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c364506710
* 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
75 lines
1.7 KiB
Markdown
75 lines
1.7 KiB
Markdown
# 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:
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```sh
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gym-foo/
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README.md
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setup.py
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gym_foo/
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__init__.py
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envs/
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__init__.py
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foo_env.py
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foo_extrahard_env.py
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```
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* `gym-foo/setup.py` should have:
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```python
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from setuptools import setup
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setup(name='gym_foo',
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version='0.0.1',
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install_requires=['gym'] # And any other dependencies foo needs
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)
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```
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* `gym-foo/gym_foo/__init__.py` should have:
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```python
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from gym.envs.registration import register
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register(
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id='foo-v0',
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entry_point='gym_foo.envs:FooEnv',
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)
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register(
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id='foo-extrahard-v0',
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entry_point='gym_foo.envs:FooExtraHardEnv',
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)
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```
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* `gym-foo/gym_foo/envs/__init__.py` should have:
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```python
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from gym_foo.envs.foo_env import FooEnv
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from gym_foo.envs.foo_extrahard_env import FooExtraHardEnv
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```
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* `gym-foo/gym_foo/envs/foo_env.py` should look something like:
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```python
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from typing import Optional
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import gym
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from gym import error, spaces, utils
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from gym.utils import seeding
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class FooEnv(gym.Env):
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metadata = {'render.modes': ['human']}
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def __init__(self):
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...
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def step(self, action):
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...
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def reset(self, seed: Optional[int] = None):
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super().reset(seed=seed)
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...
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def render(self, mode='human'):
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...
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def close(self):
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...
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```
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* 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')`
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