
"""simple docstring"""







def       A_      (       lowercase = 1    ,			lowercase = 1000   )  ->				int:


     """simple docstring"""







     UpperCAmelCase_    :     Tuple            =	1
     UpperCAmelCase_    :     List[str]            =	0

     for divide_by_number in range(lowercase    ,			digit + 1   ):
          UpperCAmelCase_    :     list[int]            =	[]
          UpperCAmelCase_    :     Optional[int]            =	numerator
          for _ in range(1    ,			digit + 1   ):
               if now_divide in has_been_divided:
                    if longest_list_length < len(lowercase   ):
                         UpperCAmelCase_    :     Dict            =	len(lowercase   )
                         UpperCAmelCase_    :     Optional[int]            =	divide_by_number
               else:
                    has_been_divided.append(lowercase   )
                    UpperCAmelCase_    :     List[str]            =	now_divide * 10 % divide_by_number

     return the_digit


# Tests
if __name__ == "__main__":
       import doctest

       doctest.testmod()



"""simple docstring"""







import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing



class 		UpperCAmelCase_						(lowerCamelCase_    ):
 """simple docstring"""




 def __init__(			self							:			List[Any]  , a_							:			str = "▁"  , a_							:			bool = True  , a_							:			Union[str, AddedToken] = "<unk>"  , a_							:			Union[str, AddedToken] = "</s>"  , a_							:			Union[str, AddedToken] = "<pad>"  , )->       List[Any]:



      """simple docstring"""

      UpperCAmelCase_    :     Dict            =	{
          """pad""": {"""id""": 0, """token""": pad_token},
          """eos""": {"""id""": 1, """token""": eos_token},
          """unk""": {"""id""": 2, """token""": unk_token},
      }

      UpperCAmelCase_    :     Dict            =	[None] * len(self.special_tokens			)
      for token_dict in self.special_tokens.values():
           UpperCAmelCase_    :     Optional[int]            =	token_dict["""token"""]

      UpperCAmelCase_    :     Tuple            =	Tokenizer(Unigram()			)

      UpperCAmelCase_    :     Optional[Any]            =	normalizers.Sequence(
          [
              normalizers.Nmt(),
              normalizers.NFKC(),
              normalizers.Replace(Regex(""" {2,}"""			)  , """ """			),
              normalizers.Lowercase(),
          ]			)
      UpperCAmelCase_    :     Any            =	pre_tokenizers.Sequence(
          [
              pre_tokenizers.Metaspace(replacement=a_  , add_prefix_space=a_			),
              pre_tokenizers.Digits(individual_digits=a_			),
              pre_tokenizers.Punctuation(),
          ]			)
      UpperCAmelCase_    :     str            =	decoders.Metaspace(replacement=a_  , add_prefix_space=a_			)

      UpperCAmelCase_    :     List[Any]            =	TemplateProcessing(
          single=f'''$A {self.special_tokens['eos']['token']}'''  , special_tokens=[(self.special_tokens["""eos"""]["""token"""], self.special_tokens["""eos"""]["""id"""])]  , )

      UpperCAmelCase_    :     Dict            =	{
          """model""": """SentencePieceUnigram""",
          """replacement""": replacement,
          """add_prefix_space""": add_prefix_space,
      }

      super().__init__(a_  , a_			)




 def 	a   (			self							:			int  , a_							:			Union[str, List[str]]  , a_							:			int = 80_00  , a_							:			bool = True  , )->       int:



      """simple docstring"""

      UpperCAmelCase_    :     int            =	trainers.UnigramTrainer(
          vocab_size=a_  , special_tokens=self.special_tokens_list  , show_progress=a_  , )

      if isinstance(a_  , a_			):
           UpperCAmelCase_    :     str            =	[files]
      self._tokenizer.train(a_  , trainer=a_			)

      self.add_unk_id()




 def 	a   (			self							:			List[Any]  , a_							:			Union[Iterator[str], Iterator[Iterator[str]]]  , a_							:			int = 80_00  , a_							:			bool = True  , )->       Any:



      """simple docstring"""

      UpperCAmelCase_    :     Union[str, Any]            =	trainers.UnigramTrainer(
          vocab_size=a_  , special_tokens=self.special_tokens_list  , show_progress=a_  , )

      self._tokenizer.train_from_iterator(a_  , trainer=a_			)

      self.add_unk_id()






 def 	a   (			self							:			Dict			)->       Union[str, Any]:



      """simple docstring"""

      UpperCAmelCase_    :     int            =	json.loads(self._tokenizer.to_str()			)

      UpperCAmelCase_    :     Any            =	self.special_tokens["""unk"""]["""id"""]

      UpperCAmelCase_    :     Tuple            =	Tokenizer.from_str(json.dumps(a_			)			)

