




'''simple docstring'''


from __future__ import annotations

from typing import Any





class    __lowercase						:







   def __init__(	self      ,							UpperCamelCase      )				->    None:
     __a			=					num_of_nodes
     __a			=					[]
     __a			=					{}







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase      ,							UpperCamelCase      )				->    None:
     self.m_edges.append([u_node, v_node, weight]      )







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    int:

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







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    None:

     if self.m_component[u_node] != u_node:
       for k in self.m_component:
         __a			=					self.find_component(UpperCamelCase      )







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase      ,							UpperCamelCase      )				->    None:

     if component_size[u_node] <= component_size[v_node]:
       __a			=					v_node
       component_size[v_node] += component_size[u_node]
       self.set_component(UpperCamelCase      )

     elif component_size[u_node] >= component_size[v_node]:
       __a			=					self.find_component(UpperCamelCase      )
       component_size[u_node] += component_size[v_node]
       self.set_component(UpperCamelCase      )







   def 		UpperCamelCase__			(	self      )				->    None:
     __a			=					[]
     __a			=					0

     __a			=					[-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      )

     __a			=					self.m_num_of_nodes

     while num_of_components > 1:
       for edge in self.m_edges:
         __a	,       __a	,       __a			=					edge

         __a			=					self.m_component[u]
         __a			=					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
             ):
               __a			=					[u, v, w]

       for edge in minimum_weight_edge:
         if isinstance(UpperCamelCase      ,							UpperCamelCase      ):
           __a	,       __a	,       __a			=					edge

           __a			=					self.m_component[u]
           __a			=					self.m_component[v]

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

       __a			=					[-1] * self.m_num_of_nodes
     print(f"The total weight of the minimal spanning tree is: {mst_weight}"      )


def 						SCREAMING_SNAKE_CASE       (      ):
  pass


if __name__ == "__main__":
  import doctest

  doctest.testmod()






'''simple docstring'''


import torch

from diffusers import StableDiffusionPipeline


UpperCAmelCase_ 		=      "path-to-your-trained-model"
UpperCAmelCase_ 		=      StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")

UpperCAmelCase_ 		=      "A photo of sks dog in a bucket"
UpperCAmelCase_ 		=      pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save("dog-bucket.png")



