


"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase__  							=logging.get_logger(__name__)

UpperCAmelCase__  							={
    '''shi-labs/dinat-mini-in1k-224''': '''https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json''',
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}





class    lowerCamelCase__						(		UpperCamelCase__			,   UpperCamelCase__    ):
      a :     List[Any]											=		"""dinat"""

      a :     Dict											=		{
          """num_attention_heads""": """num_heads""",
          """num_hidden_layers""": """num_layers""",
      }
      def __init__(		self	:	List[Any]      ,       A_	:	Tuple=4      ,       A_	:	Dict=3      ,       A_	:	Any=6_4      ,       A_	:	Optional[int]=[3, 4, 6, 5]      ,       A_	:	List[Any]=[2, 4, 8, 1_6]      ,       A_	:	str=7      ,       A_	:	Optional[Any]=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]      ,       A_	:	Union[str, Any]=3.0      ,       A_	:	Any=True      ,       A_	:	List[str]=0.0      ,       A_	:	Union[str, Any]=0.0      ,       A_	:	Union[str, Any]=0.1      ,       A_	:	List[Any]="gelu"      ,       A_	:	Union[str, Any]=0.02      ,       A_	:	Optional[int]=1e-5      ,       A_	:	Optional[int]=0.0      ,       A_	:	int=None      ,       A_	:	int=None      ,       **A_	:	Optional[int]      ,       ):






       '''simple docstring'''


       super().__init__(**A_							)

       __lowercase									=	patch_size
       __lowercase									=	num_channels
       __lowercase									=	embed_dim
       __lowercase									=	depths
       __lowercase									=	len(A_							)
       __lowercase									=	num_heads
       __lowercase									=	kernel_size
       __lowercase									=	dilations
       __lowercase									=	mlp_ratio
       __lowercase									=	qkv_bias
       __lowercase									=	hidden_dropout_prob
       __lowercase									=	attention_probs_dropout_prob
       __lowercase									=	drop_path_rate
       __lowercase									=	hidden_act
       __lowercase									=	layer_norm_eps
       __lowercase									=	initializer_range
       # we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
       # this indicates the channel dimension after the last stage of the model
       __lowercase									=	int(embed_dim * 2 ** (len(A_							) - 1)							)
       __lowercase									=	layer_scale_init_value
       __lowercase									=	["""stem"""] + [F'''stage{idx}''' for idx in range(1      ,       len(A_							) + 1							)]
       __lowercase							,		__lowercase									=	get_aligned_output_features_output_indices(
           out_features=A_      ,       out_indices=A_      ,       stage_names=self.stage_names							)






"""simple docstring"""

def lowerCAmelCase_      (				UpperCamelCase__	: Optional[Any]				,   UpperCamelCase__	: int				,   UpperCamelCase__	: Optional[Any]				,   UpperCamelCase__	: str ):






 """simple docstring"""







 __lowercase									=	[False] * len(UpperCamelCase__ )
 __lowercase									=	[]
 queue.append(UpperCamelCase__ )
 __lowercase									=	True

 while queue:
  __lowercase									=	queue.pop(0 )
  for ind in range(len(graph[u] ) ):
   if visited[ind] is False and graph[u][ind] > 0:
    queue.append(UpperCamelCase__ )
    __lowercase									=	True
    __lowercase									=	u

 return visited[t]


def lowerCAmelCase_      (				UpperCamelCase__	: str				,   UpperCamelCase__	: Any				,   UpperCamelCase__	: Optional[int] ):






 """simple docstring"""







 __lowercase									=	[-1] * (len(UpperCamelCase__ ))
 __lowercase									=	0
 while bfs(UpperCamelCase__				,   UpperCamelCase__				,   UpperCamelCase__				,   UpperCamelCase__ ):
  __lowercase									=	float("""Inf""" )
  __lowercase									=	sink

  while s != source:
   # Find the minimum value in select path
   __lowercase									=	min(UpperCamelCase__				,   graph[parent[s]][s] )
   __lowercase									=	parent[s]

  max_flow += path_flow
  __lowercase									=	sink

  while v != source:
   __lowercase									=	parent[v]
   graph[u][v] -= path_flow
   graph[v][u] += path_flow
   __lowercase									=	parent[v]
 return max_flow


UpperCAmelCase__  							=[
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

UpperCAmelCase__							,      UpperCAmelCase__  							=0, 5

print(ford_fulkerson(graph, source, sink))
