code: def test_same_actor_net_output(self):
      if not tf.executing_eagerly():
          self.skipTest(
              "Skipping test: sequential networks not supported in TF1"
          )
      observation_tensor_spec = tf.TensorSpec(
          shape=[1], dtype=tf.float32
      )
      action_tensor_spec = tensor_spec.BoundedTensorSpec(
          (8,), tf.float32, -1, 1
      )
  
      actor_net_lib = ppo_actor_network.PPOActorNetwork()
      actor_net_lib.seed_stream_class = DeterministicSeedStream
      actor_net_sequential = actor_net_lib.create_sequential_actor_net(
          fc_layer_units=(1,),
          action_tensor_spec=action_tensor_spec,
          seed=1,
      )
  
      actor_net_actor_dist = (
          actor_distribution_network.ActorDistributionNetwork(
              observation_tensor_spec,
              action_tensor_spec,
              fc_layer_params=(1,),
              activation_fn=tf.nn.tanh,
              kernel_initializer=tf.keras.initializers.Orthogonal(
                  seed=1
              ),
              seed_stream_class=DeterministicSeedStream,
              seed=1,
          )
      )
  
      sample_observation = tf.constant([[1], [2]], dtype=tf.float32)
      tf.random.set_seed(111)
      sequential_output_dist, _ = actor_net_sequential(
          sample_observation,
          step_type=ts.StepType.MID,
          network_state=(),
      )
      tf.random.set_seed(111)
      actor_dist_output_dist, _ = actor_net_actor_dist(
          sample_observation,
          step_type=ts.StepType.MID,
          network_state=(),
      )
      self.assertAllEqual(
          sequential_output_dist.mean(), actor_dist_output_dist.mean()
      )
      self.assertAllEqual(
          sequential_output_dist.stddev(),
          actor_dist_output_dist.stddev(),
      )
  
imports: from absl import flags
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.agents.ppo import ppo_actor_network
  from tf_agents.agents.ppo import ppo_agent
  from tf_agents.agents.ppo import ppo_policy
  from tf_agents.distributions import utils
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import value_network
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import test_utils
label_desc: Use image node_id 5 for calling the PpoActorNetworkTest obj's underlying member method code with example usage: obj.test_same_actor_net_output() without return types