-
Create a new repo called gym-foo, which should also be a PIP package.
-
A good example is https://github.com/openai/gym-soccer.
-
It should have at least the following files:
gym-foo/ README.md setup.py gym_foo/ __init__.py envs/ __init__.py foo_env.py foo_extrahard_env.py
-
gym-foo/setup.py
should have:from setuptools import setup setup(name='gym_foo', version='0.0.1', install_requires=['gym'] # And any other dependencies foo needs )
-
gym-foo/gym_foo/__init__.py
should have:from gym.envs.registration import register register( id='foo-v0', entry_point='gym_foo.envs:FooEnv', ) register( id='foo-extrahard-v0', entry_point='gym_foo.envs:FooExtraHardEnv', )
-
gym-foo/gym_foo/envs/__init__.py
should have:from gym_foo.envs.foo_env import FooEnv from gym_foo.envs.foo_extrahard_env import FooExtraHardEnv
-
gym-foo/gym_foo/envs/foo_env.py
should look something like:import gym from gym import error, spaces, utils from gym.utils import seeding class FooEnv(gym.Env): metadata = {'render.modes': ['human']} def __init__(self): ... def step(self, action): ... def reset(self): ... def render(self, mode='human'): ... def close(self): ...
-
After you have installed your package with
pip install -e gym-foo
, you can create an instance of the environment withgym.make('gym_foo:foo-v0')