
def   lowerCamelCase__							(					a		,		a		,		a		,		a      )      ->   Dict:
   # Return True if there is node that has not iterated.
   _A:  int					=       [False] * len(a      )
   _A:  Any					=       []
   queue.append(a      )
   _A:  List[Any]					=       True

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

   return visited[t]






def   lowerCamelCase__							(					a		,		a		,		a      )      ->   List[Any]:
   # This array is filled by BFS and to store path
   _A:  Any					=       [-1] * (len(a      ))
   _A:  Union[str, Any]					=       0
   while bfs(a		,		a		,		a		,		a      ):
      _A:  str					=       float('''Inf'''      )
      _A:  Any					=       sink

      while s != source:
         # Find the minimum value in select path
         _A:  Optional[int]					=       min(a		,		graph[parent[s]][s]      )
         _A:  List[str]					=       parent[s]

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

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


UpperCAmelCase__		:     Optional[int]     			=      [
    [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__		:     List[str]     			=      0, 5





print(ford_fulkerson(graph, source, sink))





import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict






@pytest.mark.parametrize(
    '''files'''		,		[
        ['''full:README.md''', '''dataset_infos.json'''],
        ['''empty:README.md''', '''dataset_infos.json'''],
        ['''dataset_infos.json'''],
        ['''full:README.md'''],
    ]		,		)
def   lowerCamelCase__							(					a		,		a      )      ->   Any:
   _A:  Any					=       tmp_path_factory.mktemp('''dset_infos_dir'''      )
   if "full:README.md" in files:
      with open(dataset_infos_dir / '''README.md'''		,		'''w'''      ) as f:
         f.write('''---\ndataset_info:\n  dataset_size: 42\n---'''      )
   if "empty:README.md" in files:
      with open(dataset_infos_dir / '''README.md'''		,		'''w'''      ) as f:
         f.write(''''''      )
    # we want to support dataset_infos.json for backward compatibility
   if "dataset_infos.json" in files:
      with open(dataset_infos_dir / '''dataset_infos.json'''		,		'''w'''      ) as f:
         f.write('''{"default": {"dataset_size": 42}}'''      )
   _A:  Optional[int]					=       DatasetInfosDict.from_directory(a      )
   assert dataset_infos
   assert dataset_infos["default"].dataset_size == 42






@pytest.mark.parametrize(
    '''dataset_info'''		,		[
        DatasetInfo(),
        DatasetInfo(
            description='''foo'''		,		features=Features({'''a''': Value('''int32'''      )}      )		,		builder_name='''builder'''		,		config_name='''config'''		,		version='''1.0.0'''		,		splits=[{'''name''': '''train'''}]		,		download_size=42		,		),
    ]		,		)
def   lowerCamelCase__							(					a		,		a      )      ->   Any:
   _A:  int					=       str(a      )
   dataset_info.write_to_directory(a      )
   _A:  str					=       DatasetInfo.from_directory(a      )
   assert dataset_info == reloaded
   assert os.path.exists(os.path.join(a		,		'''dataset_info.json'''      )      )






def   lowerCamelCase__							(					)      ->   Any:
   _A:  int					=       DatasetInfo(
       description='''foo'''		,		citation='''bar'''		,		homepage='''https://foo.bar'''		,		license='''CC0'''		,		features=Features({'''a''': Value('''int32'''      )}      )		,		post_processed={}		,		supervised_keys=()		,		task_templates=[]		,		builder_name='''builder'''		,		config_name='''config'''		,		version='''1.0.0'''		,		splits=[{'''name''': '''train''', '''num_examples''': 42}]		,		download_checksums={}		,		download_size=13_37		,		post_processing_size=4_42		,		dataset_size=12_34		,		size_in_bytes=13_37 + 4_42 + 12_34		,		)
   _A:  Optional[Any]					=       dataset_info._to_yaml_dict()
   assert sorted(a      ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML      )
   for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
      assert key in dataset_info_yaml_dict
      assert isinstance(dataset_info_yaml_dict[key]		,		(list, dict, int, str)      )
   _A:  str					=       yaml.safe_dump(a      )
   _A:  Optional[int]					=       yaml.safe_load(a      )
   assert dataset_info_yaml_dict == reloaded






def   lowerCamelCase__							(					)      ->   int:
   _A:  Union[str, Any]					=       DatasetInfo()
   _A:  Union[str, Any]					=       dataset_info._to_yaml_dict()
   assert dataset_info_yaml_dict == {}






@pytest.mark.parametrize(
    '''dataset_infos_dict'''		,		[
        DatasetInfosDict(),
        DatasetInfosDict({'''default''': DatasetInfo()}      ),
        DatasetInfosDict({'''my_config_name''': DatasetInfo()}      ),
        DatasetInfosDict(
            {
                '''default''': DatasetInfo(
                    description='''foo'''		,		features=Features({'''a''': Value('''int32'''      )}      )		,		builder_name='''builder'''		,		config_name='''config'''		,		version='''1.0.0'''		,		splits=[{'''name''': '''train'''}]		,		download_size=42		,		)
            }      ),
        DatasetInfosDict(
            {
                '''v1''': DatasetInfo(dataset_size=42      ),
                '''v2''': DatasetInfo(dataset_size=13_37      ),
            }      ),
    ]		,		)
def   lowerCamelCase__							(					a		,		a      )      ->   Optional[int]:
   _A:  Optional[int]					=       str(a      )
   dataset_infos_dict.write_to_directory(a      )
   _A:  Union[str, Any]					=       DatasetInfosDict.from_directory(a      )

   # the config_name of the dataset_infos_dict take over the attribute
   for config_name, dataset_info in dataset_infos_dict.items():
      _A:  Optional[Any]					=       config_name
      # the yaml representation doesn't include fields like description or citation
      # so we just test that we can recover what we can from the yaml
      _A:  Any					=       DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()      )
   assert dataset_infos_dict == reloaded

   if dataset_infos_dict:
      assert os.path.exists(os.path.join(a		,		'''README.md'''      )      )



