enjoy.py throws error about observation space with HalfCheetahBulletEnv-v0 and own saved model · Issue #64 · araffin/rl-baselines-zoo · GitHub
More Web Proxy on the site http://driver.im/
You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository was archived by the owner on May 9, 2025. It is now read-only.
Playing around with stable baselines 2.9.0 (installed with pip) on Ubuntu 18.04.4 LTS with Python 3.6.9, gym 0.16.0, tensorflow 1.14.0 and pybullet 2.6.5.
so that enjoy.py loads the model I have trained and saved with train.py, I get the following error..
"Error: the environment passed must have at least the same observation space as the model was trained on."
When I've been trying to see what the problem is today I've noticed that, because of the stored hyperparameters for ppo2 HalfCheetahBulletEnv-v0, train.py wraps the training environment in the TimeFeatureWrapper wrapper from utils/wrappers.py but enjoy.py does not because end up going into the elif "Bullet" in env_id: statement in the create_test_env() method in utils/utils.py.
I've looked and the wrapper changes the observation space from (26,) to (27,) so that may be what it is complaining about in the error message.
Am I barking up the right tree and how come the error doesn't occur with the zoo trained_agents saved models?
Thank you!
The text was updated successfully, but these errors were encountered:
without the --exp-id param I got the error message 'ValueError: No model found for ppo2 on HalfCheetahBulletEnv-v0, path: logs/ppo2/HalfCheetahBulletEnv-v0.zip' and ended up pulling the zip file out of the HalfCheetahBulletEnv-v0_1 subdirectory and into logs/ppo2/ so that it was in the place I though the load() function was looking for it, but didn't move the associated directory with the config.yaml, obs_rms.pkl and ret_rms.pkl files inside.. and it appears to be that which has caused the model to be located but the observation space error to be thrown. Putting the zip file back where it ought to be and using --exp-id works fine.
Whilst your reading this, you know the benchmark.md file, I'm assuming the n_timesteps column is the number of steps when evaluating, not the number of training timesteps. Is there anywhere that gives the number of training timesteps for the trained_agents. In baselines its 1 million, just wondering if it's the same.
Hi,
Playing around with stable baselines 2.9.0 (installed with pip) on Ubuntu 18.04.4 LTS with Python 3.6.9, gym 0.16.0, tensorflow 1.14.0 and pybullet 2.6.5.
When I run
all is well.
When I run
so that enjoy.py loads the model I have trained and saved with train.py, I get the following error..
"Error: the environment passed must have at least the same observation space as the model was trained on."
When I've been trying to see what the problem is today I've noticed that, because of the stored hyperparameters for ppo2 HalfCheetahBulletEnv-v0, train.py wraps the training environment in the TimeFeatureWrapper wrapper from utils/wrappers.py but enjoy.py does not because end up going into the
elif "Bullet" in env_id:
statement in the create_test_env() method in utils/utils.py.I've looked and the wrapper changes the observation space from (26,) to (27,) so that may be what it is complaining about in the error message.
Am I barking up the right tree and how come the error doesn't occur with the zoo trained_agents saved models?
Thank you!
The text was updated successfully, but these errors were encountered: