def __init__(self,
env_constructors,
start_serially=True,
blocking=False,
flatten=True):
"""
Args:
env_constructors (list[Callable]): a list of callable environment creators.
start_serially (bool): whether to start environments serially or in parallel.
blocking (bool): whether to step environments one after another.
flatten (bool): whether to use flatten action and time_steps during
communication to reduce overhead.
Raises:
ValueError: If the action or observation specs don't match.
"""
super(ParallelAlfEnvironment, self).__init__()
self._envs = []
self._env_ids = []
for env_id, ctor in enumerate(env_constructors):
env = ProcessEnvironment(ctor, env_id=env_id, flatten=flatten)
self._envs.append(env)
self._env_ids.append(env_id)
self._num_envs = len(env_constructors)
self._blocking = blocking
self._start_serially = start_serially
self.start()
self._action_spec = self._envs[0].action_spec()
self._observation_spec = self._envs[0].observation_spec()
self._reward_spec = self._envs[0].reward_spec()
self._time_step_spec = self._envs[0].time_step_spec()
self._env_info_spec = self._envs[0].env_info_spec()
self._num_tasks = self._envs[0].num_tasks
self._task_names = self._envs[0].task_names
self._time_step_with_env_info_spec = self._time_step_spec._replace(
env_info=self._env_info_spec)
self._parallel_execution = True
if any(env.action_spec() != self._action_spec for env in self._envs):
raise ValueError(
'All environments must have the same action spec.')
if any(env.time_step_spec() != self._time_step_spec
for env in self._envs):
raise ValueError(
'All environments must have the same time_step_spec.')
self._flatten = flatten
def test_close_no_hang_after_init(self):
constructor = functools.partial(
RandomAlfEnvironment,
ts.TensorSpec((3, 3), torch.float32),
ts.BoundedTensorSpec([1], torch.float32, minimum=-1.0,
maximum=1.0),
episode_end_probability=0,
min_duration=2,
max_duration=2)
env = ProcessEnvironment(constructor)
env.start()
env.close()
def test_reraise_exception_in_step(self):
crash_at_step = 3
constructor = functools.partial(MockEnvironmentCrashInStep,
crash_at_step)
env = ProcessEnvironment(constructor)
env.start()
env.reset()
action_spec = env.action_spec()
env.step(action_spec.sample())
env.step(action_spec.sample())
with self.assertRaises(Exception):
env.step(action_spec.sample())
def test_reraise_exception_in_reset(self):
constructor = MockEnvironmentCrashInReset
env = ProcessEnvironment(constructor)
env.start()
with self.assertRaises(Exception):
env.reset()