






class      lowercase__    :







  def __init__(	self    ,						_lowercase    ,						_lowercase    ,						_lowercase						):
       lowerCAmelCase_					:       List[Any]    =		None
       lowerCAmelCase_					:       List[Any]    =		None
       lowerCAmelCase_					:       int    =		graph

       self._normalize_graph(_lowercase    ,						_lowercase						)
       lowerCAmelCase_					:       str    =		len(_lowercase						)
       lowerCAmelCase_					:       Dict    =		None







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase						):
       if sources is int:
            lowerCAmelCase_					:       Any    =		[sources]
       if sinks is int:
            lowerCAmelCase_					:       List[str]    =		[sinks]

       if len(_lowercase						) == 0 or len(_lowercase						) == 0:
            return

       lowerCAmelCase_					:       List[Any]    =		sources[0]
       lowerCAmelCase_					:       List[Any]    =		sinks[0]

       # make fake vertex if there are more
       # than one source or sink
       if len(_lowercase						) > 1 or len(_lowercase						) > 1:
            lowerCAmelCase_					:       Optional[Any]    =		0
            for i in sources:
                 max_input_flow += sum(self.graph[i]						)

            lowerCAmelCase_					:       Union[str, Any]    =		len(self.graph						) + 1
            for room in self.graph:
                 room.insert(0    ,						0						)
            self.graph.insert(0    ,						[0] * size						)
            for i in sources:
                 lowerCAmelCase_					:       List[Any]    =		max_input_flow
            lowerCAmelCase_					:       List[Any]    =		0

            lowerCAmelCase_					:       Any    =		len(self.graph						) + 1
            for room in self.graph:
                 room.append(0						)
            self.graph.append([0] * size						)
            for i in sinks:
                 lowerCAmelCase_					:       List[Any]    =		max_input_flow
            lowerCAmelCase_					:       str    =		size - 1







  def 	UpperCAmelCase__		(	self						):
       if self.maximum_flow_algorithm is None:
            raise Exception("""You need to set maximum flow algorithm before."""						)
       if self.source_index is None or self.sink_index is None:
            return 0

       self.maximum_flow_algorithm.execute()
       return self.maximum_flow_algorithm.getMaximumFlow()







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       lowerCAmelCase_					:       List[str]    =		algorithm(self						)





class      lowercase__    :







  def __init__(	self    ,						_lowercase						):
       lowerCAmelCase_					:       Optional[Any]    =		flow_network
       lowerCAmelCase_					:       List[Any]    =		flow_network.verticesCount
       lowerCAmelCase_					:       str    =		flow_network.sourceIndex
       lowerCAmelCase_					:       Union[str, Any]    =		flow_network.sinkIndex
       # it's just a reference, so you shouldn't change
       # it in your algorithms, use deep copy before doing that
       lowerCAmelCase_					:       Optional[int]    =		flow_network.graph
       lowerCAmelCase_					:       List[str]    =		False







  def 	UpperCAmelCase__		(	self						):
       if not self.executed:
            self._algorithm()
            lowerCAmelCase_					:       Dict    =		True







  def 	UpperCAmelCase__		(	self						):
       pass





class      lowercase__    (							A_  ):







  def __init__(	self    ,						_lowercase						):
       super().__init__(_lowercase						)
       # use this to save your result
       lowerCAmelCase_					:       str    =		-1







  def 	UpperCAmelCase__		(	self						):
       if not self.executed:
            raise Exception("""You should execute algorithm before using its result!"""						)

       return self.maximum_flow





class      lowercase__    (							A_  ):







  def __init__(	self    ,						_lowercase						):
       super().__init__(_lowercase						)

       lowerCAmelCase_					:       Any    =		[[0] * self.verticies_count for i in range(self.verticies_count						)]

       lowerCAmelCase_					:       str    =		[0] * self.verticies_count
       lowerCAmelCase_					:       int    =		[0] * self.verticies_count







  def 	UpperCAmelCase__		(	self						):
       lowerCAmelCase_					:       List[Any]    =		self.verticies_count

       # push some substance to graph
       for nextvertex_index, bandwidth in enumerate(self.graph[self.source_index]						):
            self.preflow[self.source_index][nextvertex_index] += bandwidth
            self.preflow[nextvertex_index][self.source_index] -= bandwidth
            self.excesses[nextvertex_index] += bandwidth

       # Relabel-to-front selection rule
       lowerCAmelCase_					:       Any    =		[
           i
           for i in range(self.verticies_count						)
           if i != self.source_index and i != self.sink_index
       ]

       # move through list
       lowerCAmelCase_					:       int    =		0
       while i < len(_lowercase						):
            lowerCAmelCase_					:       List[Any]    =		vertices_list[i]
            lowerCAmelCase_					:       Any    =		self.heights[vertex_index]
            self.process_vertex(_lowercase						)
            if self.heights[vertex_index] > previous_height:
                 # if it was relabeled, swap elements
                 # and start from 0 index
                 vertices_list.insert(0    ,						vertices_list.pop(_lowercase						)						)
                 lowerCAmelCase_					:       Optional[Any]    =		0
            else:
                 i += 1

       lowerCAmelCase_					:       Tuple    =		sum(self.preflow[self.source_index]						)







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       while self.excesses[vertex_index] > 0:
            for neighbour_index in range(self.verticies_count						):
                 # if it's neighbour and current vertex is higher
                 if (
                     self.graph[vertex_index][neighbour_index]
                     - self.preflow[vertex_index][neighbour_index]
                     > 0
                     and self.heights[vertex_index] > self.heights[neighbour_index]
                 ):
                      self.push(_lowercase    ,						_lowercase						)

            self.relabel(_lowercase						)







  def 	UpperCAmelCase__		(	self    ,						_lowercase    ,						_lowercase						):
       lowerCAmelCase_					:       Union[str, Any]    =		min(
           self.excesses[from_index]    ,						self.graph[from_index][to_index] - self.preflow[from_index][to_index]    ,						)
       self.preflow[from_index][to_index] += preflow_delta
       self.preflow[to_index][from_index] -= preflow_delta
       self.excesses[from_index] -= preflow_delta
       self.excesses[to_index] += preflow_delta







  def 	UpperCAmelCase__		(	self    ,						_lowercase						):
       lowerCAmelCase_					:       Any    =		None
       for to_index in range(self.verticies_count						):
            if (
                self.graph[vertex_index][to_index]
                - self.preflow[vertex_index][to_index]
                > 0
            ) and (min_height is None or self.heights[to_index] < min_height):
                 lowerCAmelCase_					:       Dict    =		self.heights[to_index]

       if min_height is not None:
            lowerCAmelCase_					:       str    =		min_height + 1


if __name__ == "__main__":
      UpperCAmelCase_					:   str 							=						[0]
      UpperCAmelCase_					:   Optional[Any] 							=						[3]
      # graph = [
      #     [0, 0, 4, 6, 0, 0],
      #     [0, 0, 5, 2, 0, 0],
      #     [0, 0, 0, 0, 4, 4],
      #     [0, 0, 0, 0, 6, 6],
      #     [0, 0, 0, 0, 0, 0],
      #     [0, 0, 0, 0, 0, 0],
      # ]
      UpperCAmelCase_					:   Union[str, Any] 							=						[[0, 7, 0, 0], [0, 0, 6, 0], [0, 0, 0, 8], [9, 0, 0, 0]]

      # prepare our network
      UpperCAmelCase_					:   List[str] 							=						FlowNetwork(graph, entrances, exits)
      # set algorithm
      flow_network.set_maximum_flow_algorithm(PushRelabelExecutor)
      # and calculate
      UpperCAmelCase_					:   Optional[int] 							=						flow_network.find_maximum_flow()

      print(F"""maximum flow is {maximum_flow}""")







from typing import TYPE_CHECKING

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


UpperCAmelCase_					:   Dict 							=						{
    """configuration_poolformer""": [
        """POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """PoolFormerConfig""",
        """PoolFormerOnnxConfig""",
    ]
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCAmelCase_					:   Union[str, Any] 							=						["""PoolFormerFeatureExtractor"""]
      UpperCAmelCase_					:   str 							=						["""PoolFormerImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCAmelCase_					:   List[str] 							=						[
          """POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """PoolFormerForImageClassification""",
          """PoolFormerModel""",
          """PoolFormerPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_poolformer import (
          POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          PoolFormerConfig,
          PoolFormerOnnxConfig,
      )

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_poolformer import PoolFormerFeatureExtractor
            from .image_processing_poolformer import PoolFormerImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_poolformer import (
                POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                PoolFormerForImageClassification,
                PoolFormerModel,
                PoolFormerPreTrainedModel,
            )


else:
      import sys

      UpperCAmelCase_					:   Optional[Any] 							=						_LazyModule(__name__, globals()["""__file__"""], _import_structure)
