class_docstr: Dummy structured (multi-agent, with two agents) core environment.
  
  :param observation_space: The observation space to sample observations from
class_docstr_tok: ["Dummy","structured","(","multi-agent",",","with","two","agents",")","core","environment",".",":","param","observation_space",":","The","observation","space","to","sample","observations","from"]
docstr: Return reward of 1 for each actor as the last reward
docstr_tok: ["Return","reward","of","1","for","each","actor","as","the","last","reward"]
code: def get_actor_rewards(self) -> Optional[np.ndarray]:
      """Return reward of 1 for each actor as the last reward"""
      return np.array([1, 1])
  
file_path: maze/maze/test/shared_test_utils/dummy_env/dummy_structured_core_env.py
imports: from typing import Tuple, Dict, Any, Optional
  import gym
  import numpy
  from maze.core.annotations import override
  from maze.core.env.core_env import CoreEnv
  from maze.core.env.structured_env import StepKeyType, ActorID
label_desc: Use image node_id 11 for calling the DummyStructuredCoreEnvironment obj's underlying member method code with example usage: obj.get_actor_rewards() and returns: np