





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_rembert import RemBertTokenizer
else:
      SCREAMING_SNAKE_CASE_						       =	None

SCREAMING_SNAKE_CASE_						       =	logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_						       =	{"""vocab_file""": """sentencepiece.model""", """tokenizer_file""": """tokenizer.json"""}

SCREAMING_SNAKE_CASE_						       =	{
    """vocab_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/sentencepiece.model""",
    },
    """tokenizer_file""": {
        """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/tokenizer.json""",
    },
}

SCREAMING_SNAKE_CASE_						       =	{
    """google/rembert""": 2_5_6,
}

SCREAMING_SNAKE_CASE_						       =	"""▁"""

class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     __snake_case   :     Dict		     =      VOCAB_FILES_NAMES
     __snake_case   :     Any		     =      PRETRAINED_VOCAB_FILES_MAP
     __snake_case   :     List[Any]		     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __snake_case   :     Dict		     =      RemBertTokenizer






     def __init__(							self						:   Any						,lowerCamelCase__						:   Any=None						,lowerCamelCase__						:   Optional[int]=None						,lowerCamelCase__						:   Union[str, Any]=True						,lowerCamelCase__						:   List[str]=True						,lowerCamelCase__						:   Optional[Any]=False						,lowerCamelCase__						:   Dict="[CLS]"						,lowerCamelCase__						:   Tuple="[SEP]"						,lowerCamelCase__						:   Optional[int]="<unk>"						,lowerCamelCase__						:   Union[str, Any]="[SEP]"						,lowerCamelCase__						:   Dict="<pad>"						,lowerCamelCase__						:   int="[CLS]"						,lowerCamelCase__						:   int="[MASK]"						,**lowerCamelCase__						:   Union[str, Any]						,)					->		Tuple:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						AddedToken(lowerCamelCase__						,lstrip=lowerCamelCase__						,rstrip=lowerCamelCase__	) if isinstance(lowerCamelCase__						,lowerCamelCase__	) else mask_token

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

           SCREAMING_SNAKE_CASE		=						do_lower_case
           SCREAMING_SNAKE_CASE		=						remove_space
           SCREAMING_SNAKE_CASE		=						keep_accents
           SCREAMING_SNAKE_CASE		=						vocab_file
           SCREAMING_SNAKE_CASE		=						False if not self.vocab_file else True






     def     SCREAMING_SNAKE_CASE__  (							self						:   int						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   Optional[List[int]] = None	)					->		List[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[self.sep_token_id]
           SCREAMING_SNAKE_CASE		=						[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     SCREAMING_SNAKE_CASE__  (							self						:   Dict						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   Optional[List[int]] = None						,lowerCamelCase__						:   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(lowerCamelCase__	)) + [1] + ([0] * len(lowerCamelCase__	)) + [1]
           return [1] + ([0] * len(lowerCamelCase__	)) + [1]






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   Optional[List[int]] = None	)					->		List[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[self.sep_token_id]
           SCREAMING_SNAKE_CASE		=						[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     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]						,lowerCamelCase__						:   str						,lowerCamelCase__						:   Optional[str] = None	)					->		Tuple[str]:




           '''simple docstring'''


           if not os.path.isdir(lowerCamelCase__	):
                 logger.error("""Vocabulary path ({}) should be a directory""".format(lowerCamelCase__	)	)
                 return
           SCREAMING_SNAKE_CASE		=						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,)









def        __lowercase       (				_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )			->       int:


      '''simple docstring'''


      if index == number_of_items:
            return 0
      SCREAMING_SNAKE_CASE		=						0
      SCREAMING_SNAKE_CASE		=						0
      SCREAMING_SNAKE_CASE		=						knapsack(_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						index + 1     )
      if weights[index] <= max_weight:
            SCREAMING_SNAKE_CASE		=						values[index] + knapsack(
                _SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE			,						max_weight - weights[index]			,						index + 1     )
      return max(_SCREAMING_SNAKE_CASE			,						_SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
      import doctest

      doctest.testmod()


