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Gymnasium/docs/creating_environments.md

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# 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:
```sh
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:
```python
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:
```python
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:
```python
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:
```python
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 22:14:15 +01:00
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):
...
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 22:14:15 +01:00
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')`