code: def test_model_id_updater(self):
      loc = 0.0
      scale = 0.5
      action_spec = tensor_spec.BoundedTensorSpec(
          [1], tf.float32, tf.float32.min, tf.float32.max
      )
      wrapped_policy = DistributionPolicy(
          distribution=tfp.distributions.Normal([loc], [scale]),
          time_step_spec=self._time_step_spec,
          action_spec=action_spec,
          info_spec={
              "test_info": tf.TensorSpec(
                  shape=(1,), dtype=tf.int32, name="test_info"
              )
          },
      )
      updater_info_spec = {
          "model_id": tf.TensorSpec(
              shape=(1,), dtype=tf.int32, name="model_id"
          )
      }
      updater_info_spec.update(wrapped_policy.info_spec)
      policy = policy_info_updater_wrapper.PolicyInfoUpdaterWrapper(
          policy=wrapped_policy,
          info_spec=updater_info_spec,
          updater_fn=ModelIdUpdater(),
          name="model_id_updater",
      )
  
      self.assertEqual(policy.time_step_spec, self._time_step_spec)
      self.assertEqual(policy.action_spec, action_spec)
  
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_step = ts.restart(observations, batch_size=2)
      action_step = policy.action(time_step)
      distribution_step = policy.distribution(time_step)
  
      tf.nest.assert_same_structure(action_spec, action_step.action)
      tf.nest.assert_same_structure(
          action_spec, distribution_step.action
      )
  
      self.assertListEqual(
          list(self.evaluate(action_step.info["model_id"])), [2]
      )
      self.assertListEqual(
          list(self.evaluate(distribution_step.info["model_id"])), [2]
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow.compat.v2
  import tensorflow_probability
  from tf_agents.policies import policy_info_updater_wrapper
  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 test_utils
label_desc: Use image node_id 2 for calling the PolicyInfoUpdaterWrapperTest obj's underlying member method code with example usage: obj.test_model_id_updater() without return types