'''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 (					__UpperCAmelCase  :					Optional[int]			)							->	Tuple:
  lowercase				:							List[str]									=   Queue()
  lowercase				:							List[Any]									=   [False] * len(__UpperCAmelCase			)
  lowercase				:							List[Any]									=   [-1] * len(__UpperCAmelCase			)

  def bfs():
    while not queue.empty():
      lowercase				:							Union[str, Any]									=   queue.get()
      lowercase				:							List[Any]									=   True

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

        if color[neighbour] == -1:
          lowercase				:							List[str]									=   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			)
      lowercase				:							List[Any]									=   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'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


_A		:      Optional[Any]						   ={
    '''configuration_mobilevitv2''': [
        '''MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''MobileViTV2Config''',
        '''MobileViTV2OnnxConfig''',
    ],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:      Union[str, Any]						   =[
     '''MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''MobileViTV2ForImageClassification''',
     '''MobileViTV2ForSemanticSegmentation''',
     '''MobileViTV2Model''',
     '''MobileViTV2PreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_mobilevitva import (
     MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     MobileViTVaConfig,
     MobileViTVaOnnxConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mobilevitva import (
      MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
      MobileViTVaForImageClassification,
      MobileViTVaForSemanticSegmentation,
      MobileViTVaModel,
      MobileViTVaPreTrainedModel,
  )

else:
 import sys

 _A		:      Tuple						   =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)