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* 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
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How to create new environments for Gym
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Create a new repo called gym-foo, which should also be a PIP package.
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A good example is https://github.com/openai/gym-soccer.
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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
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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 )
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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', )
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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
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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): ...
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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')