code: def build_mfgp_with_dataset(dataset, *_):
      """Builds a MF GP by using some reasonable values for the parameters."""
      mean_func = lambda x: np.array([np.median(dataset.Y_tr)] * len(x))
      noise_var = (dataset.Y_tr.std() ** 2) / 20
      return euclidean_gp.EuclideanMFGP(
          dataset.Z_tr,
          dataset.X_tr,
          dataset.Y_tr,
          None,
          dataset.kernel_scale,
          dataset.fidel_kernel,
          dataset.domain_kernel,
          mean_func,
          noise_var,
      )
  
imports: from __future__ import division
  from argparse import Namespace
  from copy import deepcopy
  import numpy
  from .None import kernel
  from .unittest_euclidean_gp import fit_se_gp_with_dataset, fit_matern_gp_with_dataset, fit_poly_gp_with_dataset
  from .None import euclidean_gp
  from ..utils.base_test_class import BaseTestClass, execute_tests
  from ..utils.general_utils import compute_average_sq_prediction_error
  from ..utils.option_handler import load_options
label_desc: Use image node_id 8 for calling a global function with example usage: build_mfgp_with_dataset(dataset) and returns: euclidean_gp