code: def model_predict(model, env, n_steps, additional_check=None):
      """
      Test helper
      :param model: (rl model)
      :param env: (gym.Env)
      :param n_steps: (int)
      :param additional_check: (callable)
      """
      obs = env.reset()
      for _ in range(n_steps):
          action, _ = model.predict(obs)
          obs, reward, done, _ = env.step(action)
  
          if additional_check is not None:
              additional_check(obs, action, reward, done)
  
          if done:
              obs = env.reset()
  
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 1 for calling a global function with example usage: model_predict(model, env, n_steps, additional_check) without return types