



"""simple docstring"""





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


__lowerCAmelCase       :					List[Any]      					=					logging.get_logger(__name__)



class    _lowerCAmelCase    (				SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase			  =       '''upernet'''





		def __init__(					self							,    _lowercase=None							,    _lowercase=5_1_2							,    _lowercase=0.02							,    _lowercase=[1, 2, 3, 6]							,    _lowercase=True							,    _lowercase=0.4							,    _lowercase=3_8_4							,    _lowercase=2_5_6							,    _lowercase=1							,    _lowercase=False							,    _lowercase=2_5_5							,    **_lowercase							,    ) ->						List[Any]:







								'''simple docstring'''

								super().__init__(**_lowercase   )

								if backbone_config is None:
														logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""   )
														snake_case_   : Optional[Any]						=			CONFIG_MAPPING["""resnet"""](out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]   )
								elif isinstance(_lowercase							,    _lowercase   ):
														snake_case_   : List[Any]						=			backbone_config.get("""model_type"""   )
														snake_case_   : Optional[Any]						=			CONFIG_MAPPING[backbone_model_type]
														snake_case_   : Any						=			config_class.from_dict(_lowercase   )

								snake_case_   : str						=			backbone_config
								snake_case_   : Union[str, Any]						=			hidden_size
								snake_case_   : Dict						=			initializer_range
								snake_case_   : Union[str, Any]						=			pool_scales
								snake_case_   : Optional[Any]						=			use_auxiliary_head
								snake_case_   : Any						=			auxiliary_loss_weight
								snake_case_   : List[Any]						=			auxiliary_in_channels
								snake_case_   : str						=			auxiliary_channels
								snake_case_   : Dict						=			auxiliary_num_convs
								snake_case_   : List[Any]						=			auxiliary_concat_input
								snake_case_   : int						=			loss_ignore_index





		def    UpperCAmelCase__							(					self   ) ->						List[str]:







								'''simple docstring'''

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






"""simple docstring"""





def 	__lowerCAmelCase						(		__UpperCamelCase      :			Union[str, Any]    ):


						'''simple docstring'''






						snake_case_   : int						=			[0] * len(__UpperCamelCase    )
						snake_case_   : List[str]						=			[]
						snake_case_   : Any						=			[1] * len(__UpperCamelCase    )

						for values in graph.values():
												for i in values:
																		indegree[i] += 1

						for i in range(len(__UpperCamelCase    )    ):
												if indegree[i] == 0:
																		queue.append(__UpperCamelCase    )

						while queue:
												snake_case_   : Optional[int]						=			queue.pop(0    )
												for x in graph[vertex]:
																		indegree[x] -= 1

																		if long_dist[vertex] + 1 > long_dist[x]:
																								snake_case_   : Union[str, Any]						=			long_dist[vertex] + 1

																		if indegree[x] == 0:
																								queue.append(__UpperCamelCase    )

						print(max(__UpperCamelCase    )    )


# Adjacency list of Graph
__lowerCAmelCase       :					str      					=					{0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}






longest_distance(graph)

