


"""simple docstring"""


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


__snake_case       							=    logging.get_logger(__name__)

__snake_case       							=    {
    "microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}
class snake_case      (  _UpperCamelCase):
		__UpperCamelCase           =			'cvt'







		def __init__(					self      :       List[Any]    ,   a__      :       List[str]=3    ,   a__      :       List[str]=[7, 3, 3]    ,   a__      :       List[Any]=[4, 2, 2]    ,   a__      :       str=[2, 1, 1]    ,   a__      :       str=[64, 1_92, 3_84]    ,   a__      :       Optional[int]=[1, 3, 6]    ,   a__      :       str=[1, 2, 10]    ,   a__      :       str=[4.0, 4.0, 4.0]    ,   a__      :       Optional[int]=[0.0, 0.0, 0.0]    ,   a__      :       Any=[0.0, 0.0, 0.0]    ,   a__      :       Tuple=[0.0, 0.0, 0.1]    ,   a__      :       Optional[int]=[True, True, True]    ,   a__      :       Optional[int]=[False, False, True]    ,   a__      :       Any=["dw_bn", "dw_bn", "dw_bn"]    ,   a__      :       int=[3, 3, 3]    ,   a__      :       Any=[1, 1, 1]    ,   a__      :       Any=[2, 2, 2]    ,   a__      :       List[Any]=[1, 1, 1]    ,   a__      :       Dict=[1, 1, 1]    ,   a__      :       Tuple=0.0_2    ,   a__      :       str=1E-1_2    ,   **a__      :       str    ,   )       ->						Optional[int]:





						'''simple docstring'''







						super().__init__(**a__		)
						_A					  =			num_channels
						_A					  =			patch_sizes
						_A					  =			patch_stride
						_A					  =			patch_padding
						_A					  =			embed_dim
						_A					  =			num_heads
						_A					  =			depth
						_A					  =			mlp_ratio
						_A					  =			attention_drop_rate
						_A					  =			drop_rate
						_A					  =			drop_path_rate
						_A					  =			qkv_bias
						_A					  =			cls_token
						_A					  =			qkv_projection_method
						_A					  =			kernel_qkv
						_A					  =			padding_kv
						_A					  =			stride_kv
						_A					  =			padding_q
						_A					  =			stride_q
						_A					  =			initializer_range
						_A					  =			layer_norm_eps



"""simple docstring"""


def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase     ,			__lowercase   )	->	str:
				# Return True if there is node that has not iterated.
				_A					  =			[False] * len(__lowercase   )
				_A					  =			[]
				queue.append(__lowercase   )
				_A					  =			True

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

				return visited[t]






def      a__ (				__lowercase     ,			__lowercase     ,			__lowercase   )	->	int:
				# This array is filled by BFS and to store path
				_A					  =			[-1] * (len(__lowercase   ))
				_A					  =			0
				while bfs(__lowercase     ,			__lowercase     ,			__lowercase     ,			__lowercase   ):
								_A					  =			float("Inf"   )
								_A					  =			sink

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

								max_flow += path_flow
								_A					  =			sink

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


a_       							=    [
    [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],
]

a_							,     a_       							=    0, 5




print(ford_fulkerson(graph, source, sink))