class_docstr: Hindsight Experience Replay (HER) https://arxiv.org/abs/1707.01495
  
  :param policy: (BasePolicy or str) The policy model to use (MlpPolicy, CnnPolicy, CnnLstmPolicy, ...)
  :param env: (Gym environment or str) The environment to learn from (if registered in Gym, can be str)
  :param model_class: (OffPolicyRLModel) The off policy RL model to apply Hindsight Experience Replay
      currently supported: DQN, DDPG, SAC
  :param n_sampled_goal: (int)
  :param goal_selection_strategy: (GoalSelectionStrategy or str)
code: def _save_to_file(
      self, save_path, data=None, params=None, cloudpickle=False
  ):
      # HACK to save the replay wrapper
      # or better to save only the replay strategy and its params?
      # it will not work with VecEnv
      data["n_sampled_goal"] = self.n_sampled_goal
      data["goal_selection_strategy"] = self.goal_selection_strategy
      data["model_class"] = self.model_class
      data["her_obs_space"] = self.observation_space
      data["her_action_space"] = self.action_space
      super()._save_to_file(
          save_path, data, params, cloudpickle=cloudpickle
      )
  
imports: import functools
  from stable_baselines.common import BaseRLModel
  from stable_baselines.common import OffPolicyRLModel
  from stable_baselines.common.base_class import _UnvecWrapper
  from stable_baselines.common.vec_env import VecEnvWrapper
  from .replay_buffer import HindsightExperienceReplayWrapper, KEY_TO_GOAL_STRATEGY
  from .utils import HERGoalEnvWrapper
label_desc: Use image node_id 14 for calling the HER obj's underlying member method code with example usage: obj._save_to_file(save_path, data, params, cloudpickle) without return types