
"""simple docstring"""


from __future__ import annotations

import os
from collections.abc import Mapping

A_    							=					tuple[int, int]




class  __lowerCamelCase  :




				def __init__(				self							,						UpperCAmelCase							,						UpperCAmelCase   ):
							lowerCamelCase_					=  vertices
							lowerCamelCase_					=  {
							    (min(UpperCAmelCase   ), max(UpperCAmelCase   )): weight for edge, weight in edges.items()
							}




				def        UpperCAmelCase__						(				self							,						UpperCAmelCase							,						UpperCAmelCase   ):
							self.vertices.add(edge[0]   )
							self.vertices.add(edge[1]   )
							lowerCamelCase_					=  weight





				def        UpperCAmelCase__						(				self   ):
							lowerCamelCase_					=  Graph({min(self.vertices   )}							,						{}   )
							lowerCamelCase_					=  42
							lowerCamelCase_					=  42
							lowerCamelCase_					=  42
							lowerCamelCase_					=  42

							while len(subgraph.vertices   ) < len(self.vertices   ):
										lowerCamelCase_					=  max(self.edges.values()   ) + 1
										for edge, weight in self.edges.items():
													if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
																if weight < min_weight:
																			lowerCamelCase_					=  edge
																			lowerCamelCase_					=  weight

										subgraph.add_edge(UpperCAmelCase							,						UpperCAmelCase   )

							return subgraph






def  lowercase						(	lowerCAmelCase__ = "p107_network.txt"						):
			lowerCamelCase_					=  os.path.abspath(os.path.dirname(lowerCAmelCase__						)						)
			lowerCamelCase_					=  os.path.join(lowerCAmelCase__	,lowerCAmelCase__						)
			lowerCamelCase_					=  {}
			lowerCamelCase_					=  42
			lowerCamelCase_					=  42
			lowerCamelCase_					=  42

			with open(lowerCAmelCase__						) as f:
						lowerCamelCase_					=  f.read().strip().split('''\n'''						)

			lowerCamelCase_					=  [line.split(''','''						) for line in data]

			for edgea in range(1	,len(lowerCAmelCase__						)						):
						for edgea in range(lowerCAmelCase__						):
									if adjaceny_matrix[edgea][edgea] != "-":
												lowerCamelCase_					=  int(adjaceny_matrix[edgea][edgea]						)

			lowerCamelCase_					=  Graph(set(range(len(lowerCAmelCase__						)						)						)	,lowerCAmelCase__						)

			lowerCamelCase_					=  graph.prims_algorithm()

			lowerCamelCase_					=  sum(graph.edges.values()						)
			lowerCamelCase_					=  sum(subgraph.edges.values()						)

			return initial_total - optimal_total


if __name__ == "__main__":
						print(f"{solution() = }")











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


UpperCAmelCase__      			=						logging.get_logger(__name__)

UpperCAmelCase__      			=						{
    '''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}




class 							snake_case_       (    __UpperCamelCase      ):

						"""simple docstring"""



						snake_case__        =      """glpn"""



						def __init__(self:					Tuple ,					__UpperCAmelCase:					Tuple=3 ,					__UpperCAmelCase:					Dict=4 ,					__UpperCAmelCase:					Any=[2, 2, 2, 2] ,					__UpperCAmelCase:					Optional[int]=[8, 4, 2, 1] ,					__UpperCAmelCase:					Dict=[32, 64, 160, 256] ,					__UpperCAmelCase:					List[str]=[7, 3, 3, 3] ,					__UpperCAmelCase:					Dict=[4, 2, 2, 2] ,					__UpperCAmelCase:					Optional[int]=[1, 2, 5, 8] ,					__UpperCAmelCase:					Dict=[4, 4, 4, 4] ,					__UpperCAmelCase:					List[str]="gelu" ,					__UpperCAmelCase:					str=0.0 ,					__UpperCAmelCase:					List[Any]=0.0 ,					__UpperCAmelCase:					Dict=0.02 ,					__UpperCAmelCase:					List[str]=0.1 ,					__UpperCAmelCase:					Union[str, Any]=1E-6 ,					__UpperCAmelCase:					Dict=64 ,					__UpperCAmelCase:					Dict=10 ,					__UpperCAmelCase:					Union[str, Any]=-1 ,					**__UpperCAmelCase:					Dict ,					)    ->     str:




											'''simple docstring'''



											super().__init__(**__UpperCAmelCase   )

											__a					:						Optional[Any]      =					num_channels
											__a					:						Tuple      =					num_encoder_blocks
											__a					:						int      =					depths
											__a					:						Union[str, Any]      =					sr_ratios
											__a					:						str      =					hidden_sizes
											__a					:						List[Any]      =					patch_sizes
											__a					:						Optional[Any]      =					strides
											__a					:						Any      =					mlp_ratios
											__a					:						Any      =					num_attention_heads
											__a					:						Any      =					hidden_act
											__a					:						List[Any]      =					hidden_dropout_prob
											__a					:						int      =					attention_probs_dropout_prob
											__a					:						List[str]      =					initializer_range
											__a					:						Optional[int]      =					drop_path_rate
											__a					:						Any      =					layer_norm_eps
											__a					:						List[Any]      =					decoder_hidden_size
											__a					:						Any      =					max_depth
											__a					:						int      =					head_in_index





