Closed ieow closed 6 years ago
The code only supports discrete action environments currently. Please use the non-gpu version for continuous action spaces.
Based on my understanding, openai gym's CartPole-v0 is a discrete action environment. https://github.com/openai/gym/wiki/CartPole-v0
Please correct me if I am wrong.
@ieow you are correct, the Gym wrapper I created was experimental and clearly has some issues. The appropriate way is probably to check if the gym environment return a spaces.Box or spaces.Discrete. Either way, gym.* environments still needs some work. For now, you can just modify it to return isinstance(env[0].action_space, gym.spaces.Discrete)
Thanks. Somehow, I managed to get it running after some modification based on tf_atari.py
@ieow Glad to hear, I'll reopen the ticket until we fix it, feel free to make a pull request if you are comfortable with your solution.
Pull request submitted
Hi, I am trying to run gpu-implementation es.py using gym enviroment gym.CartPole-v1 I edited the configuration file es_atari_config.json by changing "frostbrite" to "gym.CartPole-V1" and encounter error below
I notice that the GymEnv in tf_env.py having property of discrete_action that will only return False which is triggering the assert in the get_ref_batch
class GymEnv(PythonEnv): ... @property def discrete_action(self): return False
Is openai gym's enviroment ready for run?