code: 
  '''simple docstring'''
  
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
  from ...utils import logging
  
  
  UpperCamelCase_     			= logging.get_logger(__name__)
  
  UpperCamelCase_     			= {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}
  
  UpperCamelCase_     			= {
      """vocab_file""": {
          """TsinghuaAI/CPM-Generate""": """https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model""",
      },
      """tokenizer_file""": {
          """TsinghuaAI/CPM-Generate""": """https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json""",
      },
  }
  
  
  class   a_  (_a    ):
  
  
  
  
         def __init__(     self   ,   snake_case_=None   ,   snake_case_=None   ,   snake_case_=False   ,   snake_case_=True   ,   snake_case_=False   ,   snake_case_="<s>"   ,   snake_case_="</s>"   ,   snake_case_="<unk>"   ,   snake_case_="<sep>"   ,   snake_case_="<pad>"   ,   snake_case_="<cls>"   ,   snake_case_="<mask>"   ,   snake_case_=["<eop>", "<eod>"]   ,   **snake_case_   ,   ):
           _lowerCAmelCase       :  Optional[Any]   				=					AddedToken(snake_case_   ,   lstrip=snake_case_   ,   rstrip=snake_case_  ) if isinstance(snake_case_   ,   snake_case_  ) else mask_token
  
           super().__init__(
               vocab_file=snake_case_   ,   tokenizer_file=snake_case_   ,   do_lower_case=snake_case_   ,   remove_space=snake_case_   ,   keep_accents=snake_case_   ,   bos_token=snake_case_   ,   eos_token=snake_case_   ,   unk_token=snake_case_   ,   sep_token=snake_case_   ,   pad_token=snake_case_   ,   cls_token=snake_case_   ,   mask_token=snake_case_   ,   additional_special_tokens=snake_case_   ,   **snake_case_   ,   )
  
           _lowerCAmelCase       :  Optional[Any]   				=					3
           _lowerCAmelCase       :  Optional[Any]   				=					do_lower_case
           _lowerCAmelCase       :  List[str]   				=					remove_space
           _lowerCAmelCase       :  Optional[Any]   				=					keep_accents
           _lowerCAmelCase       :  Tuple   				=					vocab_file
           _lowerCAmelCase       :  str   				=					False if not self.vocab_file else True
  
           try:
             import jieba
           except ModuleNotFoundError as error:
             raise error.__class__(
                 """You need to install jieba to use CpmTokenizer or CpmTokenizerFast. """
                 """See https://pypi.org/project/jieba/ for installation."""  )
           _lowerCAmelCase       :  Union[str, Any]   				=					jieba
           _lowerCAmelCase       :  Optional[int]   				=					str.maketrans(""" \n"""   ,   """\u2582\u2583"""  )
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_ = None  ):
           _lowerCAmelCase       :  List[Any]   				=					[self.sep_token_id]
           _lowerCAmelCase       :  str   				=					[self.cls_token_id]
           if token_ids_a is None:
             return token_ids_a + sep + cls
           return token_ids_a + sep + token_ids_a + sep + cls
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_ = None  ):
           _lowerCAmelCase       :  int   				=					[self.sep_token_id]
           _lowerCAmelCase       :  List[str]   				=					[2]
  
           if token_ids_a is None:
             return len(token_ids_a + sep  ) * [0] + cls_segment_id
           return len(token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1] + cls_segment_id
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_ = None  ):
           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
           _lowerCAmelCase       :  Dict   				=					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,)
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   *snake_case_   ,   **snake_case_  ):
           _lowerCAmelCase       :  int   				=					[
               """ """.join([x.translate(self.translator  ) for x in self.jieba.cut(snake_case_   ,   cut_all=snake_case_  )]  )
               for text in batch_text_or_text_pairs
           ]
           return super()._batch_encode_plus(snake_case_   ,   *snake_case_   ,   **snake_case_  )
  
  
  
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   *snake_case_   ,   **snake_case_  ):
           _lowerCAmelCase       :  List[str]   				=					super()._decode(*snake_case_   ,   **snake_case_  )
           _lowerCAmelCase       :  str   				=					text.replace(""" """   ,   """"""  ).replace("""\u2582"""   ,   """ """  ).replace("""\u2583"""   ,   """\n"""  )
           return text
  
  
  
style_context: 
  '''simple docstring'''
  
  import random
  
  
  class   a_  :
  
  
  
  
         def __init__(     self   ,   snake_case_   ,   snake_case_  ):
           _lowerCAmelCase       :  List[str]   				=					x
           _lowerCAmelCase       :  List[str]   				=					y
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           return (self.x**2 + self.y**2) <= 1
  
  
  
  
  
  
  
         @classmethod
         def 							__UpperCamelCase       (     cls  ):
           return cls(x=random.random()   ,   y=random.random()  )
  
  
  
  def 	_UpperCAmelCase				(  _lowerCamelCase						:       int		)    ->						float:
    if number_of_simulations < 1:
      raise ValueError("""At least one simulation is necessary to estimate PI."""		)
  
    _lowerCAmelCase       :  Tuple   				=					0
    for _ in range(_lowerCamelCase		):
      _lowerCAmelCase       :  Union[str, Any]   				=					Point.random_unit_square()
  
      if random_point.is_in_unit_circle():
        number_in_unit_circle += 1
  
    return 4 * number_in_unit_circle / number_of_simulations
  
  
  if __name__ == "__main__":
       # import doctest
  
       # doctest.testmod()
       from math import pi
  
       UpperCamelCase_     			=       """Please enter the desired number of Monte Carlo simulations: """
       UpperCamelCase_     			=       estimate_pi(int(input(prompt).strip()))
       print(F'An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}')
  
  
  