code: def test_vectorized_rollout():
      concurrency = 3
      vectorized_env = SequentialVectorEnv(
          [build_dummy_structured_env] * concurrency
      )
  
      standard_env = build_dummy_structured_env()
      assert (
          vectorized_env.observation_spaces_dict
          == standard_env.observation_spaces_dict
      )
      assert (
          vectorized_env.action_spaces_dict
          == standard_env.action_spaces_dict
      )
  
      policy = DistributedRandomPolicy(
          vectorized_env.action_spaces_dict, concurrency=concurrency
      )
  
      observation = vectorized_env.reset()
      for _ in range(3):
          action = policy.compute_action(
              observation,
              actor_id=vectorized_env.actor_id(),
              maze_state=None,
          )
          observation, reward, done, info = vectorized_env.step(action)
  
imports: from maze.core.agent.random_policy import DistributedRandomPolicy
  from maze.test.shared_test_utils.helper_functions import build_dummy_structured_env
  from maze.train.parallelization.vector_env.sequential_vector_env import SequentialVectorEnv
label_desc: Use image node_id 1 for calling a global function with example usage: test_vectorized_rollout() without return types