class_docstr: Parallel rollout runner that allows to collect features by replaying pre-computed action records.
  
  :param max_episode_steps: The maximum number of agent actions to take (careful these are not internal env steps).
  :param deterministic: Deterministic or stochastic action sampling.
  :param action_record_path: Path to action records.
  :param normalization_samples: Number of samples (=steps) to collect normalization statistics.
  :param n_processes: Count of processes to spread the rollout across.
  :param verbose: If True debug messages are printed to the command line.
code: def __init__(
      self,
      max_episode_steps: int,
      deterministic: bool,
      action_record_path: str,
      normalization_samples: int,
      n_processes: int,
      verbose: bool,
  ):
      super().__init__(
          n_episodes=0,
          max_episode_steps=max_episode_steps,
          deterministic=deterministic,
          record_trajectory=False,
          record_event_logs=False,
          n_processes=n_processes,
      )
      self.verbose = verbose
  
      self.action_record_paths = glob.glob(
          os.path.join(action_record_path, "*.pkl")
      )
      self.n_episodes = len(self.action_record_paths)
      self.normalization_samples = normalization_samples
  
      self.deterministic = True
  
imports: import glob
  import logging
  import os
  import traceback
  from multiprocessing import Queue, Process
  from typing import Iterable
  from omegaconf import DictConfig
  from maze.core.agent.replay_recorded_actions_policy import ReplayRecordedActionsPolicy
  from maze.core.annotations import override
  from maze.core.env.maze_env import MazeEnv
  from maze.core.rollout.parallel_rollout_runner import ParallelRolloutRunner, ParallelRolloutWorker, ExceptionReport
  from maze.core.rollout.rollout_runner import RolloutRunner
  from maze.core.utils.factory import ConfigType, CollectionOfConfigType
  from maze.core.wrappers.observation_normalization.observation_normalization_utils import obtain_normalization_statistics
  from maze.core.wrappers.observation_normalization.observation_normalization_wrapper import ObservationNormalizationWrapper
  from maze.core.wrappers.spaces_recording_wrapper import SpacesRecordingWrapper
  from maze.utils.bcolors import BColors
label_desc: Use image node_id 1 to create a new ActionRecordRolloutRunner object from inherited base classes: ParallelRolloutRunner with example: obj = ActionRecordRolloutRunner(max_episode_steps, deterministic, action_record_path, normalization_samples, n_processes, verbose)