code: def predict(self, p_bound, type_, w=None):
      return find_b_opt_max(self.gp, p_bound, type_, w)
  
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 GaussianProcessRegressor obj's underlying member method code with example usage: obj.predict(p_bound, type_, w) and returns: find_b_opt_max