code: def test_redistributes_actor_reward_if_available():
      env = build_dummy_maze_env_with_structured_core_env()
      rollout_generator = RolloutGenerator(env=env)
      policy = RandomPolicy(env.action_spaces_dict)
      trajectory = rollout_generator.rollout(policy, n_steps=1)
      assert np.all(trajectory.step_records[0].rewards == [1, 1])
  
imports: from typing import Dict, Any, Tuple
  import numpy
  from maze.core.agent.random_policy import RandomPolicy, DistributedRandomPolicy
  from maze.core.env.base_env import BaseEnv
  from maze.core.rollout.rollout_generator import RolloutGenerator
  from maze.core.wrappers.time_limit_wrapper import TimeLimitWrapper
  from maze.test.shared_test_utils.helper_functions import build_dummy_structured_env, build_dummy_maze_env, build_dummy_maze_env_with_structured_core_env
  from maze.test.shared_test_utils.helper_functions import flatten_concat_probabilistic_policy_for_env
  from maze.train.parallelization.vector_env.sequential_vector_env import SequentialVectorEnv
label_desc: Use image node_id 7 for calling a global function with example usage: test_redistributes_actor_reward_if_available() without return types