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- import numpy as np
- from multiprocessing import Process, Pipe
- from vec_env import VecEnv, CloudpickleWrapper
- def worker(remote, parent_remote, env_fn_wrapper):
- parent_remote.close()
- env = env_fn_wrapper.x()
- while True:
- cmd, data = remote.recv()
- if cmd == 'step':
- ob, reward, done, info = env.step(data)
- if done:
- ob = env.reset()
- remote.send((ob, reward, done, info))
- elif cmd == 'reset':
- ob = env.reset()
- remote.send(ob)
- elif cmd == 'reset_task':
- ob = env.reset_task()
- remote.send(ob)
- elif cmd == 'close':
- remote.close()
- break
- elif cmd == 'get_spaces':
- remote.send((env.observation_space, env.action_space))
- else:
- raise NotImplementedError
- class SubprocVecEnv(VecEnv):
- def __init__(self, env_fns, spaces=None):
- """
- envs: list of gym environments to run in subprocesses
- """
- self.waiting = False
- self.closed = False
- nenvs = len(env_fns)
- self.remotes, self.work_remotes = zip(*[Pipe() for _ in range(nenvs)])
- self.ps = [Process(target=worker, args=(work_remote, remote, CloudpickleWrapper(env_fn)))
- for (work_remote, remote, env_fn) in zip(self.work_remotes, self.remotes, env_fns)]
- for p in self.ps:
- p.daemon = True # if the main process crashes, we should not cause things to hang
- p.start()
- for remote in self.work_remotes:
- remote.close()
- self.remotes[0].send(('get_spaces', None))
- observation_space, action_space = self.remotes[0].recv()
- VecEnv.__init__(self, len(env_fns), observation_space, action_space)
- def step_async(self, actions):
- for remote, action in zip(self.remotes, actions):
- remote.send(('step', action))
- self.waiting = True
- def step_wait(self):
- results = [remote.recv() for remote in self.remotes]
- self.waiting = False
- obs, rews, dones, infos = zip(*results)
- return np.stack(obs), np.stack(rews), np.stack(dones), infos
- def reset(self):
- for remote in self.remotes:
- remote.send(('reset', None))
- return np.stack([remote.recv() for remote in self.remotes])
- def reset_task(self):
- for remote in self.remotes:
- remote.send(('reset_task', None))
- return np.stack([remote.recv() for remote in self.remotes])
- def close(self):
- if self.closed:
- return
- if self.waiting:
- for remote in self.remotes:
- remote.recv()
- for remote in self.remotes:
- remote.send(('close', None))
- for p in self.ps:
- p.join()
- self.closed = True
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