



"""simple docstring"""






class     UpperCAmelCase    :



   def __init__(       self    :	str							,       __lowerCamelCase    :	Optional[int]							,       __lowerCamelCase    :	Dict							,       __lowerCamelCase    :	Union[str, Any]				):



     """simple docstring"""
     _snake_case   	=      None
     _snake_case   	=      None
     _snake_case   	=      graph

     self._normalize_graph(__lowerCamelCase							,       __lowerCamelCase				)
     _snake_case   	=      len(__lowerCamelCase				)
     _snake_case   	=      None



   def    __UpperCAmelCase    (       self    :	Union[str, Any]							,       __lowerCamelCase    :	Tuple							,       __lowerCamelCase    :	str				):



     """simple docstring"""
     if sources is int:
       _snake_case   	=      [sources]
     if sinks is int:
       _snake_case   	=      [sinks]

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

     _snake_case   	=      sources[0]
     _snake_case   	=      sinks[0]

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

       _snake_case   	=      len(self.graph				) + 1
       for room in self.graph:
         room.insert(0							,       0				)
       self.graph.insert(0							,       [0] * size				)
       for i in sources:
         _snake_case   	=      max_input_flow
       _snake_case   	=      0

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



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     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    :	Dict							,       __lowerCamelCase    :	int				):



     """simple docstring"""
     _snake_case   	=      algorithm(self				)



class     UpperCAmelCase    :



   def __init__(       self    :	List[str]							,       __lowerCamelCase    :	Optional[Any]				):



     """simple docstring"""
     _snake_case   	=      flow_network
     _snake_case   	=      flow_network.verticesCount
     _snake_case   	=      flow_network.sourceIndex
     _snake_case   	=      flow_network.sinkIndex
     # it's just a reference, so you shouldn't change
     # it in your algorithms, use deep copy before doing that
     _snake_case   	=      flow_network.graph
     _snake_case   	=      False



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     if not self.executed:
       self._algorithm()
       _snake_case   	=      True





   def    __UpperCAmelCase    (       self    :	List[str]				):



     """simple docstring"""
     pass



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):



   def __init__(       self    :	str							,       __lowerCamelCase    :	Optional[int]				):



     """simple docstring"""
     super().__init__(__lowerCamelCase				)
     # use this to save your result
     _snake_case   	=      -1





   def    __UpperCAmelCase    (       self    :	List[Any]				):



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

     return self.maximum_flow



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):



   def __init__(       self    :	str							,       __lowerCamelCase    :	Tuple				):



     """simple docstring"""
     super().__init__(__lowerCamelCase				)

     _snake_case   	=      [[0] * self.verticies_count for i in range(self.verticies_count				)]

     _snake_case   	=      [0] * self.verticies_count
     _snake_case   	=      [0] * self.verticies_count



   def    __UpperCAmelCase    (       self    :	str				):



     """simple docstring"""
     _snake_case   	=      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
     _snake_case   	=      [
         i
         for i in range(self.verticies_count				)
         if i != self.source_index and i != self.sink_index
     ]

     # move through list
     _snake_case   	=      0
     while i < len(__lowerCamelCase				):
       _snake_case   	=      vertices_list[i]
       _snake_case   	=      self.heights[vertex_index]
       self.process_vertex(__lowerCamelCase				)
       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(__lowerCamelCase				)				)
         _snake_case   	=      0
       else:
         i += 1

     _snake_case   	=      sum(self.preflow[self.source_index]				)



   def    __UpperCAmelCase    (       self    :	str							,       __lowerCamelCase    :	Tuple				):



     """simple docstring"""
     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(__lowerCamelCase							,       __lowerCamelCase				)

       self.relabel(__lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	int							,       __lowerCamelCase    :	Optional[int]							,       __lowerCamelCase    :	Optional[int]				):



     """simple docstring"""
     _snake_case   	=      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    :	Union[str, Any]							,       __lowerCamelCase    :	Dict				):



     """simple docstring"""
     _snake_case   	=      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):
         _snake_case   	=      self.heights[to_index]

     if min_height is not None:
       _snake_case   	=      min_height + 1


if __name__ == "__main__":
     snake_case   					=				[0]
     snake_case   					=				[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],
     # ]
     snake_case   					=				[[0, 7, 0, 0], [0, 0, 6, 0], [0, 0, 0, 8], [9, 0, 0, 0]]

     # prepare our network
     snake_case   					=				FlowNetwork(graph, entrances, exits)
     # set algorithm
     flow_network.set_maximum_flow_algorithm(PushRelabelExecutor)
     # and calculate
     snake_case   					=				flow_network.find_maximum_flow()

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










"""simple docstring"""






import os
from pathlib import Path




def 			snake_case		(		)						->				Tuple:
  from torch.utils.cpp_extension import load

  _snake_case   	=      Path(lowerCAmelCase_	).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
  _snake_case   	=      [
      root / filename
      for filename in [
          '''vision.cpp''',
          os.path.join('''cpu'''  ,						'''ms_deform_attn_cpu.cpp'''	),
          os.path.join('''cuda'''  ,						'''ms_deform_attn_cuda.cu'''	),
      ]
  ]

  load(
      '''MultiScaleDeformableAttention'''  ,						lowerCAmelCase_  ,						with_cuda=lowerCAmelCase_  ,						extra_include_paths=[str(lowerCAmelCase_	)]  ,						extra_cflags=['''-DWITH_CUDA=1''']  ,						extra_cuda_cflags=[
          '''-DCUDA_HAS_FP16=1''',
          '''-D__CUDA_NO_HALF_OPERATORS__''',
          '''-D__CUDA_NO_HALF_CONVERSIONS__''',
          '''-D__CUDA_NO_HALF2_OPERATORS__''',
      ]  ,						)

  import MultiScaleDeformableAttention as MSDA

  return MSDA





