Source code for tianshou.env.worker.dummy

from typing import Any, Callable, List, Optional

import gym
import numpy as np

from tianshou.env.worker import EnvWorker


[docs]class DummyEnvWorker(EnvWorker): """Dummy worker used in sequential vector environments.""" def __init__(self, env_fn: Callable[[], gym.Env]) -> None: self.env = env_fn() super().__init__(env_fn) def __getattr__(self, key: str) -> Any: return getattr(self.env, key)
[docs] def reset(self) -> Any: return self.env.reset()
[docs] @staticmethod def wait( # type: ignore workers: List["DummyEnvWorker"], wait_num: int, timeout: Optional[float] = None ) -> List["DummyEnvWorker"]: # Sequential EnvWorker objects are always ready return workers
[docs] def send_action(self, action: np.ndarray) -> None: self.result = self.env.step(action)
[docs] def seed(self, seed: Optional[int] = None) -> List[int]: super().seed(seed) return self.env.seed(seed)
[docs] def render(self, **kwargs: Any) -> Any: return self.env.render(**kwargs)
[docs] def close_env(self) -> None: self.env.close()