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Description
🐛 Bug
When using the "check_env "function of "stable_baselines3.common.env_checker" with an environment wrapped in a "FrameStack" wrapper from "gymnasium.wrappers", I get an error on the type of observation returned.
Indeed, the observation has a <class 'gymnasium.wrappers.frame_stack.LazyFrames'> instead of a np.array type (which is normal because it is indicated in the gymnasium documentation).
But then I can still use this environment with FrameStacked observation to train an agent. I know it is not critical but is this normal that the check_env warns about a problem while the environment can still be used to train agents with stable_baselines3 algorithms?
To Reproduce
import gymnasium as gym
from gymnasium.wrappers import FrameStack
from stable_baselines3.common.env_checker import check_env
env = gym.make("CartPole-v1")
env = FrameStack(env, n_stack)
# check the obs type
obs, info = env.reset()
print(type(obs))
check_env(env, warn = True)Relevant log output / Error message
<class 'gymnasium.wrappers.frame_stack.LazyFrames'>
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
Cell In[8], line 7
4 obs, info = env.reset()
5 print(type(obs))
----> 7 check_env(env, warn = True)
File ~/.local/lib/python3.10/site-packages/stable_baselines3/common/env_checker.py:433, in check_env(env, warn, skip_render_check)
428 warnings.warn(
429 f"Your action space has dtype {action_space.dtype}, we recommend using np.float32 to avoid cast errors."
430 )
432 # ============ Check the returned values ===============
--> 433 _check_returned_values(env, observation_space, action_space)
435 # ==== Check the render method and the declared render modes ====
436 if not skip_render_check:
File ~/.local/lib/python3.10/site-packages/stable_baselines3/common/env_checker.py:274, in _check_returned_values(env, observation_space, action_space)
272 raise AssertionError(f"Error while checking key={key}: " + str(e)) from e
273 else:
--> 274 _check_obs(obs, observation_space, "reset")
276 # Sample a random action
277 action = action_space.sample()
File ~/.local/lib/python3.10/site-packages/stable_baselines3/common/env_checker.py:189, in _check_obs(obs, observation_space, method_name)
187 assert np.issubdtype(type(obs), np.integer), f"The observation returned by `{method_name}()` method must be an int"
188 elif _is_numpy_array_space(observation_space):
--> 189 assert isinstance(obs, np.ndarray), f"The observation returned by `{method_name}()` method must be a numpy array"
191 # Additional checks for numpy arrays, so the error message is clearer (see GH#1399)
192 if isinstance(obs, np.ndarray):
193 # check obs dimensions, dtype and bounds
AssertionError: The observation returned by `reset()` method must be a numpy arraySystem Info
I am using these versions :
- Python: 3.10.6
- stable_baselines : 2.0.0a5
- gymnasium : 0.28.1
Checklist
- I have checked that there is no similar issue in the repo
- I have read the documentation
- I have provided a minimal working example to reproduce the bug
- I've used the markdown code blocks for both code and stack traces.