





"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


A 			=  logging.get_logger(__name__)

A 			=  {
    '''microsoft/resnet-50''': '''https://huggingface.co/microsoft/resnet-50/blob/main/config.json''',
}




class 				__lowercase			(			_UpperCamelCase   ,      _UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  '''resnet'''
					__lowerCAmelCase  =  ['''basic''', '''bottleneck''']







					def __init__(						self	,			_UpperCAmelCase=3	,			_UpperCAmelCase=64	,			_UpperCAmelCase=[256, 512, 1024, 2048]	,			_UpperCAmelCase=[3, 4, 6, 3]	,			_UpperCAmelCase="bottleneck"	,			_UpperCAmelCase="relu"	,			_UpperCAmelCase=False	,			_UpperCAmelCase=None	,			_UpperCAmelCase=None	,			**_UpperCAmelCase	,			):
									super().__init__(**_UpperCAmelCase     )
									if layer_type not in self.layer_types:
													raise ValueError(f"""layer_type={layer_type} is not one of {",".join(self.layer_types     )}"""     )
									__a :						Any			       =  num_channels
									__a :						Optional[Any]			       =  embedding_size
									__a :						Union[str, Any]			       =  hidden_sizes
									__a :						List[Any]			       =  depths
									__a :						Any			       =  layer_type
									__a :						Optional[int]			       =  hidden_act
									__a :						Dict			       =  downsample_in_first_stage
									__a :						str			       =  ['''stem'''] + [f"""stage{idx}""" for idx in range(1	,			len(_UpperCAmelCase     ) + 1     )]
									__a       ,						__a :						Optional[int]			       =  get_aligned_output_features_output_indices(
									    out_features=_UpperCAmelCase	,			out_indices=_UpperCAmelCase	,			stage_names=self.stage_names     )






class 				__lowercase			(			_UpperCamelCase							):







					'''simple docstring'''




					__lowerCAmelCase  =  version.parse('''1.11'''							)







					@property
					def  _lowerCamelCase		(						self     ):
									return OrderedDict(
									    [
									        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
									    ]     )







					@property
					def  _lowerCamelCase		(						self     ):
									return 1e-3






"""simple docstring"""






from __future__ import annotations

import os
from collections.abc import Mapping

A 			=  tuple[int, int]




class 				__lowercase			:







					'''simple docstring'''




					def __init__(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									__a :						set[int]			       =  vertices
									__a :						dict[EdgeT, int]			       =  {
									    (min(_UpperCAmelCase     ), max(_UpperCAmelCase     )): weight for edge, weight in edges.items()
									}







					def  _lowerCamelCase		(						self	,			_UpperCAmelCase	,			_UpperCAmelCase     ):
									self.vertices.add(edge[0]     )
									self.vertices.add(edge[1]     )
									__a :						Any			       =  weight







					def  _lowerCamelCase		(						self     ):
									__a :						Graph			       =  Graph({min(self.vertices     )}	,			{}     )
									__a :						EdgeT
									__a :						int
									__a :						EdgeT
									__a :						int

									while len(subgraph.vertices     ) < len(self.vertices     ):
													__a :						List[Any]			       =  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:
																									__a :						str			       =  edge
																									__a :						int			       =  weight

													subgraph.add_edge(_UpperCAmelCase	,			_UpperCAmelCase     )

									return subgraph






def     __A      (			a_						:str = "p107_network.txt")		->		int:
				__a :						str			       =  os.path.abspath(os.path.dirname(a_))
				__a :						str			       =  os.path.join(a_   ,       a_)
				__a :						dict[EdgeT, int]			       =  {}
				__a :						list[str]
				__a :						int
				__a :						int

				with open(a_) as f:
								__a :						Any			       =  f.read().strip().split('''\n''')

				__a :						Union[str, Any]			       =  [line.split(''',''') for line in data]

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

				__a :						Graph			       =  Graph(set(range(len(a_)))   ,       a_)

				__a :						Graph			       =  graph.prims_algorithm()

				__a :						int			       =  sum(graph.edges.values())
				__a :						int			       =  sum(subgraph.edges.values())

				return initial_total - optimal_total


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