
"""simple docstring"""







import os
from shutil import copyfile
from typing import List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase_         =       logging.get_logger(__name__)

lowercase_         =       {"vocab_file": "sentencepiece.model"}

lowercase_         =       {
    "vocab_file": {
        "google/rembert": "https://huggingface.co/google/rembert/resolve/main/sentencepiece.model",
    },
}

lowercase_         =       {
    "google/rembert": 256,
}



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




 UpperCamelCase_    :  int					 =     VOCAB_FILES_NAMES
 UpperCamelCase_    :  List[str]					 =     PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase_    :  Any					 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




 def __init__(			self							:			List[str]  , a_							:			List[str]  , a_							:			str=False  , a_							:			List[str]=True  , a_							:			Dict=True  , a_							:			List[Any]="[CLS]"  , a_							:			List[Any]="[SEP]"  , a_							:			Any="[UNK]"  , a_							:			Any="[SEP]"  , a_							:			int="[PAD]"  , a_							:			Optional[int]="[CLS]"  , a_							:			List[Any]="[MASK]"  , **a_							:			List[str]  , )->       List[Any]:



      """simple docstring"""

      super().__init__(
          do_lower_case=a_  , remove_space=a_  , keep_accents=a_  , bos_token=a_  , eos_token=a_  , unk_token=a_  , sep_token=a_  , pad_token=a_  , cls_token=a_  , mask_token=a_  , **a_  , )

      UpperCAmelCase_    :     Any            =	do_lower_case
      UpperCAmelCase_    :     Any            =	remove_space
      UpperCAmelCase_    :     Optional[Any]            =	keep_accents
      UpperCAmelCase_    :     Union[str, Any]            =	vocab_file

      UpperCAmelCase_    :     List[Any]            =	spm.SentencePieceProcessor()
      self.sp_model.Load(a_			)




 @property
 def 	a   (			self							:			Optional[Any]			)->       Dict:



      """simple docstring"""

      return len(self.sp_model			)




 def 	a   (			self							:			int			)->       List[str]:



      """simple docstring"""

      UpperCAmelCase_    :     Dict            =	{self.convert_ids_to_tokens(a_			): i for i in range(self.vocab_size			)}
      vocab.update(self.added_tokens_encoder			)
      return vocab




 def __getstate__(			self							:			Tuple			)->       Dict:



      """simple docstring"""

      UpperCAmelCase_    :     List[Any]            =	self.__dict__.copy()
      UpperCAmelCase_    :     Optional[Any]            =	None
      return state




 def __setstate__(			self							:			List[str]  , a_							:			str			)->       int:



      """simple docstring"""

      UpperCAmelCase_    :     str            =	d
      UpperCAmelCase_    :     List[Any]            =	spm.SentencePieceProcessor()
      self.sp_model.Load(self.vocab_file			)




 def 	a   (			self							:			List[str]  , a_							:			int  , a_							:			Any=False			)->       Any:



      """simple docstring"""

      UpperCAmelCase_    :     Any            =	self.sp_model.EncodeAsPieces(a_			)
      return pieces




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



      """simple docstring"""

      return self.sp_model.PieceToId(a_			)




 def 	a   (			self							:			Optional[Any]  , a_							:			Dict			)->       List[Any]:



      """simple docstring"""

      return self.sp_model.IdToPiece(a_			)




 def 	a   (			self							:			Union[str, Any]  , a_							:			int			)->       List[str]:



      """simple docstring"""

      UpperCAmelCase_    :     Optional[Any]            =	self.sp_model.decode_pieces(a_			)
      return out_string




 def 	a   (			self							:			int  , a_							:			List[int]  , a_							:			Optional[List[int]] = None			)->       List[int]:



      """simple docstring"""

      UpperCAmelCase_    :     int            =	[self.sep_token_id]
      UpperCAmelCase_    :     List[str]            =	[self.cls_token_id]
      if token_ids_a is None:
           return cls + token_ids_a + sep
      return cls + token_ids_a + sep + token_ids_a + sep




 def 	a   (			self							:			List[Any]  , a_							:			List[int]  , a_							:			Optional[List[int]] = None  , a_							:			bool = False			)->       List[int]:



      """simple docstring"""

      if already_has_special_tokens:
           if token_ids_a is not None:
                raise ValueError(
                    """You should not supply a second sequence if the provided sequence of """
                    """ids is already formatted with special tokens for the model."""			)
           return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

      if token_ids_a is not None:
           return [1] + ([0] * len(a_			)) + [1] + ([0] * len(a_			)) + [1]
      return [1] + ([0] * len(a_			)) + [1]




 def 	a   (			self							:			List[str]  , a_							:			List[int]  , a_							:			Optional[List[int]] = None			)->       List[int]:



      """simple docstring"""

      UpperCAmelCase_    :     List[Any]            =	[self.sep_token_id]
      UpperCAmelCase_    :     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			) * [0] + len(token_ids_a + sep			) * [1]






 def 	a   (			self							:			List[str]  , a_							:			str  , a_							:			Optional[str] = None			)->       Tuple[str]:



      """simple docstring"""

      if not os.path.isdir(a_			):
           logger.error("""Vocabulary path ({}) should be a directory""".format(a_			)			)
           return
      UpperCAmelCase_    :     int            =	os.path.join(
          a_  , (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]			)

      if os.path.abspath(self.vocab_file			) != os.path.abspath(a_			):
           copyfile(self.vocab_file  , a_			)

      return (out_vocab_file,)



"""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()

