code: def _run_test_rollout(env: MazeEnv, n_episodes: int = 5):
      reporting_queue = MockQueue()
      seeding_queue = MockQueue()
  
      for _ in range(n_episodes):
          seeding_queue.put((1337, 1337))
  
      ParallelRolloutWorker.run(
          env_config=env,
          wrapper_config={},
          agent_config=RandomPolicy(
              action_spaces_dict=env.action_spaces_dict
          ),
          deterministic=False,
          max_episode_steps=3,
          record_trajectory=False,
          input_directory=None,
          reporting_queue=reporting_queue,
          seeding_queue=seeding_queue,
      )
  
      assert len(reporting_queue.items) == n_episodes
  
      for r in reporting_queue.items:
          assert isinstance(r, EpisodeStatsReport)
  
imports: import queue
  from collections import deque
  from typing import Any, Type, Optional
  from maze.core.agent.random_policy import RandomPolicy
  from maze.core.env.maze_env import MazeEnv
  from maze.core.env.observation_conversion import ObservationType
  from maze.core.rollout.parallel_rollout_runner import ParallelRolloutWorker, EpisodeStatsReport
  from maze.test.shared_test_utils.dummy_env.dummy_core_env import DummyCoreEnvironment
  from maze.test.shared_test_utils.dummy_env.dummy_maze_env import DummyEnvironment
  from maze.test.shared_test_utils.dummy_env.space_interfaces.action_conversion.dict import DictActionConversion
  from maze.test.shared_test_utils.dummy_env.space_interfaces.observation_conversion.dict import ObservationConversion
label_desc: Use image node_id 2 for calling a global function with example usage: _run_test_rollout(env, n_episodes) without return types