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","."]
docstr: Clip action record to maximum length.
  
  :param max_items: Maximum number of items in action record.
docstr_tok: ["Clip","action","record","to","maximum","length",".",":","param","max_items",":","Maximum","number","of","items","in","action","record","."]
code: def clip(self, max_items: int) -> None:
      """Clip action record to maximum length.
  
      :param max_items: Maximum number of items in action record.
      """
      self.maze_actions = dict(
          [
              (key, value)
              for key, value in list(self.maze_actions.items())[
                  :max_items
              ]
          ]
      )
  
      self.agent_actions = dict(
          [
              (key, value)
              for key, value in list(self.agent_actions.items())[
                  :max_items
              ]
          ]
      )
  
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 9 for calling the ActionRecord obj's underlying member method code with example usage: obj.clip(max_items) without return types