code: def test_her(
      model_class, goal_selection_strategy, discrete_obs_space
  ):
      env = BitFlippingEnv(
          N_BITS,
          continuous=model_class in [DDPG, SAC, TD3],
          max_steps=N_BITS,
          discrete_obs_space=discrete_obs_space,
      )
  
      # Take random actions 10% of the time
      kwargs = (
          {"random_exploration": 0.1}
          if model_class in [DDPG, SAC, TD3]
          else {}
      )
      model = HER(
          "MlpPolicy",
          env,
          model_class,
          n_sampled_goal=4,
          goal_selection_strategy=goal_selection_strategy,
          verbose=0,
          **kwargs,
      )
      model.learn(150)
  
file_path: stable-baselines/tests/test_her.py
imports: import os
  import pytest
  from stable_baselines import HER, DQN, SAC, DDPG, TD3
  from stable_baselines.her import GoalSelectionStrategy, HERGoalEnvWrapper
  from stable_baselines.her.replay_buffer import KEY_TO_GOAL_STRATEGY
  from stable_baselines.common.bit_flipping_env import BitFlippingEnv
  from stable_baselines.common.vec_env import DummyVecEnv, VecNormalize
label_desc: Use image node_id 2 for calling a global function with example usage: test_her(model_class, goal_selection_strategy, discrete_obs_space) without return types