code: def test_offpolicy_normalization(model_class):
      if model_class == DQN:
          env = DummyVecEnv([lambda: gym.make("CartPole-v1")])
      else:
          env = DummyVecEnv([make_env])
      env = VecNormalize(
          env,
          norm_obs=True,
          norm_reward=True,
          clip_obs=10.0,
          clip_reward=10.0,
      )
  
      model = model_class("MlpPolicy", env, verbose=1)
      model.learn(total_timesteps=1000)
      # Check getter
      assert isinstance(model.get_vec_normalize_env(), VecNormalize)
  
file_path: stable-baselines/tests/test_vec_normalize.py
imports: import subprocess
  import gym
  import numpy
  import pytest
  from stable_baselines import DDPG, DQN, SAC, TD3
  from stable_baselines.common.running_mean_std import RunningMeanStd
  from stable_baselines.common.vec_env import DummyVecEnv, VecNormalize, VecFrameStack, sync_envs_normalization, unwrap_vec_normalize
  from .test_common import _assert_eq
label_desc: Use image node_id 9 for calling a global function with example usage: test_offpolicy_normalization(model_class) without return types