docstr: Test that acquisition function with gradients returns correct weight acquisition and gradient
          
docstr_tok: ["Test","that","acquisition","function","with","gradients","returns","correct","weight","acquisition","and","gradient"]
code: def test_acquisition_function_withGradients(self):
      """Test that acquisition function with gradients returns correct weight acquisition and gradient"""
      self.mock_model.predict_withGradients.return_value = (
          1,
          1,
          0.1,
          0.1,
      )
      self.mock_model.get_fmin.return_value = 0.1
  
      (
          weighted_acquisition,
          weighted_gradient,
      ) = self.ei_acquisition.acquisition_function_withGradients(
          np.array([2, 2])
      )
  
      assert np.isclose(
          weighted_acquisition, np.array([[-0.0986038], [-0.0986038]])
      ).all()
      assert np.isclose(
          weighted_gradient,
          np.array(
              [[-0.00822768, -0.00822768], [-0.00822768, -0.00822768]]
          ),
      ).all()
  
file_path: GPyOpt/GPyOpt/testing/acquisitions_tests/test_ei_acquisition.py
imports: import unittest
  from mock import Mock
  import numpy
  from GPyOpt.acquisitions import AcquisitionEI
  from GPyOpt.core.task.space import Design_space
label_desc: Use image node_id 3 for calling the TestEIAcquisition obj's underlying member method code with example usage: obj.test_acquisition_function_withGradients() without return types