class_docstr: A replay action record policy that executes in each (sub-)step the action stored in the provided action record.
  
  :param action_record_path: Action record or path to action record dump.
  :param with_agent_actions: If True agent actions are returned; else MazeActions.
class_docstr_tok: ["A","replay","action","record","policy","that","executes","in","each","(","sub-",")","step","the","action","stored","in","the","provided","action","record",".",":","param","action_record_path",":","Action","record","or","path","to","action","record","dump",".",":","param","with_agent_actions",":","If","True","agent","actions","are","returned",";","else","MazeActions","."]
docstr: Implementation of :py:attr:`~maze.core.agent.policy.Policy.compute_top_action_candidates`.
docstr_tok: ["Implementation","of",":","py",":","attr",":","`","~maze.core.agent.policy.Policy.compute_top_action_candidates","`","."]
code: def compute_top_action_candidates(
      self,
      observation: ObservationType,
      num_candidates: int,
      maze_state: Optional[MazeStateType],
      env: Optional[MazeEnv],
      actor_id: Union[str, int] = None,
  ) -> Tuple[Sequence[ActionType], Sequence[float]]:
      """
      Implementation of :py:attr:`~maze.core.agent.policy.Policy.compute_top_action_candidates`.
      """
      raise NotImplementedError
  
imports: import os.path
  from typing import Tuple
  from typing import Union, Optional, Sequence
  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.maze_action import MazeActionType
  from maze.core.env.maze_env import MazeEnv
  from maze.core.env.maze_state import MazeStateType
  from maze.core.env.observation_conversion import ObservationType
  from maze.core.env.structured_env import ActorID
  from maze.core.trajectory_recording.records.action_record import ActionRecord
label_desc: Use image node_id 7 for calling the ReplayRecordedActionsPolicy 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