code: def diag(self, X):
      n = self.n
      return self.kernels[0].diag(X[:, :n]) * self.kernels[1].diag(
          X[:, n:]
      )
  
imports: import random
  import os
  import sys
  import collections
  import itertools
  import pickle
  import scipy.sparse
  import networkx
  import numpy
  from sklearn.cluster import SpectralClustering
  from sklearn import gaussian_process
  from scipy.optimize import minimize
  from bayes_opt import BayesianOptimization
label_desc: Use image node_id 3 for calling the K obj's underlying member method code with example usage: obj.diag(X) and returns: unknown