code: def _get_action_step(action):
      return policy_step.PolicyStep(
          action=tf.convert_to_tensor(action),
          info=policy_utilities.PolicyInfo(),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from typing import List, Tuple
  import numpy
  import tensorflow
  from tf_agents.bandits.agents import greedy_multi_objective_neural_agent
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.multi_objective import multi_objective_scalarizer
  from tf_agents.bandits.networks import global_and_arm_feature_network
  from tf_agents.bandits.networks import heteroscedastic_q_network
  from tf_agents.bandits.specs import utils
  from tf_agents.networks import network
  from tf_agents.policies import utils
  from tf_agents.specs import array_spec
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import common
label_desc: Use image node_id 3 for calling a global function with example usage: _get_action_step(action) and returns: policy_step