code: def _convert_string_vector_to_action_input(example):
      return (
          ts.TimeStep(
              step_type=tf.cast(
                  tf.strings.to_number(example[:, 0], tf.float32),
                  tf.int32,
              ),
              reward=tf.strings.to_number(example[:, 1], tf.float32),
              discount=tf.strings.to_number(example[:, 2], tf.float32),
              observation=tf.strings.to_number(
                  example[:, 3:7], tf.float32
              ),
          ),
          (),
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import shutil
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import q_network
  from tf_agents.networks import q_rnn_network
  from tf_agents.policies import actor_policy
  from tf_agents.policies import policy_saver
  from tf_agents.policies import q_policy
  from tf_agents.policies import tf_policy
  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 common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 3 for calling a global function with example usage: _convert_string_vector_to_action_input(example) and returns: ts,  