






'''simple docstring'''

import copy

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


UpperCAmelCase__						:Optional[Any]          =			logging.get_logger(__name__)







class 	SCREAMING_SNAKE_CASE	(      lowerCAmelCase_  ):
       snake_case__    :     str   		=			'encoder-decoder'
       snake_case__    :     Tuple   		=			True




       def __init__(					self      : int	,    **A__      : Optional[int]					):


            """simple docstring"""







            super().__init__(**A__					)
            assert (
                "encoder" in kwargs and "decoder" in kwargs
            ), "Config has to be initialized with encoder and decoder config"
            __lowerCamelCase						:       Optional[Any]				   =				kwargs.pop("""encoder"""					)
            __lowerCamelCase						:       List[str]				   =				encoder_config.pop("""model_type"""					)
            __lowerCamelCase						:       List[Any]				   =				kwargs.pop("""decoder"""					)
            __lowerCamelCase						:       Dict				   =				decoder_config.pop("""model_type"""					)

            from ..auto.configuration_auto import AutoConfig

            __lowerCamelCase						:       Tuple				   =				AutoConfig.for_model(A__	,    **A__					)
            __lowerCamelCase						:       str				   =				AutoConfig.for_model(A__	,    **A__					)
            __lowerCamelCase						:       List[str]				   =				True




       @classmethod
       def 					a_					(					cls      : int	,    A__      : PretrainedConfig	,    A__      : PretrainedConfig	,    **A__      : Optional[Any]					):


            """simple docstring"""







            logger.info("""Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"""					)
            __lowerCamelCase						:       str				   =				True
            __lowerCamelCase						:       str				   =				True

            return cls(encoder=encoder_config.to_dict()	,    decoder=decoder_config.to_dict()	,    **A__					)




       def 					a_					(					self      : List[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       Optional[int]				   =				copy.deepcopy(self.__dict__					)
            __lowerCamelCase						:       List[Any]				   =				self.encoder.to_dict()
            __lowerCamelCase						:       Dict				   =				self.decoder.to_dict()
            __lowerCamelCase						:       Optional[int]				   =				self.__class__.model_type
            return output











'''simple docstring'''

def     __lowercase  (_lowercase,						_lowercase,						_lowercase,						_lowercase     )   ->     Union[str, Any]:


     """simple docstring"""
     # Return True if there is node that has not iterated.
     __lowerCamelCase						:       Optional[Any]				   =				[False] * len(_lowercase     )
     __lowerCamelCase						:       Dict				   =				[]
     queue.append(_lowercase     )
     __lowerCamelCase						:       Optional[int]				   =				True

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

     return visited[t]
def     __lowercase  (_lowercase,						_lowercase,						_lowercase     )   ->     Optional[Any]:


     """simple docstring"""
     # This array is filled by BFS and to store path
     __lowerCamelCase						:       Any				   =				[-1] * (len(_lowercase     ))
     __lowerCamelCase						:       Optional[int]				   =				0
     while bfs(_lowercase,						_lowercase,						_lowercase,						_lowercase     ):
          __lowerCamelCase						:       List[Any]				   =				float("""Inf"""     )
          __lowerCamelCase						:       Union[str, Any]				   =				sink

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

          max_flow += path_flow
          __lowerCamelCase						:       str				   =				sink

          while v != source:
               __lowerCamelCase						:       List[Any]				   =				parent[v]
               graph[u][v] -= path_flow
               graph[v][u] += path_flow
               __lowerCamelCase						:       Dict				   =				parent[v]
     return max_flow


UpperCAmelCase__						:str          =			[
    [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],
]

UpperCAmelCase__       ,				UpperCAmelCase__						:Optional[Any]          =			0, 5
print(ford_fulkerson(graph, source, sink))



