ray/rllib/examples/env/d4rl_env.py
Michael Luo 4cbe13cdfd
[RLlib] CQL loss fn fixes, MuJoCo + Pendulum benchmarks, offline-RL example script w/ json file. (#15603)
Co-authored-by: Sven Mika <sven@anyscale.io>
Co-authored-by: sven1977 <svenmika1977@gmail.com>
2021-05-04 19:06:19 +02:00

44 lines
835 B
Python

"""
8 Environments from D4RL Environment.
Use fully qualified class-path in your configs:
e.g. "env": "ray.rllib.examples.env.d4rl_env.halfcheetah_random".
"""
import gym
try:
import d4rl
d4rl.__name__ # Fool LINTer.
except ImportError:
d4rl = None
def halfcheetah_random():
return gym.make("halfcheetah-random-v0")
def halfcheetah_medium():
return gym.make("halfcheetah-medium-v0")
def halfcheetah_expert():
return gym.make("halfcheetah-expert-v0")
def halfcheetah_medium_replay():
return gym.make("halfcheetah-medium-replay-v0")
def hopper_random():
return gym.make("hopper-random-v0")
def hopper_medium():
return gym.make("hopper-medium-v0")
def hopper_expert():
return gym.make("hopper-expert-v0")
def hopper_medium_replay():
return gym.make("hopper-medium-replay-v0")