






from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_		:		Any		     =			logging.get_logger(__name__)

A_		:		List[str]		     =			{
    'google/vivit-b-16x2-kinetics400': (
        'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'
    ),
    # See all Vivit models at https://huggingface.co/models?filter=vivit
}




class     _lowerCAmelCase(	UpperCAmelCase_ ):





       """simple docstring"""







       a    :		List[Any]									='''vivit'''





       def __init__( self  ,      _lowerCamelCase=2_2_4  ,      _lowerCamelCase=3_2  ,      _lowerCamelCase=[2, 1_6, 1_6]  ,      _lowerCamelCase=3  ,      _lowerCamelCase=7_6_8  ,      _lowerCamelCase=1_2  ,      _lowerCamelCase=1_2  ,      _lowerCamelCase=3_0_7_2  ,      _lowerCamelCase="gelu_fast"  ,      _lowerCamelCase=0.0  ,      _lowerCamelCase=0.0  ,      _lowerCamelCase=0.0_2  ,      _lowerCamelCase=1e-06  ,      _lowerCamelCase=True  ,      **_lowerCamelCase  ,      ):
         UpperCamelCase_: int   				=    hidden_size
         UpperCamelCase_: List[str]   				=    num_hidden_layers
         UpperCamelCase_: Union[str, Any]   				=    num_attention_heads
         UpperCamelCase_: Optional[int]   				=    intermediate_size
         UpperCamelCase_: int   				=    hidden_act
         UpperCamelCase_: Any   				=    hidden_dropout_prob
         UpperCamelCase_: int   				=    attention_probs_dropout_prob
         UpperCamelCase_: List[str]   				=    initializer_range
         UpperCamelCase_: Optional[Any]   				=    layer_norm_eps

         UpperCamelCase_: Dict   				=    image_size
         UpperCamelCase_: Optional[int]   				=    num_frames
         UpperCamelCase_: Optional[Any]   				=    tubelet_size
         UpperCamelCase_: List[str]   				=    num_channels
         UpperCamelCase_: Optional[int]   				=    qkv_bias

         super().__init__(**_lowerCamelCase							)







# 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.

def   snake_case (UpperCAmelCase__  )	->    List[str]:
  UpperCamelCase_: int   				=    [False] * len(UpperCAmelCase__  )
  UpperCamelCase_: Any   				=    [-1] * len(UpperCAmelCase__  )

  def dfs(UpperCAmelCase__     ,   UpperCAmelCase__  ):
    UpperCamelCase_: Tuple   				=    True
    UpperCamelCase_: Optional[int]   				=    c
    for u in graph[v]:
      if not visited[u]:
        dfs(UpperCAmelCase__     ,   1 - c  )

  for i in range(len(UpperCAmelCase__  )  ):
    if not visited[i]:
      dfs(UpperCAmelCase__     ,   0  )

  for i in range(len(UpperCAmelCase__  )  ):
    for j in graph[i]:
      if color[i] == color[j]:
        return False

  return True


# Adjacency list of graph
A_		:		Dict		     =			{0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2], 4: []}
print(check_bipartite_dfs(graph))