ray/examples/custom_env/custom_env.py
2018-04-13 00:57:00 -07:00

58 lines
1.6 KiB
Python

"""Example of a custom gym environment. Run this for a demo."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import gym
from gym.spaces import Discrete, Box
from gym.envs.registration import EnvSpec
import ray
from ray.tune import run_experiments
from ray.tune.registry import register_env
class SimpleCorridor(gym.Env):
"""Example of a custom env in which you have to walk down a corridor.
You can configure the length of the corridor via the env config."""
def __init__(self, config):
self.end_pos = config["corridor_length"]
self.cur_pos = 0
self.action_space = Discrete(2)
self.observation_space = Box(
0.0, self.end_pos, shape=(1,), dtype=np.float32)
self._spec = EnvSpec("SimpleCorridor-{}-v0".format(self.end_pos))
def reset(self):
self.cur_pos = 0
return [self.cur_pos]
def step(self, action):
assert action in [0, 1]
if action == 0 and self.cur_pos > 0:
self.cur_pos -= 1
elif action == 1:
self.cur_pos += 1
done = self.cur_pos >= self.end_pos
return [self.cur_pos], 1 if done else 0, done, {}
if __name__ == "__main__":
env_creator_name = "corridor"
register_env(env_creator_name, lambda config: SimpleCorridor(config))
ray.init()
run_experiments({
"demo": {
"run": "PPO",
"env": "corridor",
"config": {
"env_config": {
"corridor_length": 5,
},
},
},
})