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","."]
code: def __init__(
      self,
      action_record_path: Optional[Union[ActionRecord, str]],
      with_agent_actions: bool,
  ):
      super().__init__()
  
      self._with_agent_actions = with_agent_actions
  
      self.action_record = None
      if action_record_path is not None:
          self.load_action_record(action_record_path)
  
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 1 to create a new ReplayRecordedActionsPolicy object from inherited base classes: Policy with example: obj = ReplayRecordedActionsPolicy(action_record_path, with_agent_actions)