code: def test_high_dimension_action_space():
      """
      Test for continuous action space
      with more than one action.
      """
      env = gym.make("Pendulum-v0")
      # Patch the action space
      env.action_space = spaces.Box(
          low=-1, high=1, shape=(20,), dtype=np.float32
      )
  
      # Patch to avoid error
      def patched_step(_action):
          return env.observation_space.sample(), 0.0, False, {}
  
      env.step = patched_step
      check_env(env)
  
file_path: stable-baselines/tests/test_envs.py
imports: import pytest
  import gym
  from gym import spaces
  import numpy
  from stable_baselines.common.env_checker import check_env
  from stable_baselines.common.bit_flipping_env import BitFlippingEnv
  from stable_baselines.common.identity_env import IdentityEnv, IdentityEnvBox, IdentityEnvMultiBinary, IdentityEnvMultiDiscrete
label_desc: Use image node_id 3 for calling a global function with example usage: test_high_dimension_action_space() and returns: env,  int,  False,  dict