code: def check_shape(make_env, model_class, shape_1, shape_2):
      model = model_class(
          policy="MlpPolicy", env=DummyVecEnv([make_env])
      )
  
      env0 = make_env()
      env1 = DummyVecEnv([make_env])
  
      for env, expected_shape in [(env0, shape_1), (env1, shape_2)]:
  
          def callback(locals_, _globals):
              assert np.array(locals_["action"]).shape == expected_shape
  
          evaluate_policy(
              model, env, n_eval_episodes=5, callback=callback
          )
  
file_path: stable-baselines/tests/test_auto_vec_detection.py
imports: import pytest
  import numpy
  from stable_baselines import A2C, ACER, ACKTR, DDPG, DQN, PPO1, PPO2, SAC, TRPO, TD3
  from stable_baselines.common.vec_env import DummyVecEnv
  from stable_baselines.common.identity_env import IdentityEnv, IdentityEnvBox, IdentityEnvMultiBinary, IdentityEnvMultiDiscrete
  from stable_baselines.common.evaluation import evaluate_policy
label_desc: Use image node_id 1 for calling a global function with example usage: check_shape(make_env, model_class, shape_1, shape_2) without return types