Closed Robokan closed 5 months ago
Hello, i guess if you use another os (for instance linux in a google colab), it does work? make sure to have latest version of tensorflow proba and jax, support for mac os might be experimental.
I have the latest JAX working great on macOS. I am even running the Brax simulator on top of it. Your repo would be great for speeding up my stable-baselines/Gym code. I really appreciate you posting it. Any ideas of how to go about debugging this?
I did try it in on Google Colab and your example does work there.
I did try it in on Google Colab and your example does work there.
I have the latest JAX working great on macOS.
Then it seems that it comes from tensorflow probability (which is in jax only despite the name), you should probably open an issue there.
Thanks. I will see if there is anything about this in JAX.
Important Note: We do not do technical support, nor consulting and don't answer personal questions per email. Please post your question on the RL Discord, Reddit or Stack Overflow in that case.
If your issue is related to a custom gym environment, please use the custom gym env template.
🐛 Bug
A clear and concise description of what the bug is.
If I run the example in your readme it crashes
To Reproduce
Steps to reproduce the behavior.
import gym
from sbx import TQC, DroQ, SAC, PPO, DQN
env = gym.make("Pendulum-v1")
model = TQC("MlpPolicy", env, verbose=1) model.learn(total_timesteps=10_000, progress_bar=True)
vec_env = model.get_env() obs = vec_env.reset() for i in range(1000): action, _states = model.predict(obs, deterministic=True) obs, reward, done, info = vec_env.step(action) vec_env.render()
vec_env.close()
Please try to provide a minimal example to reproduce the bug. Error messages and stack traces are also helpful.
Please use the markdown code blocks for both code and stack traces.
Additional context
Add any other context about the problem here.
Checklist