




'''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 			_UpperCamelCase (_lowerCamelCase							:     int	)->   int:




     '''simple docstring'''





     __snake_case    					=  Queue()
     __snake_case    					=  [False] * len(_lowerCamelCase	)
     __snake_case    					=  [-1] * len(_lowerCamelCase	)

     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(_lowerCamelCase	)

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

          return True

     for i in range(len(_lowerCamelCase	)	):
          if not visited[i]:
               queue.put(_lowerCamelCase	)
               __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]}))












'''simple docstring'''



import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


UpperCAmelCase_       :  int      =		logging.get_logger(__name__)





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  None:



            '''simple docstring'''




            warnings.warn(
                '''The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
                ''' Please use MaskFormerImageProcessor instead.'''    ,  __SCREAMING_SNAKE_CASE    ,  )
            super().__init__(*__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )






