code: def predict_wrapper(X, gpr):
      """Predict that can handle 1-D input"""
      X = np.expand_dims(X, axis=0)
      return gpr.predict(X, return_std=True)
  
file_path: scikit-optimize/skopt/learning/gaussian_process/tests/test_gpr.py
imports: import numpy
  import pytest
  from scipy import optimize
  from numpy.testing import assert_almost_equal
  from numpy.testing import assert_array_almost_equal
  from numpy.testing import assert_array_equal
  from skopt.learning import GaussianProcessRegressor
  from skopt.learning.gaussian_process.kernels import RBF
  from skopt.learning.gaussian_process.kernels import Matern
  from skopt.learning.gaussian_process.kernels import WhiteKernel
  from skopt.learning.gaussian_process.gpr import _param_for_white_kernel_in_Sum
label_desc: Use image node_id 1 for calling a global function with example usage: predict_wrapper(X, gpr) and returns: gpr