def test_step_takes_steps_for_all_non_waiting_envs(self):
SubprocessEnvManager.create_worker = lambda em, worker_id, step_queue, env_factory, engine_c: MockEnvWorker(
worker_id, EnvironmentResponse("step", worker_id, worker_id))
manager = SubprocessEnvManager(mock_env_factory,
EngineConfig.default_config(), 3)
manager.step_queue = Mock()
manager.step_queue.get_nowait.side_effect = [
EnvironmentResponse("step", 0, StepResponse(0, None)),
EnvironmentResponse("step", 1, StepResponse(1, None)),
EmptyQueue(),
]
step_mock = Mock()
last_steps = [Mock(), Mock(), Mock()]
manager.env_workers[0].previous_step = last_steps[0]
manager.env_workers[1].previous_step = last_steps[1]
manager.env_workers[2].previous_step = last_steps[2]
manager.env_workers[2].waiting = True
manager._take_step = Mock(return_value=step_mock)
res = manager.step()
for i, env in enumerate(manager.env_workers):
if i < 2:
env.send.assert_called_with("step", step_mock)
manager.step_queue.get_nowait.assert_called()
# Check that the "last steps" are set to the value returned for each step
self.assertEqual(
manager.env_workers[i].previous_step.
current_all_brain_info, i)
assert res == [
manager.env_workers[0].previous_step,
manager.env_workers[1].previous_step,
]
def test_step_takes_steps_for_all_non_waiting_envs(self,
mock_create_worker):
mock_create_worker.side_effect = create_worker_mock
manager = SubprocessEnvManager(mock_env_factory,
EngineConfig.default_config(), 3)
manager.step_queue = Mock()
manager.step_queue.get_nowait.side_effect = [
EnvironmentResponse(EnvironmentCommand.STEP, 0,
StepResponse(0, None, {})),
EnvironmentResponse(EnvironmentCommand.STEP, 1,
StepResponse(1, None, {})),
EmptyQueue(),
]
step_mock = Mock()
last_steps = [Mock(), Mock(), Mock()]
manager.env_workers[0].previous_step = last_steps[0]
manager.env_workers[1].previous_step = last_steps[1]
manager.env_workers[2].previous_step = last_steps[2]
manager.env_workers[2].waiting = True
manager._take_step = Mock(return_value=step_mock)
res = manager._step()
for i, env in enumerate(manager.env_workers):
if i < 2:
env.send.assert_called_with(EnvironmentCommand.STEP, step_mock)
manager.step_queue.get_nowait.assert_called()
# Check that the "last steps" are set to the value returned for each step
self.assertEqual(
manager.env_workers[i].previous_step.
current_all_step_result, i)
assert res == [
manager.env_workers[0].previous_step,
manager.env_workers[1].previous_step,
]
def test_crashed_env_restarts(self, mock_create_worker):
crashing_worker = MockEnvWorker(
0, EnvironmentResponse(EnvironmentCommand.RESET, 0, 0)
)
restarting_worker = MockEnvWorker(
0, EnvironmentResponse(EnvironmentCommand.RESET, 0, 0)
)
healthy_worker = MockEnvWorker(
1, EnvironmentResponse(EnvironmentCommand.RESET, 1, 1)
)
mock_create_worker.side_effect = [
crashing_worker,
healthy_worker,
restarting_worker,
]
manager = SubprocessEnvManager(mock_env_factory, RunOptions(), 2)
manager.step_queue = Mock()
manager.step_queue.get_nowait.side_effect = [
EnvironmentResponse(
EnvironmentCommand.ENV_EXITED,
0,
UnityCommunicationException("Test msg"),
),
EnvironmentResponse(EnvironmentCommand.CLOSED, 0, None),
EnvironmentResponse(EnvironmentCommand.STEP, 1, StepResponse(0, None, {})),
EmptyQueue(),
EnvironmentResponse(EnvironmentCommand.STEP, 0, StepResponse(1, None, {})),
EnvironmentResponse(EnvironmentCommand.STEP, 1, StepResponse(2, None, {})),
EmptyQueue(),
]
step_mock = Mock()
last_steps = [Mock(), Mock(), Mock()]
assert crashing_worker is manager.env_workers[0]
assert healthy_worker is manager.env_workers[1]
crashing_worker.previous_step = last_steps[0]
crashing_worker.waiting = True
healthy_worker.previous_step = last_steps[1]
healthy_worker.waiting = True
manager._take_step = Mock(return_value=step_mock)
manager._step()
healthy_worker.send.assert_has_calls(
[
call(EnvironmentCommand.ENVIRONMENT_PARAMETERS, ANY),
call(EnvironmentCommand.RESET, ANY),
call(EnvironmentCommand.STEP, ANY),
]
)
restarting_worker.send.assert_has_calls(
[
call(EnvironmentCommand.ENVIRONMENT_PARAMETERS, ANY),
call(EnvironmentCommand.RESET, ANY),
call(EnvironmentCommand.STEP, ANY),
]
)
def worker_aai(
parent_conn: Connection,
step_queue: Queue,
pickled_env_factory: str,
worker_id: int,
engine_configuration: EngineConfig,
) -> None:
env_factory: Callable[
[int, List[SideChannel]], AnimalAIEnvironment
] = cloudpickle.loads(pickled_env_factory)
shared_float_properties = FloatPropertiesChannel()
engine_configuration_channel = EngineConfigurationChannel()
engine_configuration_channel.set_configuration(engine_configuration)
env: AnimalAIEnvironment = env_factory(
worker_id, [shared_float_properties, engine_configuration_channel]
)
def _send_response(cmd_name, payload):
parent_conn.send(EnvironmentResponse(cmd_name, worker_id, payload))
def _generate_all_results() -> AllStepResult:
all_step_result: AllStepResult = {}
for brain_name in env.get_agent_groups():
all_step_result[brain_name] = env.get_step_result(brain_name)
return all_step_result
def external_brains():
result = {}
for brain_name in env.get_agent_groups():
result[brain_name] = group_spec_to_brain_parameters(
brain_name, env.get_agent_group_spec(brain_name)
)
return result
try:
while True:
cmd: EnvironmentCommand = parent_conn.recv()
if cmd.name == "step":
all_action_info = cmd.payload
for brain_name, action_info in all_action_info.items():
if len(action_info.action) != 0:
env.set_actions(brain_name, action_info.action)
env.step()
all_step_result = _generate_all_results()
# The timers in this process are independent from all the processes and the "main" process
# So after we send back the root timer, we can safely clear them.
# Note that we could randomly return timers a fraction of the time if we wanted to reduce
# the data transferred.
# TODO get gauges from the workers and merge them in the main process too.
step_response = StepResponse(all_step_result, get_timer_root())
step_queue.put(EnvironmentResponse("step", worker_id, step_response))
reset_timers()
elif cmd.name == "external_brains":
_send_response("external_brains", external_brains())
elif cmd.name == "get_properties":
reset_params = shared_float_properties.get_property_dict_copy()
_send_response("get_properties", reset_params)
elif cmd.name == "reset":
env.reset(arenas_configurations=cmd.payload)
all_step_result = _generate_all_results()
_send_response("reset", all_step_result)
elif cmd.name == "close":
break
except (KeyboardInterrupt, UnityCommunicationException, UnityTimeOutException):
logger.info(f"UnityEnvironment worker {worker_id}: environment stopping.")
step_queue.put(EnvironmentResponse("env_close", worker_id, None))
finally:
# If this worker has put an item in the step queue that hasn't been processed by the EnvManager, the process
# will hang until the item is processed. We avoid this behavior by using Queue.cancel_join_thread()
# See https://docs.python.org/3/library/multiprocessing.html#multiprocessing.Queue.cancel_join_thread for
# more info.
logger.debug(f"UnityEnvironment worker {worker_id} closing.")
step_queue.cancel_join_thread()
step_queue.close()
env.close()
logger.debug(f"UnityEnvironment worker {worker_id} done.")