code: def edit_distance(x, y):
      """The distance between two neural networks.
      Args:
          x: An instance of NetworkDescriptor.
          y: An instance of NetworkDescriptor
      Returns:
          The edit-distance between x and y.
      """
  
      ret = layers_distance(x.layers, y.layers)
      ret += Constant.KERNEL_LAMBDA * skip_connections_distance(
          x.skip_connections, y.skip_connections
      )
      return ret
  
imports: import math
  import random
  from copy import deepcopy
  from functools import total_ordering
  from queue import PriorityQueue
  import numpy
  from scipy.linalg import LinAlgError, cho_solve, cholesky, solve_triangular
  from scipy.optimize import linear_sum_assignment
  from sklearn.metrics.pairwise import rbf_kernel
  from nni.utils import OptimizeMode
  from .graph_transformer import transform
  from .utils import Constant
  from .layers import is_layer
label_desc: Use image node_id 6 for calling a global function with example usage: edit_distance(x, y) and returns: ret