code: def test_obs_and_action_spaces_are_gym_spaces(self):
      env = RandomEnv()
      observation_space = env.observation_space
      env.observation_space = "not a gym space"
      with pytest.raises(
          ValueError, match="Observation space must be a gym.space"
      ):
          check_env(env)
      env.observation_space = observation_space
      env.action_space = "not an action space"
      with pytest.raises(
          ValueError, match="Action space must be a gym.space"
      ):
          check_env(env)
  
imports: import logging
  import unittest
  from unittest.mock import MagicMock, Mock
  import gymnasium
  import numpy
  import pytest
  from gymnasium.spaces import Box, Dict, Discrete
  from ray.rllib.env.base_env import convert_to_base_env
  from ray.rllib.env.multi_agent_env import MultiAgentEnvWrapper, make_multi_agent
  from ray.rllib.examples.env.parametric_actions_cartpole import ParametricActionsCartPole
  from ray.rllib.examples.env.random_env import RandomEnv
  from ray.rllib.utils.pre_checks.env import check_base_env, check_env, check_gym_environments, check_multiagent_environments
label_desc: Use image node_id 3 for calling the TestGymCheckEnv obj's underlying member method code with example usage: obj.test_obs_and_action_spaces_are_gym_spaces() without return types