42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
|
import gym
|
||
|
|
import numpy as np
|
||
|
|
from typing import List, Callable, Optional, Any
|
||
|
|
|
||
|
|
from tianshou.env.worker import EnvWorker
|
||
|
|
|
||
|
|
|
||
|
|
class DummyEnvWorker(EnvWorker):
|
||
|
|
"""Dummy worker used in sequential vector environments."""
|
||
|
|
|
||
|
|
def __init__(self, env_fn: Callable[[], gym.Env]) -> None:
|
||
|
|
super().__init__(env_fn)
|
||
|
|
self.env = env_fn()
|
||
|
|
|
||
|
|
def __getattr__(self, key: str):
|
||
|
|
if hasattr(self.env, key):
|
||
|
|
return getattr(self.env, key)
|
||
|
|
return None
|
||
|
|
|
||
|
|
def reset(self) -> Any:
|
||
|
|
return self.env.reset()
|
||
|
|
|
||
|
|
@staticmethod
|
||
|
|
def wait(workers: List['DummyEnvWorker'],
|
||
|
|
wait_num: int,
|
||
|
|
timeout: Optional[float] = None) -> List['DummyEnvWorker']:
|
||
|
|
# SequentialEnvWorker objects are always ready
|
||
|
|
return workers
|
||
|
|
|
||
|
|
def send_action(self, action: np.ndarray) -> None:
|
||
|
|
self.result = self.env.step(action)
|
||
|
|
|
||
|
|
def seed(self, seed: Optional[int] = None) -> List[int]:
|
||
|
|
return self.env.seed(seed) if hasattr(self.env, 'seed') else None
|
||
|
|
|
||
|
|
def render(self, **kwargs) -> Any:
|
||
|
|
return self.env.render(**kwargs) \
|
||
|
|
if hasattr(self.env, 'render') else None
|
||
|
|
|
||
|
|
def close_env(self) -> None:
|
||
|
|
self.env.close()
|