code: def _get_experience(initial_step, action_step, final_step):
      single_experience = driver_utils.trajectory_for_bandit(
          initial_step, action_step, final_step
      )
      # Adds a 'time' dimension.
      return tf.nest.map_structure(
          lambda x: tf.expand_dims(tf.convert_to_tensor(x), 1),
          single_experience,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.agents import lin_ucb_agent
  from tf_agents.bandits.agents import mixture_agent
  from tf_agents.bandits.agents import neural_epsilon_greedy_agent
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.policies import mixture_policy
  from tf_agents.networks import q_network
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 4 for calling a global function with example usage: _get_experience(initial_step, action_step, final_step) and returns: tf