






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


snake_case    				=		logging.get_logger(__name__)

snake_case    				=		{'''vocab_file''': '''sentencepiece.model'''}

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

snake_case    				=		{
    '''google/rembert''': 256,
}


class  SCREAMING_SNAKE_CASE			(			UpperCamelCase__					):
     '''simple docstring'''


     UpperCamelCase_							:		List[Any]			=	VOCAB_FILES_NAMES
     UpperCamelCase_							:		Optional[Any]			=	PRETRAINED_VOCAB_FILES_MAP
     UpperCamelCase_							:		Any			=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


     def __init__(				self       :	Union[str, Any]					, UpperCAmelCase_       :	Any					, UpperCAmelCase_       :	Optional[int]=False					, UpperCAmelCase_       :	int=True					, UpperCAmelCase_       :	Tuple=True					, UpperCAmelCase_       :	Dict="[CLS]"					, UpperCAmelCase_       :	Optional[Any]="[SEP]"					, UpperCAmelCase_       :	int="[UNK]"					, UpperCAmelCase_       :	Dict="[SEP]"					, UpperCAmelCase_       :	Union[str, Any]="[PAD]"					, UpperCAmelCase_       :	Optional[Any]="[CLS]"					, UpperCAmelCase_       :	Dict="[MASK]"					, **UpperCAmelCase_       :	Optional[Any]					, ):
       super().__init__(
           do_lower_case=UpperCAmelCase_					, remove_space=UpperCAmelCase_					, keep_accents=UpperCAmelCase_					, bos_token=UpperCAmelCase_					, eos_token=UpperCAmelCase_					, unk_token=UpperCAmelCase_					, sep_token=UpperCAmelCase_					, pad_token=UpperCAmelCase_					, cls_token=UpperCAmelCase_					, mask_token=UpperCAmelCase_					, **UpperCAmelCase_					, )

       SCREAMING_SNAKE_CASE       :      Dict							=    do_lower_case
       SCREAMING_SNAKE_CASE       :      Optional[Any]							=    remove_space
       SCREAMING_SNAKE_CASE       :      Optional[Any]							=    keep_accents
       SCREAMING_SNAKE_CASE       :      List[Any]							=    vocab_file

       SCREAMING_SNAKE_CASE       :      List[str]							=    spm.SentencePieceProcessor()
       self.sp_model.Load(UpperCAmelCase_      )


     @property
     def 				_A       (				self       :	int      ):
       return len(self.sp_model      )


     def 				_A       (				self       :	List[str]      ):
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    {self.convert_ids_to_tokens(UpperCAmelCase_      ): i for i in range(self.vocab_size      )}
       vocab.update(self.added_tokens_encoder      )
       return vocab


     def __getstate__(				self       :	Any      ):
       SCREAMING_SNAKE_CASE       :      str							=    self.__dict__.copy()
       SCREAMING_SNAKE_CASE       :      Optional[Any]							=    None
       return state


     def __setstate__(				self       :	Any					, UpperCAmelCase_       :	Any      ):
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    d
       SCREAMING_SNAKE_CASE       :      List[str]							=    spm.SentencePieceProcessor()
       self.sp_model.Load(self.vocab_file      )


     def 				_A       (				self       :	Optional[Any]					, UpperCAmelCase_       :	Tuple					, UpperCAmelCase_       :	int=False      ):
       SCREAMING_SNAKE_CASE       :      int							=    self.sp_model.EncodeAsPieces(UpperCAmelCase_      )
       return pieces


     def 				_A       (				self       :	int					, UpperCAmelCase_       :	Any      ):
       return self.sp_model.PieceToId(UpperCAmelCase_      )


     def 				_A       (				self       :	List[str]					, UpperCAmelCase_       :	Dict      ):
       return self.sp_model.IdToPiece(UpperCAmelCase_      )


     def 				_A       (				self       :	List[Any]					, UpperCAmelCase_       :	int      ):
       SCREAMING_SNAKE_CASE       :      List[str]							=    self.sp_model.decode_pieces(UpperCAmelCase_      )
       return out_string


     def 				_A       (				self       :	int					, UpperCAmelCase_       :	Dict					, UpperCAmelCase_       :	List[str] = None      ):
       SCREAMING_SNAKE_CASE       :      List[str]							=    [self.sep_token_id]
       SCREAMING_SNAKE_CASE       :      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       :	Dict					, UpperCAmelCase_       :	List[Any]					, UpperCAmelCase_       :	Tuple = None					, UpperCAmelCase_       :	int = False      ):

       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(UpperCAmelCase_      )) + [1] + ([0] * len(UpperCAmelCase_      )) + [1]
       return [1] + ([0] * len(UpperCAmelCase_      )) + [1]


     def 				_A       (				self       :	Tuple					, UpperCAmelCase_       :	List[Any]					, UpperCAmelCase_       :	Tuple = None      ):
       SCREAMING_SNAKE_CASE       :      List[Any]							=    [self.sep_token_id]
       SCREAMING_SNAKE_CASE       :      Optional[int]							=    [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       :	Tuple					, UpperCAmelCase_       :	Tuple					, UpperCAmelCase_       :	int = None      ):
       if not os.path.isdir(UpperCAmelCase_      ):
         logger.error("Vocabulary path ({}) should be a directory".format(UpperCAmelCase_      )      )
         return
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    os.path.join(
           UpperCAmelCase_					, (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]      )

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

       return (out_vocab_file,)














def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






  SCREAMING_SNAKE_CASE       :      Dict							=    [0] * len(lowercase				)
  SCREAMING_SNAKE_CASE       :      List[str]							=    []
  SCREAMING_SNAKE_CASE       :      Optional[Any]							=    []
  SCREAMING_SNAKE_CASE       :      Any							=    0

  for values in graph.values():
    for i in values:
      indegree[i] += 1

  for i in range(len(lowercase				)				):
    if indegree[i] == 0:
      queue.append(lowercase				)

  while queue:
    SCREAMING_SNAKE_CASE       :      Optional[Any]							=    queue.pop(0				)
    cnt += 1
    topo.append(lowercase				)
    for x in graph[vertex]:
      indegree[x] -= 1
      if indegree[x] == 0:
        queue.append(lowercase				)

  if cnt != len(lowercase				):
    print("Cycle exists"				)
  else:
    print(lowercase				)


# Adjacency List of Graph
snake_case    				=		{0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}

topological_sort(graph)






