600f4bbd55
Preparation for #914 and #920 Changes formatting to ruff and black. Remove python 3.8 ## Additional Changes - Removed flake8 dependencies - Adjusted pre-commit. Now CI and Make use pre-commit, reducing the duplication of linting calls - Removed check-docstyle option (ruff is doing that) - Merged format and lint. In CI the format-lint step fails if any changes are done, so it fulfills the lint functionality. --------- Co-authored-by: Jiayi Weng <jiayi@openai.com>
73 lines
2.3 KiB
Python
73 lines
2.3 KiB
Python
import contextlib
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from typing import Any, Callable, Optional
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import gymnasium as gym
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import numpy as np
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from tianshou.env.utils import gym_new_venv_step_type
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from tianshou.env.worker import EnvWorker
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with contextlib.suppress(ImportError):
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import ray
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class _SetAttrWrapper(gym.Wrapper):
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def set_env_attr(self, key: str, value: Any) -> None:
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setattr(self.env.unwrapped, key, value)
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def get_env_attr(self, key: str) -> Any:
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return getattr(self.env, key)
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class RayEnvWorker(EnvWorker):
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"""Ray worker used in RayVectorEnv."""
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def __init__(self, env_fn: Callable[[], gym.Env]) -> None:
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self.env = ray.remote(_SetAttrWrapper).options(num_cpus=0).remote(env_fn()) # type: ignore
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super().__init__(env_fn)
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def get_env_attr(self, key: str) -> Any:
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return ray.get(self.env.get_env_attr.remote(key))
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def set_env_attr(self, key: str, value: Any) -> None:
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ray.get(self.env.set_env_attr.remote(key, value))
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def reset(self, **kwargs: Any) -> Any:
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if "seed" in kwargs:
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super().seed(kwargs["seed"])
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return ray.get(self.env.reset.remote(**kwargs))
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@staticmethod
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def wait( # type: ignore
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workers: list["RayEnvWorker"],
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wait_num: int,
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timeout: Optional[float] = None,
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) -> list["RayEnvWorker"]:
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results = [x.result for x in workers]
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ready_results, _ = ray.wait(results, num_returns=wait_num, timeout=timeout)
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return [workers[results.index(result)] for result in ready_results]
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def send(self, action: Optional[np.ndarray], **kwargs: Any) -> None:
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# self.result is actually a handle
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if action is None:
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self.result = self.env.reset.remote(**kwargs)
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else:
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self.result = self.env.step.remote(action)
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def recv(self) -> gym_new_venv_step_type:
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return ray.get(self.result) # type: ignore
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def seed(self, seed: Optional[int] = None) -> Optional[list[int]]:
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super().seed(seed)
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try:
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return ray.get(self.env.seed.remote(seed))
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except (AttributeError, NotImplementedError):
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self.env.reset.remote(seed=seed)
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return None
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def render(self, **kwargs: Any) -> Any:
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return ray.get(self.env.render.remote(**kwargs))
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def close_env(self) -> None:
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ray.get(self.env.close.remote())
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