code: def test_gradient(self):
      index_points = np.linspace(
          -4.0, 4.0, 10, dtype=self.dtype
      ).reshape([-1, 2])
      observations = np.linspace(2.0, 10.0, 8, dtype=self.dtype)
      observation_index_points = np.linspace(
          4.0, 10.0, 16, dtype=self.dtype
      ).reshape([-1, 2])
      predictive_distribution = gprm.GaussianProcessRegressionModel(
          kernel=exponentiated_quadratic.ExponentiatedQuadratic(
              amplitude=self.dtype(1.0)
          ),
          observations=observations,
          observation_index_points=observation_index_points,
          observation_noise_variance=self.dtype(0.0),
          index_points=index_points,
      )
      mes = (
          max_value_entropy_search.GaussianProcessMaxValueEntropySearch(
              predictive_distribution=predictive_distribution,
              observations=observations,
              num_max_value_samples=1,
              seed=test_util.test_seed(),
          )
      )
      _, grad = gradient.value_and_gradient(
          lambda x: mes(index_points=x),
          tf.convert_to_tensor(index_points),
      )
      self.assertAllNotNan(grad)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gaussian_process_regression_model
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.bayesopt.acquisition import max_value_entropy_search
  from tensorflow_probability.python.experimental.bayesopt.acquisition.max_value_entropy_search import fit_max_value_distribution
  from tensorflow_probability.python.experimental.bayesopt.acquisition.max_value_entropy_search import inverse_mills_ratio
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import exponentiated_quadratic
label_desc: Use image node_id 3 for calling the _MaxValueEntropySearchTest obj's underlying member method code with example usage: obj.test_gradient() without return types