code: def _time_step_batch(self):
      return ts.TimeStep(
          tf.constant(
              ts.StepType.FIRST,
              dtype=tf.int32,
              shape=[2],
              name="step_type",
          ),
          tf.constant(0.0, dtype=tf.float32, shape=[2], name="reward"),
          tf.constant(
              1.0, dtype=tf.float32, shape=[2], name="discount"
          ),
          tf.constant(
              [[1, 2], [3, 4]], dtype=tf.float32, name="observation"
          ),
      )
  
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.networks import actor_distribution_network
  from tf_agents.networks import network
  from tf_agents.policies import actor_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 3 for calling the ActorPolicyDiscreteActionsTest obj's underlying member method code with example usage: obj._time_step_batch() and returns: ts