code: def normal_upper_confidence_bound(mean, stddev, exploration=0.01):
      """Normal distribution upper confidence bound.
  
      Args:
        mean: Array of predicted means. Must broadcast with `stddev`.
        stddev: Array of predicted standard deviations. Must broadcast with `mean`.
        exploration: Float parameter controlling the exploration/exploitation
          tradeoff.
  
      Returns:
        ucb: Array of upper confidence bound values.
      """
      dtype = dtype_util.common_dtype([mean, stddev])
      mean = tf.convert_to_tensor(mean, dtype=dtype)
      stddev = tf.convert_to_tensor(stddev, dtype=dtype)
      return mean + exploration * stddev
  
file_path: probability/tensorflow_probability/python/experimental/bayesopt/acquisition/upper_confidence_bound.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.bayesopt.acquisition import acquisition_function
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import samplers
label_desc: Use image node_id 1 for calling a global function with example usage: normal_upper_confidence_bound(mean, stddev, exploration) and returns: unknown