




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


lowerCamelCase	:	int				=   logging.get_logger(__name__)

lowerCamelCase	:	List[str]				=   {'vocab_file': 'sentencepiece.model'}

lowerCamelCase	:	Any				=   {
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

lowerCamelCase	:	int				=   {
    'google/rembert': 2_5_6,
}




class 						__lowercase		(snake_case_							):




      """simple docstring"""





      _snake_case												=						VOCAB_FILES_NAMES
      _snake_case												=						PRETRAINED_VOCAB_FILES_MAP
      _snake_case												=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

      def __init__(				self    ,				A    ,				A=False    ,				A=True    ,				A=True    ,				A="[CLS]"    ,				A="[SEP]"    ,				A="[UNK]"    ,				A="[SEP]"    ,				A="[PAD]"    ,				A="[CLS]"    ,				A="[MASK]"    ,				**A    ,				)		->    List[Any]:
         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    ,				)

         snake_case				:    List[str]           =	do_lower_case
         snake_case				:    Dict           =	remove_space
         snake_case				:    Optional[int]           =	keep_accents
         snake_case				:    Union[str, Any]           =	vocab_file

         snake_case				:    Any           =	spm.SentencePieceProcessor()
         self.sp_model.Load(A     )

      @property
      def      UpperCAmelCase				(				self     )		->    List[Any]:
         return len(self.sp_model     )

      def      UpperCAmelCase				(				self     )		->    Optional[Any]:
         snake_case				:    List[Any]           =	{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     )		->    str:
         snake_case				:    Any           =	self.__dict__.copy()
         snake_case				:    Any           =	None
         return state

      def __setstate__(				self    ,				A     )		->    str:
         snake_case				:    List[str]           =	d
         snake_case				:    int           =	spm.SentencePieceProcessor()
         self.sp_model.Load(self.vocab_file     )

      def      UpperCAmelCase				(				self    ,				A    ,				A=False     )		->    List[str]:
         snake_case				:    Dict           =	self.sp_model.EncodeAsPieces(A     )
         return pieces

      def      UpperCAmelCase				(				self    ,				A     )		->    str:
         return self.sp_model.PieceToId(A     )

      def      UpperCAmelCase				(				self    ,				A     )		->    Dict:
         return self.sp_model.IdToPiece(A     )

      def      UpperCAmelCase				(				self    ,				A     )		->    str:
         snake_case				:    str           =	self.sp_model.decode_pieces(A     )
         return out_string

      def      UpperCAmelCase				(				self    ,				A    ,				A = None     )		->    List[int]:
         snake_case				:    Any           =	[self.sep_token_id]
         snake_case				:    Tuple           =	[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      UpperCAmelCase				(				self    ,				A    ,				A = None    ,				A = False     )		->    List[int]:





         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      UpperCAmelCase				(				self    ,				A    ,				A = None     )		->    List[int]:
         snake_case				:    Union[str, Any]           =	[self.sep_token_id]
         snake_case				:    Union[str, 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      UpperCAmelCase				(				self    ,				A    ,				A = None     )		->    Tuple[str]:





         if not os.path.isdir(A     ):
            logger.error("""Vocabulary path ({}) should be a directory""".format(A     )     )
            return
         snake_case				:    Optional[Any]           =	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,)







def 						SCREAMING_SNAKE_CASE__ (   )  ->       Dict:
   snake_case				:    Optional[int]           =	[]
   snake_case				:    Tuple           =	1

   while len(lowercase					) < 1E6:
      constant.append(str(lowercase					)					)
      i += 1

   snake_case				:    int           =	"""""".join(lowercase					)

   return (
       int(constant[0]					)
       * int(constant[9]					)
       * int(constant[99]					)
       * int(constant[999]					)
       * int(constant[9999]					)
       * int(constant[99999]					)
       * int(constant[999999]					)
   )


if __name__ == "__main__":
       print(solution())





