class_docstr: Action record holding either maze_action objects of agent actions for later deterministic (seeded) replays.
  
  :param seed: The seed identifying the respective deterministic episode for the action record.
class_docstr_tok: ["Action","record","holding","either","maze_action","objects","of","agent","actions","for","later","deterministic","(","seeded",")","replays",".",":","param","seed",":","The","seed","identifying","the","respective","deterministic","episode","for","the","action","record","."]
code: def __init__(self, seed: int):
      self.seed = seed
      self.maze_actions: Dict[int, MazeActionType] = dict()
      self.agent_actions: Dict[
          int, Dict[ActorID, ActionType]
      ] = defaultdict(dict)
  
      # corresponding reward for action record (useful for deterministic replay checks)
      self.cum_action_record_reward = None
  
file_path: maze/maze/core/trajectory_recording/records/action_record.py
imports: import os
  import pickle
  from collections import defaultdict
  from typing import Dict
  from maze.core.env.action_conversion import ActionType
  from maze.core.env.maze_action import MazeActionType
  from maze.core.env.structured_env import ActorID
label_desc: Use image node_id 1 to create a new ActionRecord object  with example: obj = ActionRecord(seed)