


from __future__ import annotations

from typing import Any


class 	A_ :




						'''simple docstring'''


						def __init__(    self:	List[Any]						,				a:	str    ):
							__lowerCamelCase		:							int		 =						num_of_nodes
							__lowerCamelCase		:							list[list[int]]		 =						[]
							__lowerCamelCase		:							dict[int, int]		 =						{}




						def 					_snake_case     (    self:	Dict						,				a:	Tuple						,				a:	List[Any]						,				a:	Optional[int]    ):
							self.m_edges.append([u_node, v_node, weight]    )




						def 					_snake_case     (    self:	Optional[int]						,				a:	Dict    ):

							if self.m_component[u_node] == u_node:
								return u_node
							return self.find_component(self.m_component[u_node]    )




						def 					_snake_case     (    self:	Optional[Any]						,				a:	Union[str, Any]    ):

							if self.m_component[u_node] != u_node:
								for k in self.m_component:
									__lowerCamelCase		:							Optional[int]		 =						self.find_component(lowercase_    )




						def 					_snake_case     (    self:	str						,				a:	Union[str, Any]						,				a:	Dict						,				a:	Tuple    ):

							if component_size[u_node] <= component_size[v_node]:
								__lowerCamelCase		:							Optional[Any]		 =						v_node
								component_size[v_node] += component_size[u_node]
								self.set_component(lowercase_    )

							elif component_size[u_node] >= component_size[v_node]:
								__lowerCamelCase		:							Optional[Any]		 =						self.find_component(lowercase_    )
								component_size[u_node] += component_size[v_node]
								self.set_component(lowercase_    )




						def 					_snake_case     (    self:	List[Any]    ):
							__lowerCamelCase		:							List[Any]		 =						[]
							__lowerCamelCase		:							List[str]		 =						0

							__lowerCamelCase		:							list[Any]		 =						[-1] * self.m_num_of_nodes

							# A list of components (initialized to all of the nodes)
							for node in range(self.m_num_of_nodes    ):
								self.m_component.update({node: node}    )
								component_size.append(1    )

							__lowerCamelCase		:							int		 =						self.m_num_of_nodes

							while num_of_components > 1:
								for edge in self.m_edges:
									__lowerCamelCase		:							str		 =						edge

									__lowerCamelCase		:							Dict		 =						self.m_component[u]
									__lowerCamelCase		:							str		 =						self.m_component[v]

									if u_component != v_component:

										for component in (u_component, v_component):
											if (
											    minimum_weight_edge[component] == -1
											    or minimum_weight_edge[component][2] > w
											):
												__lowerCamelCase		:							List[Any]		 =						[u, v, w]

								for edge in minimum_weight_edge:
									if isinstance(lowercase_						,				lowercase_    ):
										__lowerCamelCase		:							Tuple		 =						edge

										__lowerCamelCase		:							List[Any]		 =						self.m_component[u]
										__lowerCamelCase		:							Union[str, Any]		 =						self.m_component[v]

										if u_component != v_component:
											mst_weight += w
											self.union(lowercase_						,				lowercase_						,				lowercase_    )
											print(F'Added edge [{u} - {v}]\nAdded weight: {w}\n'    )
											num_of_components -= 1

								__lowerCamelCase		:							List[Any]		 =						[-1] * self.m_num_of_nodes
							print(F'The total weight of the minimal spanning tree is: {mst_weight}'    )



def 				UpperCamelCase__					(  ):
	pass


if __name__ == "__main__":
							import doctest

							doctest.testmod()





import warnings

from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor


lowercase_	   =     logging.get_logger(__name__)


class 	A_ (	__UpperCamelCase   ):




      '''simple docstring'''


      def __init__(    self:	List[str]						,				*a:	List[Any]						,				**a:	Optional[Any]    ):
       warnings.warn(
           'The class ChineseCLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use ChineseCLIPImageProcessor instead.'						,				a						,				)
       super().__init__(*a						,				**a    )

