Make SubprocVecEnv works with DummyVecEnv (#908)

* Make SubprocVecEnv works with DummyVecEnv (nested environments for synchronous sampling)

* SubprocVecEnv now supports running environments in series in each process

* Added docstring to the test definition

* Added additional test to check, whether SubprocVecEnv results with the same output when in_series parameter is enabled and not

* Added more test cases for in_series parameter

* Refactored worker function, added docstring for in_series parameter

* Remove check for TF presence in setup.py
This commit is contained in:
Tomasz Wrona
2019-08-29 21:16:25 +02:00
committed by pzhokhov
parent 0182fe1877
commit d80b075904
2 changed files with 80 additions and 15 deletions

View File

@@ -4,33 +4,36 @@ import numpy as np
from .vec_env import VecEnv, CloudpickleWrapper, clear_mpi_env_vars
def worker(remote, parent_remote, env_fn_wrapper):
def worker(remote, parent_remote, env_fn_wrappers):
def step_env(env, action):
ob, reward, done, info = env.step(action)
if done:
ob = env.reset()
return ob, reward, done, info
parent_remote.close()
env = env_fn_wrapper.x()
envs = [env_fn_wrapper() for env_fn_wrapper in env_fn_wrappers.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))
remote.send([step_env(env, action) for env, action in zip(envs, data)])
elif cmd == 'reset':
ob = env.reset()
remote.send(ob)
remote.send([env.reset() for env in envs])
elif cmd == 'render':
remote.send(env.render(mode='rgb_array'))
remote.send([env.render(mode='rgb_array') for env in envs])
elif cmd == 'close':
remote.close()
break
elif cmd == 'get_spaces_spec':
remote.send((env.observation_space, env.action_space, env.spec))
remote.send((envs[0].observation_space, envs[0].action_space, envs[0].spec))
else:
raise NotImplementedError
except KeyboardInterrupt:
print('SubprocVecEnv worker: got KeyboardInterrupt')
finally:
env.close()
for env in envs:
env.close()
class SubprocVecEnv(VecEnv):
@@ -38,17 +41,23 @@ 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'):
def __init__(self, env_fns, spaces=None, context='spawn', in_series=1):
"""
Arguments:
env_fns: iterable of callables - functions that create environments to run in subprocesses. Need to be cloud-pickleable
in_series: number of environments to run in series in a single process
(e.g. when len(env_fns) == 12 and in_series == 3, it will run 4 processes, each running 3 envs in series)
"""
self.waiting = False
self.closed = False
self.in_series = in_series
nenvs = len(env_fns)
assert nenvs % in_series == 0, "Number of envs must be divisible by number of envs to run in series"
self.nremotes = nenvs // in_series
env_fns = np.array_split(env_fns, self.nremotes)
ctx = mp.get_context(context)
self.remotes, self.work_remotes = zip(*[ctx.Pipe() for _ in range(nenvs)])
self.remotes, self.work_remotes = zip(*[ctx.Pipe() for _ in range(self.nremotes)])
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:
@@ -61,10 +70,11 @@ class SubprocVecEnv(VecEnv):
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)
VecEnv.__init__(self, nenvs, observation_space, action_space)
def step_async(self, actions):
self._assert_not_closed()
actions = np.array_split(actions, self.nremotes)
for remote, action in zip(self.remotes, actions):
remote.send(('step', action))
self.waiting = True
@@ -72,6 +82,7 @@ class SubprocVecEnv(VecEnv):
def step_wait(self):
self._assert_not_closed()
results = [remote.recv() for remote in self.remotes]
results = _flatten_list(results)
self.waiting = False
obs, rews, dones, infos = zip(*results)
return _flatten_obs(obs), np.stack(rews), np.stack(dones), infos
@@ -80,7 +91,9 @@ class SubprocVecEnv(VecEnv):
self._assert_not_closed()
for remote in self.remotes:
remote.send(('reset', None))
return _flatten_obs([remote.recv() for remote in self.remotes])
obs = [remote.recv() for remote in self.remotes]
obs = _flatten_list(obs)
return _flatten_obs(obs)
def close_extras(self):
self.closed = True
@@ -97,6 +110,7 @@ class SubprocVecEnv(VecEnv):
for pipe in self.remotes:
pipe.send(('render', None))
imgs = [pipe.recv() for pipe in self.remotes]
imgs = _flatten_list(imgs)
return imgs
def _assert_not_closed(self):
@@ -115,3 +129,10 @@ def _flatten_obs(obs):
return {k: np.stack([o[k] for o in obs]) for k in keys}
else:
return np.stack(obs)
def _flatten_list(l):
assert isinstance(l, (list, tuple))
assert len(l) > 0
assert all([len(l_) > 0 for l_ in l])
return [l__ for l_ in l for l__ in l_]

View File

@@ -67,6 +67,50 @@ def test_vec_env(klass, dtype): # pylint: disable=R0914
assert_venvs_equal(env1, env2, num_steps=num_steps)
@pytest.mark.parametrize('dtype', ('uint8', 'float32'))
@pytest.mark.parametrize('num_envs_in_series', (3, 4, 6))
def test_sync_sampling(dtype, num_envs_in_series):
"""
Test that a SubprocVecEnv running with envs in series
outputs the same as DummyVecEnv.
"""
num_envs = 12
num_steps = 100
shape = (3, 8)
def make_fn(seed):
"""
Get an environment constructor with a seed.
"""
return lambda: SimpleEnv(seed, shape, dtype)
fns = [make_fn(i) for i in range(num_envs)]
env1 = DummyVecEnv(fns)
env2 = SubprocVecEnv(fns, in_series=num_envs_in_series)
assert_venvs_equal(env1, env2, num_steps=num_steps)
@pytest.mark.parametrize('dtype', ('uint8', 'float32'))
@pytest.mark.parametrize('num_envs_in_series', (3, 4, 6))
def test_sync_sampling_sanity(dtype, num_envs_in_series):
"""
Test that a SubprocVecEnv running with envs in series
outputs the same as SubprocVecEnv without running in series.
"""
num_envs = 12
num_steps = 100
shape = (3, 8)
def make_fn(seed):
"""
Get an environment constructor with a seed.
"""
return lambda: SimpleEnv(seed, shape, dtype)
fns = [make_fn(i) for i in range(num_envs)]
env1 = SubprocVecEnv(fns)
env2 = SubprocVecEnv(fns, in_series=num_envs_in_series)
assert_venvs_equal(env1, env2, num_steps=num_steps)
class SimpleEnv(gym.Env):
"""
An environment with a pre-determined observation space