docstr: 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, 2, 3, 4],
          [3, 2, 3, 2],
          [0.1, 0.1, 0.1, 0.1],
          [0.2, 0.2, 0.2, 0.2],
      )
      self.mock_model.get_fmin.return_value = [1, 1, 2, 3]
  
      (
          weighted_acquisition,
          weighted_gradient,
      ) = self.ei_mcmc_acquisition.acquisition_function_withGradients(
          np.array([2, 2])
      )
  
      self.assertTrue(
          np.isclose(
              weighted_acquisition,
              np.array([[-0.69137376], [-0.69137376]]),
          ).all()
      )
      self.assertTrue(
          np.isclose(
              weighted_gradient,
              np.array(
                  [
                      [-0.03690296, -0.03690296],
                      [-0.03690296, -0.03690296],
                  ]
              ),
          ).all()
      )
  
file_path: GPyOpt/GPyOpt/testing/acquisitions_tests/test_ei_mcmc_acquisition.py
imports: import unittest
  from mock import Mock
  import numpy
  from GPyOpt.acquisitions import AcquisitionEI_MCMC
  from GPyOpt.core.task.space import Design_space
label_desc: Use image node_id 3 for calling the TestEImcmcAcquisition obj's underlying member method code with example usage: obj.test_acquisition_function_withGradients() without return types