code: def _check_unsupported_obs_spaces(
      env: gym.Env, observation_space: spaces.Space
  ) -> None:
      """Emit warnings when the observation space used is not supported by Stable-Baselines."""
  
      if isinstance(observation_space, spaces.Dict) and not isinstance(
          env, gym.GoalEnv
      ):
          warnings.warn(
              "The observation space is a Dict but the environment is not a gym.GoalEnv "
              "(cf https://github.com/openai/gym/blob/master/gym/core.py), "
              "this is currently not supported by Stable Baselines "
              "(cf https://github.com/hill-a/stable-baselines/issues/133), "
              "you will need to use a custom policy. "
          )
  
      if isinstance(observation_space, spaces.Tuple):
          warnings.warn(
              "The observation space is a Tuple,"
              "this is currently not supported by Stable Baselines "
              "(cf https://github.com/hill-a/stable-baselines/issues/133), "
              "you will need to flatten the observation and maybe use a custom policy. "
          )
  
file_path: stable-baselines/stable_baselines/common/env_checker.py
imports: import warnings
  from typing import Union
  import gym
  from gym import spaces
  import numpy
  from stable_baselines.common.vec_env import DummyVecEnv, VecCheckNan
label_desc: Use image node_id 3 for calling a global function with example usage: _check_unsupported_obs_spaces(env, observation_space) without return types