import gym import time import ctypes import numpy as np from collections import OrderedDict from multiprocessing.context import Process from multiprocessing import Array, Pipe, connection from typing import Any, List, Tuple, Union, Callable, Optional from tianshou.env.worker import EnvWorker from tianshou.env.utils import CloudpickleWrapper _NP_TO_CT = { np.bool: ctypes.c_bool, np.bool_: ctypes.c_bool, np.uint8: ctypes.c_uint8, np.uint16: ctypes.c_uint16, np.uint32: ctypes.c_uint32, np.uint64: ctypes.c_uint64, np.int8: ctypes.c_int8, np.int16: ctypes.c_int16, np.int32: ctypes.c_int32, np.int64: ctypes.c_int64, np.float32: ctypes.c_float, np.float64: ctypes.c_double, } class ShArray: """Wrapper of multiprocessing Array.""" def __init__(self, dtype: np.generic, shape: Tuple[int]) -> None: self.arr = Array( _NP_TO_CT[dtype.type], # type: ignore int(np.prod(shape)), ) self.dtype = dtype self.shape = shape def save(self, ndarray: np.ndarray) -> None: assert isinstance(ndarray, np.ndarray) dst = self.arr.get_obj() dst_np = np.frombuffer(dst, dtype=self.dtype).reshape(self.shape) np.copyto(dst_np, ndarray) def get(self) -> np.ndarray: obj = self.arr.get_obj() return np.frombuffer(obj, dtype=self.dtype).reshape(self.shape) def _setup_buf(space: gym.Space) -> Union[dict, tuple, ShArray]: if isinstance(space, gym.spaces.Dict): assert isinstance(space.spaces, OrderedDict) return {k: _setup_buf(v) for k, v in space.spaces.items()} elif isinstance(space, gym.spaces.Tuple): assert isinstance(space.spaces, tuple) return tuple([_setup_buf(t) for t in space.spaces]) else: return ShArray(space.dtype, space.shape) def _worker( parent: connection.Connection, p: connection.Connection, env_fn_wrapper: CloudpickleWrapper, obs_bufs: Optional[Union[dict, tuple, ShArray]] = None, ) -> None: def _encode_obs( obs: Union[dict, tuple, np.ndarray], buffer: Union[dict, tuple, ShArray], ) -> None: if isinstance(obs, np.ndarray) and isinstance(buffer, ShArray): buffer.save(obs) elif isinstance(obs, tuple) and isinstance(buffer, tuple): for o, b in zip(obs, buffer): _encode_obs(o, b) elif isinstance(obs, dict) and isinstance(buffer, dict): for k in obs.keys(): _encode_obs(obs[k], buffer[k]) return None parent.close() env = env_fn_wrapper.data() try: while True: try: cmd, data = p.recv() except EOFError: # the pipe has been closed p.close() break if cmd == "step": obs, reward, done, info = env.step(data) if obs_bufs is not None: _encode_obs(obs, obs_bufs) obs = None p.send((obs, reward, done, info)) elif cmd == "reset": obs = env.reset() if obs_bufs is not None: _encode_obs(obs, obs_bufs) obs = None p.send(obs) elif cmd == "close": p.send(env.close()) p.close() break elif cmd == "render": p.send(env.render(**data) if hasattr(env, "render") else None) elif cmd == "seed": p.send(env.seed(data) if hasattr(env, "seed") else None) elif cmd == "getattr": p.send(getattr(env, data) if hasattr(env, data) else None) else: p.close() raise NotImplementedError except KeyboardInterrupt: p.close() class SubprocEnvWorker(EnvWorker): """Subprocess worker used in SubprocVectorEnv and ShmemVectorEnv.""" def __init__( self, env_fn: Callable[[], gym.Env], share_memory: bool = False ) -> None: super().__init__(env_fn) self.parent_remote, self.child_remote = Pipe() self.share_memory = share_memory self.buffer: Optional[Union[dict, tuple, ShArray]] = None if self.share_memory: dummy = env_fn() obs_space = dummy.observation_space dummy.close() del dummy self.buffer = _setup_buf(obs_space) args = ( self.parent_remote, self.child_remote, CloudpickleWrapper(env_fn), self.buffer, ) self.process = Process(target=_worker, args=args, daemon=True) self.process.start() self.child_remote.close() def __getattr__(self, key: str) -> Any: self.parent_remote.send(["getattr", key]) return self.parent_remote.recv() def _decode_obs(self) -> Union[dict, tuple, np.ndarray]: def decode_obs( buffer: Optional[Union[dict, tuple, ShArray]] ) -> Union[dict, tuple, np.ndarray]: if isinstance(buffer, ShArray): return buffer.get() elif isinstance(buffer, tuple): return tuple([decode_obs(b) for b in buffer]) elif isinstance(buffer, dict): return {k: decode_obs(v) for k, v in buffer.items()} else: raise NotImplementedError return decode_obs(self.buffer) def reset(self) -> Any: self.parent_remote.send(["reset", None]) obs = self.parent_remote.recv() if self.share_memory: obs = self._decode_obs() return obs @staticmethod def wait( # type: ignore workers: List["SubprocEnvWorker"], wait_num: int, timeout: Optional[float] = None, ) -> List["SubprocEnvWorker"]: remain_conns = conns = [x.parent_remote for x in workers] ready_conns: List[connection.Connection] = [] remain_time, t1 = timeout, time.time() while len(remain_conns) > 0 and len(ready_conns) < wait_num: if timeout: remain_time = timeout - (time.time() - t1) if remain_time <= 0: break # connection.wait hangs if the list is empty new_ready_conns = connection.wait( remain_conns, timeout=remain_time) ready_conns.extend(new_ready_conns) # type: ignore remain_conns = [ conn for conn in remain_conns if conn not in ready_conns] return [workers[conns.index(con)] for con in ready_conns] def send_action(self, action: np.ndarray) -> None: self.parent_remote.send(["step", action]) def get_result( self, ) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: obs, rew, done, info = self.parent_remote.recv() if self.share_memory: obs = self._decode_obs() return obs, rew, done, info def seed(self, seed: Optional[int] = None) -> Optional[List[int]]: self.parent_remote.send(["seed", seed]) return self.parent_remote.recv() def render(self, **kwargs: Any) -> Any: self.parent_remote.send(["render", kwargs]) return self.parent_remote.recv() def close_env(self) -> None: try: self.parent_remote.send(["close", None]) # mp may be deleted so it may raise AttributeError self.parent_remote.recv() self.process.join() except (BrokenPipeError, EOFError, AttributeError): pass # ensure the subproc is terminated self.process.terminate()