code: def tf_wheel_bandit_compute_optimal_reward(
      observation, delta, mu_inside, mu_high
  ):
      """TF wrapper around `compute_optimal_reward` to be used in `tf_metrics`."""
      return tf.py_function(
          wheel_py_environment.compute_optimal_reward,
          [observation, delta, mu_inside, mu_high],
          tf.float32,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import gin
  import numpy
  from six.moves import range
  import tensorflow
  from tf_agents.bandits.agents import utils
  from tf_agents.bandits.environments import wheel_py_environment
label_desc: Use image node_id 18 for calling a global function with example usage: tf_wheel_bandit_compute_optimal_reward(observation, delta, mu_inside, mu_high) and returns: tf