




class       a					:

     '''simple docstring'''





     def __init__(     self       :      Union[str, Any] ,   __snake_case       :      Tuple ,   __snake_case       :      Tuple ,   __snake_case       :      List[str]    ):
         UpperCAmelCase_										=					None
         UpperCAmelCase_										=					None
         UpperCAmelCase_										=					graph

         self._normalize_graph(__snake_case ,   __snake_case    )
         UpperCAmelCase_										=					len(__snake_case    )
         UpperCAmelCase_										=					None
     def   lowerCamelCase_       (     self       :      Tuple ,   __snake_case       :      str ,   __snake_case       :      Any    ):
         if sources is int:
             UpperCAmelCase_										=					[sources]
         if sinks is int:
             UpperCAmelCase_										=					[sinks]

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

         UpperCAmelCase_										=					sources[0]
         UpperCAmelCase_										=					sinks[0]

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

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

             UpperCAmelCase_										=					len(self.graph    ) + 1
             for room in self.graph:
                 room.append(0    )
             self.graph.append([0] * size    )
             for i in sinks:
                 UpperCAmelCase_										=					max_input_flow
             UpperCAmelCase_										=					size - 1
     def   lowerCamelCase_       (     self       :      str    ):
         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   lowerCamelCase_       (     self       :      List[str] ,   __snake_case       :      int    ):
         UpperCAmelCase_										=					algorithm(self    )



class       a					:

     '''simple docstring'''





     def __init__(     self       :      Dict ,   __snake_case       :      List[str]    ):
         UpperCAmelCase_										=					flow_network
         UpperCAmelCase_										=					flow_network.verticesCount
         UpperCAmelCase_										=					flow_network.sourceIndex
         UpperCAmelCase_										=					flow_network.sinkIndex
         # it's just a reference, so you shouldn't change
         # it in your algorithms, use deep copy before doing that
         UpperCAmelCase_										=					flow_network.graph
         UpperCAmelCase_										=					False
     def   lowerCamelCase_       (     self       :      Tuple    ):
         if not self.executed:
             self._algorithm()
             UpperCAmelCase_										=					True




     def   lowerCamelCase_       (     self       :      Union[str, Any]    ):
         pass



class       a					(       _A      ):

     '''simple docstring'''





     def __init__(     self       :      List[Any] ,   __snake_case       :      Union[str, Any]    ):
         super().__init__(__snake_case    )
         # use this to save your result
         UpperCAmelCase_										=					-1




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

         return self.maximum_flow



class       a					(       _A      ):

     '''simple docstring'''





     def __init__(     self       :      Any ,   __snake_case       :      Any    ):
         super().__init__(__snake_case    )

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

         UpperCAmelCase_										=					[0] * self.verticies_count
         UpperCAmelCase_										=					[0] * self.verticies_count
     def   lowerCamelCase_       (     self       :      Optional[int]    ):
         UpperCAmelCase_										=					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
         UpperCAmelCase_										=					[
             i
             for i in range(self.verticies_count    )
             if i != self.source_index and i != self.sink_index
         ]

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

         UpperCAmelCase_										=					sum(self.preflow[self.source_index]    )
     def   lowerCamelCase_       (     self       :      Tuple ,   __snake_case       :      Optional[Any]    ):
         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(__snake_case ,   __snake_case    )

             self.relabel(__snake_case    )
     def   lowerCamelCase_       (     self       :      List[str] ,   __snake_case       :      Tuple ,   __snake_case       :      Optional[int]    ):
         UpperCAmelCase_										=					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   lowerCamelCase_       (     self       :      List[Any] ,   __snake_case       :      str    ):
         UpperCAmelCase_										=					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):
                 UpperCAmelCase_										=					self.heights[to_index]

         if min_height is not None:
             UpperCAmelCase_										=					min_height + 1


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

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

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











import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate



@dataclass(frozen=_A      )
class       a					(       _A      ):

     '''simple docstring'''





     lowerCAmelCase    :	str       		=  field(default='audio-classification'     ,       metadata={'include_in_asdict_even_if_is_default': True}      )
     lowerCAmelCase    :	ClassVar[Features]       		=  Features({'audio': Audio()}      )
     lowerCAmelCase    :	ClassVar[Features]       		=  Features({'labels': ClassLabel}      )
     lowerCAmelCase    :	str       		=  "audio"
     lowerCAmelCase    :	str       		=  "labels"
     def   lowerCamelCase_       (     self       :      Optional[Any] ,   __snake_case       :      List[Any]    ):
         if self.label_column not in features:
             raise ValueError(F'Column {self.label_column} is not present in features.'    )
         if not isinstance(features[self.label_column] ,   __snake_case    ):
             raise ValueError(F'Column {self.label_column} is not a ClassLabel.'    )
         UpperCAmelCase_										=					copy.deepcopy(self    )
         UpperCAmelCase_										=					self.label_schema.copy()
         UpperCAmelCase_										=					features[self.label_column]
         UpperCAmelCase_										=					label_schema
         return task_template




     @property
     def   lowerCamelCase_       (     self       :      Tuple    ):
         return {
             self.audio_column: "audio",
             self.label_column: "labels",
         }





