code: def testValue(self, network_cls):
      actor_network = network_cls(self._action_spec)
      value_network = DummyValueNet()
  
      policy = ppo_policy.PPOPolicy(
          self._time_step_spec,
          self._action_spec,
          actor_network=actor_network,
          value_network=value_network,
      )
  
      batch_size = tf.compat.dimension_value(
          self._time_step.step_type.shape[0]
      )
      policy_state = policy.get_initial_state(batch_size=batch_size)
      value_pred, unused_policy_state = policy.apply_value_network(
          self._time_step.observation,
          self._time_step.step_type,
          policy_state,
      )
      self.assertEqual(value_pred.shape.as_list(), [1, 1])
      self.assertEqual(value_pred.dtype, tf.float32)
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(value_pred)
  
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.agents.ppo import ppo_policy
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import mask_splitter_network
  from tf_agents.networks import network
  from tf_agents.networks import sequential
  from tf_agents.networks import value_network
  from tf_agents.specs import distribution_spec
  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 11 for calling the PPOPolicyTest obj's underlying member method code with example usage: obj.testValue(network_cls) without return types