code: def compute_optimal_reward_with_movielens_environment(
      observation, environment
  ):
      """Helper function for gin configurable Regret metric."""
      del observation
      return tf.py_function(
          environment.compute_optimal_reward, [], 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 19 for calling a global function with example usage: compute_optimal_reward_with_movielens_environment(observation, environment) and returns: tf