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subproc_vec_env.py
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subproc_vec_env.py
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import multiprocessing as mp
import numpy as np
from .vec_env import VecEnv, CloudpickleWrapper, clear_mpi_env_vars
def worker(remote, parent_remote, env_fn_wrapper):
parent_remote.close()
env = env_fn_wrapper.x()
try:
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 == 'render':
remote.send(env.render(mode='rgb_array'))
elif cmd == 'close':
remote.close()
break
elif cmd == 'get_spaces_spec':
remote.send((env.observation_space, env.action_space, env.spec))
else:
raise NotImplementedError
except KeyboardInterrupt:
print('SubprocVecEnv worker: got KeyboardInterrupt')
finally:
env.close()
class SubprocVecEnv(VecEnv):
"""
VecEnv that runs multiple environments in parallel in subproceses and communicates with them via pipes.
Recommended to use when num_envs > 1 and step() can be a bottleneck.
"""
def __init__(self, env_fns, spaces=None, context='spawn'):
"""
Arguments:
env_fns: iterable of callables - functions that create environments to run in subprocesses. Need to be cloud-pickleable
"""
self.waiting = False
self.closed = False
nenvs = len(env_fns)
ctx = mp.get_context(context)
self.remotes, self.work_remotes = zip(*[ctx.Pipe() for _ in range(nenvs)])
self.ps = [ctx.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
with clear_mpi_env_vars():
p.start()
for remote in self.work_remotes:
remote.close()
self.remotes[0].send(('get_spaces_spec', None))
observation_space, action_space, self.spec = self.remotes[0].recv()
self.viewer = None
VecEnv.__init__(self, len(env_fns), observation_space, action_space)
def step_async(self, actions):
self._assert_not_closed()
for remote, action in zip(self.remotes, actions):
remote.send(('step', action))
self.waiting = True
def step_wait(self):
self._assert_not_closed()
results = [remote.recv() for remote in self.remotes]
self.waiting = False
obs, rews, dones, infos = zip(*results)
return _flatten_obs(obs), np.stack(rews), np.stack(dones), infos
def reset(self):
self._assert_not_closed()
for remote in self.remotes:
remote.send(('reset', None))
return _flatten_obs([remote.recv() for remote in self.remotes])
def close_extras(self):
self.closed = True
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()
def get_images(self):
self._assert_not_closed()
for pipe in self.remotes:
pipe.send(('render', None))
imgs = [pipe.recv() for pipe in self.remotes]
return imgs
def _assert_not_closed(self):
assert not self.closed, "Trying to operate on a SubprocVecEnv after calling close()"
def __del__(self):
if not self.closed:
self.close()
def _flatten_obs(obs):
assert isinstance(obs, (list, tuple))
assert len(obs) > 0
if isinstance(obs[0], dict):
keys = obs[0].keys()
return {k: np.stack([o[k] for o in obs]) for k in keys}
else:
return np.stack(obs)