--- name: "\U0001F916 Custom Gym Environment Issue" about: How to report an issue when using a custom Gym environment labels: question, custom gym env --- **Important Note: We do not do technical support, nor consulting** and don't answer personal questions per email. Please post your question on [reddit](https://www.reddit.com/r/reinforcementlearning/) or [stack overflow](https://stackoverflow.com/) in that case. ### 🤖 Custom Gym Environment **Please check your environment first using**: ```python from stable_baselines3.common.env_checker import check_env env = CustomEnv(arg1, ...) # It will check your custom environment and output additional warnings if needed check_env(env) ``` ### Describe the bug A clear and concise description of what the bug is. ### Code example Please try to provide a minimal example to reproduce the bug. For a custom environment, you need to give at least the observation space, action space, `reset()` and `step()` methods (see working example below). Error messages and stack traces are also helpful. Please use the [markdown code blocks](https://help.github.com/en/articles/creating-and-highlighting-code-blocks) for both code and stack traces. ```python import gym import numpy as np from stable_baselines3 import A2C from stable_baselines3.common.env_checker import check_env class CustomEnv(gym.Env): def __init__(self): super(CustomEnv, self).__init__() self.observation_space = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(14,)) self.action_space = gym.spaces.Box(low=-1, high=1, shape=(6,)) def reset(self): return self.observation_space.sample() def step(self, action): obs = self.observation_space.sample() reward = 1.0 done = False info = {} return obs, reward, done, info env = CustomEnv() check_env(env) model = A2C("MlpPolicy", env, verbose=1).learn(1000) ``` ```bash Traceback (most recent call last): File ... ``` ### System Info Describe the characteristic of your environment: * Describe how the library was installed (pip, docker, source, ...) * GPU models and configuration * Python version * PyTorch version * Gym version * Versions of any other relevant libraries ### Additional context Add any other context about the problem here. ### Checklist - [ ] I have read the [documentation](https://stable-baselines3.readthedocs.io/en/master/) (**required**) - [ ] I have checked that there is no similar [issue](https://github.com/DLR-RM/stable-baselines3/issues) in the repo (**required**) - [ ] I have checked my env using the env checker (**required**) - [ ] I have provided a minimal working example to reproduce the bug (**required**)