code: def predict(self, X, return_std=True):
      X = np.array(X)
      return np.zeros(X.shape[0]), np.ones(X.shape[0])
  
imports: import numpy
  import pytest
  from scipy import optimize
  from sklearn.multioutput import MultiOutputRegressor
  from numpy.testing import assert_array_almost_equal
  from numpy.testing import assert_array_equal
  from numpy.testing import assert_raises
  from skopt.acquisition import _gaussian_acquisition
  from skopt.acquisition import gaussian_acquisition_1D
  from skopt.acquisition import gaussian_ei
  from skopt.acquisition import gaussian_lcb
  from skopt.acquisition import gaussian_pi
  from skopt.learning import GaussianProcessRegressor
  from skopt.learning.gaussian_process.kernels import Matern
  from skopt.learning.gaussian_process.kernels import WhiteKernel
  from skopt.space import Space
  from skopt.utils import cook_estimator
label_desc: Use image node_id 1 for calling the ConstSurrogate obj's underlying member method code with example usage: obj.predict(X, return_std) and returns: np,  np