code: 
  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:
  			UpperCamelCase_	:    Any  					=       None
  
  
  UpperCamelCase_	:    Dict  					=       logging.get_logger(__name__)
  
  UpperCamelCase_	:    Optional[int]  					=       {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}
  
  UpperCamelCase_	:    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"""
          ),
      },
  }
  
  UpperCamelCase_	:    Union[str, Any]  					=       {
      """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      __lowercase	(	__snake_case					):
  	_A   			=      VOCAB_FILES_NAMES
  	_A   			=      PRETRAINED_VOCAB_FILES_MAP
  	_A   			=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  	_A   			=      ["input_ids", "attention_mask"]
  	_A   			=      XLMRobertaTokenizer
  
  
  
  
  
  
  	def __init__(self							:   Union[str, Any]			,  snake_case							:   str=None			,  snake_case							:   List[Any]=None			,  snake_case							:   int="<s>"			,  snake_case							:   Optional[Any]="</s>"			,  snake_case							:   Union[str, Any]="</s>"			,  snake_case							:   Tuple="<s>"			,  snake_case							:   Dict="<unk>"			,  snake_case							:   Union[str, Any]="<pad>"			,  snake_case							:   List[Any]="<mask>"			,  **snake_case							:   Dict			,  )   -> Any:
  							# Mask token behave like a normal word, i.e. include the space before it
  							_lowercase					:  Union[str, Any]    			=      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			,  )
  
  							_lowercase					:  Union[str, Any]    			=      vocab_file
  							_lowercase					:  Optional[Any]    			=      False if not self.vocab_file else True
  
  
  
  
  
  
  	def 			_a(self							:   str			,  snake_case							:   List[int]			,  snake_case							:   Optional[List[int]] = None						)   -> List[int]:
  
  							if token_ids_a is None:
  													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  							_lowercase					:  Any    			=      [self.cls_token_id]
  							_lowercase					:  int    			=      [self.sep_token_id]
  							return cls + token_ids_a + sep + sep + token_ids_a + sep
  
  
  
  
  
  
  	def 			_a(self							:   List[Any]			,  snake_case							:   List[int]			,  snake_case							:   Optional[List[int]] = None						)   -> List[int]:
  							_lowercase					:  List[Any]    			=      [self.sep_token_id]
  							_lowercase					:  Optional[Any]    			=      [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 			_a(self							:   Any			,  snake_case							:   str			,  snake_case							:   Optional[str] = None						)   -> Tuple[str]:
  							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
  							_lowercase					:  Optional[int]    			=      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: 
  from __future__ import annotations
  
  
  
  def 		UpperCamelCase    (					_UpperCAmelCase     :      list[int]   , _UpperCAmelCase     :      int     )      -> int:
  
  
  
  
  
  
  						'''simple docstring'''
  
  						_lowercase			,						_lowercase					:  Any    			=      0, len(_UpperCAmelCase     ) - 1
  						while start_ind <= end_ind:
  												if array[start_ind] == search_item:
  																		return start_ind
  												elif array[end_ind] == search_item:
  																		return end_ind
  												else:
  																		start_ind += 1
  																		end_ind -= 1
      # returns -1 if search_item is not found in array
  						return -1
  
  
  if __name__ == "__main__":
  							print(double_linear_search(list(range(100)), 40))
  
  
  
  
  