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:
      _A						=     None
  
  
  _A						=     logging.get_logger(__name__)
  
  _A						=     {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}
  
  _A						=     {
      """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"""
          ),
      },
  }
  
  _A						=     {
      """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 			lowerCamelCase  (					lowerCAmelCase__      ):
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    SCREAMING_SNAKE_CASE							=     VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE							=     PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    SCREAMING_SNAKE_CASE							=     ['input_ids', 'attention_mask']
    SCREAMING_SNAKE_CASE							=     XLMRobertaTokenizer
  
  
  
    def __init__(self       ,					_lowerCamelCase=None       ,					_lowerCamelCase=None       ,					_lowerCamelCase="<s>"       ,					_lowerCamelCase="</s>"       ,					_lowerCamelCase="</s>"       ,					_lowerCamelCase="<s>"       ,					_lowerCamelCase="<unk>"       ,					_lowerCamelCase="<pad>"       ,					_lowerCamelCase="<mask>"       ,					**_lowerCamelCase       ,					):
  
  
          """simple docstring"""
  
          UpperCAmelCase__ :       Any						=						AddedToken(_lowerCamelCase       ,					lstrip=_lowerCamelCase       ,					rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase       ,					_lowerCamelCase  ) else mask_token
  
          super().__init__(
              _lowerCamelCase       ,					tokenizer_file=_lowerCamelCase       ,					bos_token=_lowerCamelCase       ,					eos_token=_lowerCamelCase       ,					sep_token=_lowerCamelCase       ,					cls_token=_lowerCamelCase       ,					unk_token=_lowerCamelCase       ,					pad_token=_lowerCamelCase       ,					mask_token=_lowerCamelCase       ,					**_lowerCamelCase       ,					)
  
          UpperCAmelCase__ :       Any						=						vocab_file
          UpperCAmelCase__ :       Union[str, Any]						=						False if not self.vocab_file else True
  
  
  
    def    _a			(self       ,					_lowerCamelCase       ,					_lowerCamelCase = None  ):
  
  
          """simple docstring"""
  
          if token_ids_a is None:
                return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          UpperCAmelCase__ :       Dict						=						[self.cls_token_id]
          UpperCAmelCase__ :       Tuple						=						[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep
  
  
  
    def    _a			(self       ,					_lowerCamelCase       ,					_lowerCamelCase = None  ):
  
  
          """simple docstring"""
  
          UpperCAmelCase__ :       Tuple						=						[self.sep_token_id]
          UpperCAmelCase__ :       Dict						=						[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       ,					_lowerCamelCase       ,					_lowerCamelCase = None  ):
  
  
          """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(_lowerCamelCase  ):
                logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""  )
                return
          UpperCAmelCase__ :       str						=						os.path.join(
              _lowerCamelCase       ,					(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )
  
          if os.path.abspath(self.vocab_file  ) != os.path.abspath(_lowerCamelCase  ):
                copyfile(self.vocab_file       ,					_lowerCamelCase  )
  
          return (out_vocab_file,)
  
  
style_context: 
  
  """simple docstring"""
  from __future__ import annotations
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   set[int]:
        UpperCAmelCase__ :       List[Any]						=						{1}
        UpperCAmelCase__ :       Optional[int]						=						[1]
        for _ in range(2 ,  depth + 1						):
              UpperCAmelCase__ :       Tuple						=						[*previous_coefficients, 0]
              UpperCAmelCase__ :       List[str]						=						[0, *previous_coefficients]
              UpperCAmelCase__ :       Dict						=						[]
              for x, y in zip(lowerCAmelCase ,  lowerCAmelCase						):
                    coefficients.add(x + y						)
                    previous_coefficients.append(x + y						)
        return coefficients
  
  
  
  
  def 				a__	(	lowerCAmelCase						)  ->   set[int]:
        UpperCAmelCase__ :       List[str]						=						set()
        for number in unique_coefficients:
              UpperCAmelCase__ :       int						=						2
              UpperCAmelCase__ :       List[Any]						=						number
              while divisor**2 <= copy_number:
                    UpperCAmelCase__ :       Tuple						=						0
                    while copy_number % divisor == 0:
                          copy_number //= divisor
                          multiplicity += 1
                    if multiplicity >= 2:
                          non_squarefrees.add(lowerCAmelCase						)
                          break
                    divisor += 1
  
        return unique_coefficients.difference(lowerCAmelCase						)
  
  
  
  
  def 				a__	(	lowerCAmelCase = 51						)  ->   int:
        UpperCAmelCase__ :       Any						=						get_pascal_triangle_unique_coefficients(lowerCAmelCase						)
        UpperCAmelCase__ :       Dict						=						get_squarefrees(lowerCAmelCase						)
        return sum(lowerCAmelCase						)
  
  
  if __name__ == "__main__":
      print(f'''{solution() = }''')
  
  