code: def test_acquisition_api():
      rng = np.random.RandomState(0)
      X = rng.randn(10, 2)
      y = rng.randn(10)
      gpr = GaussianProcessRegressor()
      gpr.fit(X, y)
  
      for method in [gaussian_ei, gaussian_lcb, gaussian_pi]:
          assert_array_equal(method(X, gpr).shape, 10)
          assert_raises(ValueError, method, rng.rand(10), gpr)
  
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 5 for calling a global function with example usage: test_acquisition_api() without return types