code: def random_x(self):
      # sample a random X and give it to convert
      type_ = self.get_type()
      bound = self.get_bound()
      res = random_with_bound_type(bound, type_)
      return res
  
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 7 for calling the Params obj's underlying member method code with example usage: obj.random_x() and returns: res