def 							__magic_name__							(					self		: Optional[int]			,				snake_case_		: List[int]			,				snake_case_		: Optional[List[int]] = None   )   ->							List[int]:
  
  
  
  
       '''simple docstring'''
  
       if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       A__ =       [self.cls_token_id]
       A__ =       [self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep
  
  
  
  
      def 							__magic_name__							(					self		: Union[str, Any]			,				snake_case_		: List[int]			,				snake_case_		: Optional[List[int]] = None   )   ->							List[int]:
  
  
  
  
       '''simple docstring'''
  
       A__ =       [self.sep_token_id]
       A__ =       [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 							__magic_name__							(					self		: Optional[int]			,				snake_case_		: str			,				snake_case_		: Optional[str] = None   )   ->							Tuple[str]:
  
  
  
  
       '''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(snake_case_   ):
        logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""   )
        return
       A__ =       os.path.join(
           snake_case_			,				(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )
  
       if os.path.abspath(self.vocab_file   ) != os.path.abspath(snake_case_   ):
        copyfile(self.vocab_file			,				snake_case_   )
  
       return (out_vocab_file,)
  
  
  
  
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  
  
  def 						_SCREAMING_SNAKE_CASE     (							lowercase_		)		->	str:
   return " ".join(sorted(set(sentence.split()		)		)		)
  
  
  if __name__ == "__main__":
        import doctest
  
        doctest.testmod()
  
  
  
  
  
  