






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:
   snake_case    				=		None

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

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""",
    },
}

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

snake_case    				=		"""▁"""


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


     UpperCamelCase_							:		Tuple			=	VOCAB_FILES_NAMES
     UpperCamelCase_							:		Any			=	PRETRAINED_VOCAB_FILES_MAP
     UpperCamelCase_							:		List[str]			=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCamelCase_							:		Union[str, Any]			=	RemBertTokenizer


     def __init__(				self       :	Optional[Any]					, UpperCAmelCase_       :	Any=None					, UpperCAmelCase_       :	List[str]=None					, UpperCAmelCase_       :	Any=True					, UpperCAmelCase_       :	int=True					, UpperCAmelCase_       :	List[Any]=False					, UpperCAmelCase_       :	Union[str, Any]="[CLS]"					, UpperCAmelCase_       :	Tuple="[SEP]"					, UpperCAmelCase_       :	str="<unk>"					, UpperCAmelCase_       :	Tuple="[SEP]"					, UpperCAmelCase_       :	List[Any]="<pad>"					, UpperCAmelCase_       :	Optional[int]="[CLS]"					, UpperCAmelCase_       :	Optional[int]="[MASK]"					, **UpperCAmelCase_       :	int					, ):
       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE       :      Optional[int]							=    AddedToken(UpperCAmelCase_					, lstrip=UpperCAmelCase_					, rstrip=UpperCAmelCase_      ) if isinstance(UpperCAmelCase_					, UpperCAmelCase_      ) else mask_token

       super().__init__(
           UpperCAmelCase_					, tokenizer_file=UpperCAmelCase_					, 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       :      Optional[Any]							=    do_lower_case
       SCREAMING_SNAKE_CASE       :      int							=    remove_space
       SCREAMING_SNAKE_CASE       :      str							=    keep_accents
       SCREAMING_SNAKE_CASE       :      Optional[int]							=    vocab_file
       SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    False if not self.vocab_file else True


     def 				_A       (				self       :	Union[str, Any]					, UpperCAmelCase_       :	List[int]					, UpperCAmelCase_       :	Optional[List[int]] = None      ):
       SCREAMING_SNAKE_CASE       :      List[str]							=    [self.sep_token_id]
       SCREAMING_SNAKE_CASE       :      Dict							=    [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       :	Optional[Any]					, UpperCAmelCase_       :	List[int]					, UpperCAmelCase_       :	Optional[List[int]] = None					, UpperCAmelCase_       :	bool = 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       :	Union[str, Any]					, UpperCAmelCase_       :	List[int]					, UpperCAmelCase_       :	Optional[List[int]] = None      ):
       SCREAMING_SNAKE_CASE       :      Dict							=    [self.sep_token_id]
       SCREAMING_SNAKE_CASE       :      List[str]							=    [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       :	Any					, UpperCAmelCase_       :	str					, UpperCAmelCase_       :	Optional[str] = None      ):
       if not os.path.isdir(UpperCAmelCase_      ):
         logger.error("Vocabulary path ({}) should be a directory".format(UpperCAmelCase_      )      )
         return
       SCREAMING_SNAKE_CASE       :      Optional[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)






