code: def build_euc_gp_with_dataset(dataset, kernel_type):
      """Function to build a SE GP with the dataset."""
      mean_func = lambda x: np.array([np.median(dataset[1])] * len(x))
      noise_var = dataset[1].std() ** 2 / 20
      kernel_hyperparams = dataset[2].hyperparams
      kernel_hyperparams["dim"] = len(dataset[0][0])
      kernel_hyperparams["nu"] = 2.5
      return EuclideanGP(
          dataset[0],
          dataset[1],
          kernel_type,
          mean_func,
          noise_var,
          kernel_hyperparams,
      )
  
imports: from __future__ import division
  import unittest
  import numpy
  from .euclidean_gp import EuclideanGP, EuclideanGPFitter, euclidean_gp_args
  from .unittest_gp_core import compute_average_prediction_error
  from .unittest_gp_core import gen_gp_test_data
  from ..utils.base_test_class import BaseTestClass, execute_tests
  from ..utils.option_handler import load_options
label_desc: Use image node_id 1 for calling a global function with example usage: build_euc_gp_with_dataset(dataset, kernel_type) and returns: EuclideanGP