code: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  from __future__ import annotations
  
  import random
  
  # Adjacency list representation of this graph:
  # https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
  lowerCamelCase_     :     Any    		=						{
      '1': ['2', '3', '4', '5'],
      '2': ['1', '3', '4', '5'],
      '3': ['1', '2', '4', '5', '10'],
      '4': ['1', '2', '3', '5', '6'],
      '5': ['1', '2', '3', '4', '7'],
      '6': ['7', '8', '9', '10', '4'],
      '7': ['6', '8', '9', '10', '5'],
      '8': ['6', '7', '9', '10'],
      '9': ['6', '7', '8', '10'],
      '10': ['6', '7', '8', '9', '3'],
  }
  def _A		(		lowercase	):
  
  
  
  
  
  
  
  				"""simple docstring"""
  				a					={node: {node} for node in graph}
  
  				a					={node: graph[node][:] for node in graph}
  
  				while len(_A	) > 2:
  								# Choose a random edge.
  								a					=random.choice(list(graph_copy.keys()	)	)
  								a					=random.choice(graph_copy[u]	)
  
  								# Contract edge (u, v) to new node uv
  								a					=u + v
  								a					=list(set(graph_copy[u] + graph_copy[v]	)	)
  								uv_neighbors.remove(_A	)
  								uv_neighbors.remove(_A	)
  								a					=uv_neighbors
  								for neighbor in uv_neighbors:
  												graph_copy[neighbor].append(_A	)
  
  								a					=set(contracted_nodes[u].union(contracted_nodes[v]	)	)
  
  								# Remove nodes u and v.
  								del graph_copy[u]
  								del graph_copy[v]
  								for neighbor in uv_neighbors:
  												if u in graph_copy[neighbor]:
  																graph_copy[neighbor].remove(_A	)
  												if v in graph_copy[neighbor]:
  																graph_copy[neighbor].remove(_A	)
  
      # Find cutset.
  				a					=[contracted_nodes[node] for node in graph_copy]
  				return {
  				    (node, neighbor)
  				    for node in groups[0]
  				    for neighbor in graph[node]
  				    if neighbor in groups[1]
  				}
  
  
  if __name__ == "__main__":
  							print(partition_graph(TEST_GRAPH))
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  from cva import destroyAllWindows, imread, imshow, waitKey
  def _A		(		lowercase ,					lowercase	):
  
  
  
  
  
  
  
      """simple docstring"""
      a	,   a					=img.shape[0], img.shape[1]
  
      def to_grayscale(lowercase ,					lowercase ,					lowercase	):
          return 0.2126 * red + 0.587 * green + 0.114 * blue
  
      def normalize(lowercase	):
          return min(lowercase ,					2_55	)
  
      for i in range(lowercase	):
          for j in range(lowercase	):
              a					=int(to_grayscale(*img[i][j]	)	)
              a					=[
                  normalize(lowercase	),
                  normalize(greyscale + factor	),
                  normalize(greyscale + 2 * factor	),
              ]
  
      return img
  
  
  if __name__ == "__main__":
         # read original image
         lowerCamelCase_     :     Any    		=						{
             percentage: imread("""image_data/lena.jpg""", 1) for percentage in (1_0, 2_0, 3_0, 4_0)
         }
  
         for percentage, img in images.items():
                make_sepia(img, percentage)
  
         for percentage, img in images.items():
                imshow(F'Original image with sepia (factor: {percentage})', img)
  
         waitKey(0)
         destroyAllWindows()