

def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   [False] * len(UpperCamelCase__				)
							snake_case_          =   []
							queue.append(UpperCamelCase__				)
							snake_case_          =   True

							while queue:
														snake_case_          =   queue.pop(0				)
														for ind in range(len(graph[u]				)				):
																					if visited[ind] is False and graph[u][ind] > 0:
																												queue.append(UpperCamelCase__				)
																												snake_case_          =   True
																												snake_case_          =   u

							return visited[t]





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   [-1] * (len(UpperCamelCase__				))
							snake_case_          =   0
							while bfs(UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):
														snake_case_          =   float('Inf'				)
														snake_case_          =   sink

														while s != source:
																					# Find the minimum value in select path
																					snake_case_          =   min(UpperCamelCase__       ,							graph[parent[s]][s]				)
																					snake_case_          =   parent[s]

														max_flow += path_flow
														snake_case_          =   sink

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


_UpperCAmelCase		:       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		:       str						    =	0, 5


print(ford_fulkerson(graph, source, sink))







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase		:       Tuple						    =	{
    """configuration_xlm_roberta_xl""": [
        """XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaXLConfig""",
        """XLMRobertaXLOnnxConfig""",
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:       int						    =	[
					    """XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """XLMRobertaXLForCausalLM""",
					    """XLMRobertaXLForMaskedLM""",
					    """XLMRobertaXLForMultipleChoice""",
					    """XLMRobertaXLForQuestionAnswering""",
					    """XLMRobertaXLForSequenceClassification""",
					    """XLMRobertaXLForTokenClassification""",
					    """XLMRobertaXLModel""",
					    """XLMRobertaXLPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_xlm_roberta_xl import (
					    XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    XLMRobertaXLConfig,
					    XLMRobertaXLOnnxConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_xlm_roberta_xl import (
										    XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
										    XLMRobertaXLForCausalLM,
										    XLMRobertaXLForMaskedLM,
										    XLMRobertaXLForMultipleChoice,
										    XLMRobertaXLForQuestionAnswering,
										    XLMRobertaXLForSequenceClassification,
										    XLMRobertaXLForTokenClassification,
										    XLMRobertaXLModel,
										    XLMRobertaXLPreTrainedModel,
										)

else:
					import sys

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




