



"""simple docstring"""
__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],
]
def    A_  (			_lowercase,					_lowercase,					_lowercase,					_lowercase	):







						'''simple docstring'''


						snake_case_ :int						=			[False] * len(_lowercase	)
						snake_case_ :int						=			[s]
						snake_case_ :Tuple						=			True

						while queue:
												snake_case_ :int						=			queue.pop(0	)
												for ind in range(len(graph[u]	)	):
																		if visited[ind] is False and graph[u][ind] > 0:
																								queue.append(_lowercase	)
																								snake_case_ :List[Any]						=			True
																								snake_case_ :Optional[Any]						=			u

						return visited[t]
def    A_  (			_lowercase,					_lowercase,					_lowercase	):







						'''simple docstring'''


						snake_case_ :Union[str, Any]						=			[-1] * (len(_lowercase	))
						snake_case_ :Optional[int]						=			0
						snake_case_ :Any						=			[]
						snake_case_ :List[str]						=			[i[:] for i in graph]  # Record original cut, copy.
						while bfs(_lowercase,					_lowercase,					_lowercase,					_lowercase	):
												snake_case_ :Optional[Any]						=			float("""Inf"""	)
												snake_case_ :Tuple						=			sink

												while s != source:
																		# Find the minimum value in select path
																		snake_case_ :Optional[int]						=			min(_lowercase,					graph[parent[s]][s]	)
																		snake_case_ :Dict						=			parent[s]

												max_flow += path_flow
												snake_case_ :List[str]						=			sink

												while v != source:
																		snake_case_ :Optional[int]						=			parent[v]
																		graph[u][v] -= path_flow
																		graph[v][u] += path_flow
																		snake_case_ :str						=			parent[v]

						for i in range(len(_lowercase	)	):
												for j in range(len(graph[0]	)	):
																		if graph[i][j] == 0 and temp[i][j] > 0:
																								res.append((i, j)	)

						return res


if __name__ == "__main__":
						print(mincut(test_graph, source=0, sink=5))





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__a      =				{
    "configuration_altclip": [
        "ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AltCLIPConfig",
        "AltCLIPTextConfig",
        "AltCLIPVisionConfig",
    ],
    "processing_altclip": ["AltCLIPProcessor"],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				[
						    "ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "AltCLIPPreTrainedModel",
						    "AltCLIPModel",
						    "AltCLIPTextModel",
						    "AltCLIPVisionModel",
						]


if TYPE_CHECKING:
						from .configuration_altclip import (
						    ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    AltCLIPConfig,
						    AltCLIPTextConfig,
						    AltCLIPVisionConfig,
						)
						from .processing_altclip import AltCLIPProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_altclip import (
												    ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    AltCLIPModel,
												    AltCLIPPreTrainedModel,
												    AltCLIPTextModel,
												    AltCLIPVisionModel,
												)


else:
						import sys

						__a      =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
