class_docstr: Dummy structured policy for the CartPole env.
  
  Useful mainly for showcase of the config scheme and for testing.
class_docstr_tok: ["Dummy","structured","policy","for","the","CartPole","env",".","Useful","mainly","for","showcase","of","the","config","scheme","and","for","testing","."]
docstr: implementation of :class:`~maze.core.agent.policy.Policy` interface
          
docstr_tok: ["implementation","of",":","class",":","`","~maze.core.agent.policy.Policy","`","interface"]
code: def compute_top_action_candidates(
      self,
      observation: ObservationType,
      num_candidates: Optional[int],
      maze_state: Optional[MazeStateType],
      env: Optional[BaseEnv],
      actor_id: ActorID = None,
  ) -> Tuple[Sequence[ActionType], Sequence[float]]:
      """implementation of :class:`~maze.core.agent.policy.Policy` interface"""
      raise NotImplementedError
  
file_path: maze/maze/core/agent/dummy_cartpole_policy.py
imports: from typing import Sequence, Tuple, Optional
  import gym
  from maze.core.agent.policy import Policy
  from maze.core.annotations import override
  from maze.core.env.action_conversion import ActionType
  from maze.core.env.base_env import BaseEnv
  from maze.core.env.maze_state import MazeStateType
  from maze.core.env.observation_conversion import ObservationType
  from maze.core.env.structured_env import ActorID
label_desc: Use image node_id 5 for calling the DummyCartPolePolicy obj's underlying member method code with example usage: obj.compute_top_action_candidates(observation, num_candidates, maze_state, env, actor_id) without return types