a9f9940d17
- Refacor code to remove duplicate code - Enable async simulation for all vector envs - Remove `collector.close` and rename `VectorEnv` to `DummyVectorEnv` The abstraction of vector env changed. Prior to this pr, each vector env is almost independent. After this pr, each env is wrapped into a worker, and vector envs differ with their worker type. In fact, users can just use `BaseVectorEnv` with different workers, I keep `SubprocVectorEnv`, `ShmemVectorEnv` for backward compatibility. Co-authored-by: n+e <463003665@qq.com> Co-authored-by: magicly <magicly007@gmail.com>
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
import gym
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import numpy as np
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from typing import List, Callable, Optional, Any
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from tianshou.env.worker import EnvWorker
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class DummyEnvWorker(EnvWorker):
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"""Dummy worker used in sequential vector environments."""
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def __init__(self, env_fn: Callable[[], gym.Env]) -> None:
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super().__init__(env_fn)
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self.env = env_fn()
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def __getattr__(self, key: str):
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if hasattr(self.env, key):
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return getattr(self.env, key)
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return None
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def reset(self) -> Any:
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return self.env.reset()
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@staticmethod
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def wait(workers: List['DummyEnvWorker'],
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wait_num: int,
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timeout: Optional[float] = None) -> List['DummyEnvWorker']:
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# SequentialEnvWorker objects are always ready
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return workers
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def send_action(self, action: np.ndarray) -> None:
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self.result = self.env.step(action)
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def seed(self, seed: Optional[int] = None) -> List[int]:
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return self.env.seed(seed) if hasattr(self.env, 'seed') else None
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def render(self, **kwargs) -> Any:
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return self.env.render(**kwargs) \
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if hasattr(self.env, 'render') else None
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def close_env(self) -> None:
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self.env.close()
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