code: def test_same_initialization(self):
      if not tf.executing_eagerly():
          self.skipTest(
              "Skipping test: sequential networks not supported in TF1"
          )
      tf.random.set_seed(111)
      agent_seq = PPOAgentSequential()
      seq_variables = agent_seq._actor_net.trainable_weights
  
      tf.random.set_seed(111)
      agent_act_dist = PPOAgentActorDist()
      act_dist_variables = agent_act_dist._actor_net.trainable_weights
  
      self.assertEqual(len(seq_variables), len(act_dist_variables))
      set_seq_weights = set()
      set_act_dist_weights = set()
      for i in range(len(seq_variables)):
          set_seq_weights.add(seq_variables[i].numpy().sum())
          set_act_dist_weights.add(act_dist_variables[i].numpy().sum())
      self.assertSetEqual(set_seq_weights, set_act_dist_weights)
  
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 3 for calling the PpoActorNetworkTest obj's underlying member method code with example usage: obj.test_same_initialization() without return types