class_docstr: Max-value entropy search acquisition function.
  
  Computes the sequential max-value entropy search acquisition function.
  
  Requires that `predictive_distribution` has a `.mean`, `stddev` method.
  
  #### Examples
  
  Build and evaluate a Gausian Process Maximum Value Entropy Search acquisition
  function.
  
  ```python
  import numpy as np
  import tensorflow_probability as tfp
  
  tfd = tfp.distributions
  tfpk = tfp.math.psd_kernels
  tfp_acq = tfp.experimental.bayesopt.acquisition
  
  # Sample 10 20-dimensional index points and associated observations.
  index_points = np.random.uniform(size=[10, 20])
  observations = np.random.uniform(size=[10])
  
  # Build a Gaussian Process regression model.
  dist = tfd.GaussianProcessRegressionModel(
      kernel=tfpk.MaternFiveHalves(),
      observation_index_points=index_points,
      observations=observations)
  
  # Define a GP max value entropy search acquisition function.
  gp_mes = tfp_acq.GaussianProcessMaxValueEntropySearch(
      predictive_distribution=dist,
      observations=observations,
      num_max_value_samples=200)
  
  # Evaluate the acquisition function at a set of predictive index points.
  pred_index_points = np.random.uniform(size=[6, 20])
  acq_fn_vals = gp_mes(pred_index_points)
  ```
  
  #### References
  [1] Z. Wang, S. Jegelka. Max-value Entropy Search for Efficient Bayesian
      Optimization. https://arxiv.org/abs/1703.01968
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code: def num_max_value_samples(self):
      return self._num_max_value_samples
  
file_path: probability/tensorflow_probability/python/experimental/bayesopt/acquisition/max_value_entropy_search.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gumbel
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.bayesopt.acquisition import acquisition_function
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.math import root_search
  from tensorflow_probability.python.math import special
  from tensorflow_probability.python.mcmc import sample_halton_sequence_lib
label_desc: Use image node_id 2 for calling the GaussianProcessMaxValueEntropySearch obj's underlying member method code with example usage: obj.num_max_value_samples() and returns: self