Files
Gymnasium/docs/creating_environments.md
Ariel Kwiatkowski c364506710 Seeding update (#2422)
* Ditch most of the seeding.py and replace np_random with the numpy default_rng. Let's see if tests pass

* Updated a bunch of RNG calls from the RandomState API to Generator API

* black; didn't expect that, did ya?

* Undo a typo

* blaaack

* More typo fixes

* Fixed setting/getting state in multidiscrete spaces

* Fix typo, fix a test to work with the new sampling

* Correctly (?) pass the randomly generated seed if np_random is called with None as seed

* Convert the Discrete sample to a python int (as opposed to np.int64)

* Remove some redundant imports

* First version of the compatibility layer for old-style RNG. Mainly to trigger tests.

* Removed redundant f-strings

* Style fixes, removing unused imports

* Try to make tests pass by removing atari from the dockerfile

* Try to make tests pass by removing atari from the setup

* Try to make tests pass by removing atari from the setup

* Try to make tests pass by removing atari from the setup

* First attempt at deprecating `env.seed` and supporting `env.reset(seed=seed)` instead. Tests should hopefully pass but throw up a million warnings.

* black; didn't expect that, didya?

* Rename the reset parameter in VecEnvs back to `seed`

* Updated tests to use the new seeding method

* Removed a bunch of old `seed` calls.

Fixed a bug in AsyncVectorEnv

* Stop Discrete envs from doing part of the setup (and using the randomness) in init (as opposed to reset)

* Add explicit seed to wrappers reset

* Remove an accidental return

* Re-add some legacy functions with a warning.

* Use deprecation instead of regular warnings for the newly deprecated methods/functions
2021-12-08 16:14:15 -05:00

1.7 KiB

How to create new environments for Gym

  • 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:

    from typing import Optional
    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, seed: Optional[int] = None):
        super().reset(seed=seed)
        ...
      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 with gym.make('gym_foo:foo-v0')