




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_UpperCAmelCase		:  Tuple	=   {
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  List[Any]	=   ["LxmertTokenizerFast"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  int	=   [
         "LxmertEncoder",
         "LxmertForPreTraining",
         "LxmertForQuestionAnswering",
         "LxmertModel",
         "LxmertPreTrainedModel",
         "LxmertVisualFeatureEncoder",
         "LxmertXLayer",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  Union[str, Any]	=   [
         "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFLxmertForPreTraining",
         "TFLxmertMainLayer",
         "TFLxmertModel",
         "TFLxmertPreTrainedModel",
         "TFLxmertVisualFeatureEncoder",
     ]


if TYPE_CHECKING:
     from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
     from .tokenization_lxmert import LxmertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_lxmert_fast import LxmertTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_lxmert import (
              LxmertEncoder,
              LxmertForPreTraining,
              LxmertForQuestionAnswering,
              LxmertModel,
              LxmertPreTrainedModel,
              LxmertVisualFeatureEncoder,
              LxmertXLayer,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_lxmert import (
              TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFLxmertForPreTraining,
              TFLxmertMainLayer,
              TFLxmertModel,
              TFLxmertPreTrainedModel,
              TFLxmertVisualFeatureEncoder,
          )

else:
     import sys

     _UpperCAmelCase		:  Optional[Any]	=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase,	lowerCamelCase,	lowerCamelCase      ):
  # Return True if there is node that has not iterated.
  lowercase			:Union[str, Any]							=  [False] * len(lowerCamelCase      )
  lowercase			:Union[str, Any]							=  []
  queue.append(lowerCamelCase      )
  lowercase			:Optional[Any]							=  True

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

  return visited[t]



def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase,	lowerCamelCase      ):
  # This array is filled by BFS and to store path
  lowercase			:Optional[int]							=  [-1] * (len(lowerCamelCase      ))
  lowercase			:int							=  0
  while bfs(lowerCamelCase,	lowerCamelCase,	lowerCamelCase,	lowerCamelCase      ):
    lowercase			:int							=  float("Inf"      )
    lowercase			:Any							=  sink

    while s != source:
      # Find the minimum value in select path
      lowercase			:Any							=  min(lowerCamelCase,	graph[parent[s]][s]      )
      lowercase			:Dict							=  parent[s]

    max_flow += path_flow
    lowercase			:Union[str, Any]							=  sink

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


_UpperCAmelCase		:  Optional[Any]	=   [
    [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		:  Any	=   0, 5







print(ford_fulkerson(graph, source, sink))



