mirror of
https://github.com/saymrwulf/stable-baselines3.git
synced 2026-05-18 21:30:19 +00:00
8f0b488bc5
* Update Gymnasium to v1.0.0a1 * Comment out `gymnasium.wrappers.monitor` (todo update to VideoRecord) * Fix ruff warnings * Register Atari envs * Update `getattr` to `Env.get_wrapper_attr` * Reorder imports * Fix `seed` order * Fix collecting `max_steps` * Copy and paste video recorder to prevent the need to rewrite the vec vide recorder wrapper * Use `typing.List` rather than list * Fix env attribute forwarding * Separate out env attribute collection from its utilisation * Update for Gymnasium alpha 2 * Remove assert for OrderedDict * Update setup.py * Add type: ignore * Test with Gymnasium main * Remove `gymnasium.logger.debug/info` * Fix github CI yaml * Run gym 0.29.1 on python 3.10 * Update lower bounds * Integrate video recorder * Remove ordered dict * Update changelog --------- Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>
100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
import warnings
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from inspect import signature
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from typing import Union
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import gymnasium
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try:
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import gym
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gym_installed = True
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except ImportError:
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gym_installed = False
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def _patch_env(env: Union["gym.Env", gymnasium.Env]) -> gymnasium.Env: # pragma: no cover
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"""
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Adapted from https://github.com/thu-ml/tianshou.
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Takes an environment and patches it to return Gymnasium env.
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This function takes the environment object and returns a patched
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env, using shimmy wrapper to convert it to Gymnasium,
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if necessary.
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:param env: A gym/gymnasium env
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:return: Patched env (gymnasium env)
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"""
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# Gymnasium env, no patching to be done
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if isinstance(env, gymnasium.Env):
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return env
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if not gym_installed or not isinstance(env, gym.Env):
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raise ValueError(
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f"The environment is of type {type(env)}, not a Gymnasium "
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f"environment. In this case, we expect OpenAI Gym to be "
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f"installed and the environment to be an OpenAI Gym environment."
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)
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try:
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import shimmy
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except ImportError as e:
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raise ImportError(
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"Missing shimmy installation. You provided an OpenAI Gym environment. "
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"Stable-Baselines3 (SB3) has transitioned to using Gymnasium internally. "
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"In order to use OpenAI Gym environments with SB3, you need to "
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"install shimmy (`pip install 'shimmy>=2.0'`)."
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) from e
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warnings.warn(
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"You provided an OpenAI Gym environment. "
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"We strongly recommend transitioning to Gymnasium environments. "
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"Stable-Baselines3 is automatically wrapping your environments in a compatibility "
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"layer, which could potentially cause issues."
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)
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if "seed" in signature(env.unwrapped.reset).parameters:
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# Gym 0.26+ env
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return shimmy.GymV26CompatibilityV0(env=env)
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# Gym 0.21 env
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return shimmy.GymV21CompatibilityV0(env=env)
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def _convert_space(space: Union["gym.Space", gymnasium.Space]) -> gymnasium.Space: # pragma: no cover
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"""
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Takes a space and patches it to return Gymnasium Space.
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This function takes the space object and returns a patched
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space, using shimmy wrapper to convert it to Gymnasium,
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if necessary.
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:param env: A gym/gymnasium Space
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:return: Patched space (gymnasium Space)
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"""
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# Gymnasium space, no conversion to be done
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if isinstance(space, gymnasium.Space):
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return space
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if not gym_installed or not isinstance(space, gym.Space):
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raise ValueError(
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f"The space is of type {type(space)}, not a Gymnasium "
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f"space. In this case, we expect OpenAI Gym to be "
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f"installed and the space to be an OpenAI Gym space."
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)
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try:
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import shimmy
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except ImportError as e:
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raise ImportError(
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"Missing shimmy installation. You provided an OpenAI Gym space. "
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"Stable-Baselines3 (SB3) has transitioned to using Gymnasium internally. "
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"In order to use OpenAI Gym space with SB3, you need to "
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"install shimmy (`pip install 'shimmy>=0.2.1'`)."
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) from e
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warnings.warn(
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"You loaded a model that was trained using OpenAI Gym. "
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"We strongly recommend transitioning to Gymnasium by saving that model again."
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)
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return shimmy.openai_gym_compatibility._convert_space(space)
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