

'''simple docstring'''





# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.
from queue import Queue





def 			_lowercase    (      __UpperCamelCase     :		int ):
      snake_case__					=   Queue()
      snake_case__					=   [False] * len(__UpperCamelCase )
      snake_case__					=   [-1] * len(__UpperCamelCase )

      def bfs():
            while not queue.empty():
                  snake_case__					=   queue.get()
                  snake_case__					=   True

                  for neighbour in graph[u]:
                        if neighbour == u:
                              return False

                        if color[neighbour] == -1:
                              snake_case__					=   1 - color[u]
                              queue.put(__UpperCamelCase )

                        elif color[neighbour] == color[u]:
                              return False

            return True

      for i in range(len(__UpperCamelCase ) ):
            if not visited[i]:
                  queue.put(__UpperCamelCase )
                  snake_case__					=   0
                  if bfs() is False:
                        return False

      return True


if __name__ == "__main__":
       # Adjacency List of graph
       print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}))









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

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_reformer import ReformerTokenizer
else:
       lowerCAmelCase						:   Union[str, Any]										=    None


lowerCAmelCase						:   str										=    logging.get_logger(__name__)


lowerCAmelCase						:   Any										=    '''▁'''

lowerCAmelCase						:   Tuple										=    {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase						:   Optional[Any]										=    {
    '''vocab_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'''
        )
    },
    '''tokenizer_file''': {
        '''google/reformer-crime-and-punishment''': (
            '''https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'''
        )
    },
}

lowerCAmelCase						:   Union[str, Any]										=    {
    '''google/reformer-crime-and-punishment''': 52_4288,
}
class     SCREAMING_SNAKE_CASE__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     Union[str, Any]				    =       VOCAB_FILES_NAMES
       UpperCamelCase__ :     str				    =       PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase__ :     str				    =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase__ :     str				    =       ['''input_ids''', '''attention_mask''']
       UpperCamelCase__ :     Optional[Any]				    =       ReformerTokenizer

       def __init__(						self       :						List[str]    ,		lowerCAmelCase__       :						Tuple=None    ,		lowerCAmelCase__       :						Optional[Any]=None    ,		lowerCAmelCase__       :						Dict="</s>"    ,		lowerCAmelCase__       :						Tuple="<unk>"    ,		lowerCAmelCase__       :						Dict=[]    ,		**lowerCAmelCase__       :						Optional[Any]    ,		)			->    Dict:
             super().__init__(
                 lowerCAmelCase__    ,		tokenizer_file=lowerCAmelCase__    ,		eos_token=lowerCAmelCase__    ,		unk_token=lowerCAmelCase__    ,		additional_special_tokens=lowerCAmelCase__    ,		**lowerCAmelCase__    ,		)

             snake_case__					=   vocab_file
             snake_case__					=   False if not self.vocab_file else True

       def UpperCAmelCase_						(						self       :						int    ,		lowerCAmelCase__       :						str    ,		lowerCAmelCase__       :						Optional[str] = None							)			->    Tuple[str]:
             if not self.can_save_slow_tokenizer:
                   raise ValueError(
                       """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
                       """tokenizer."""							)

             if not os.path.isdir(lowerCAmelCase__							):
                   logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''							)
                   return
             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,)






