def smarts(agent_spec):
smarts = SMARTS(
agent_interfaces={AGENT_ID: agent_spec.interface},
traffic_sim=SumoTrafficSimulation(),
)
yield smarts
smarts.destroy()
def __init__(self, config):
self._config = config
# XXX: These are intentionally left public at PyMARL's request
self.n_agents = config.get("n_agents", 1)
self.episode_limit = config.get("episode_limit", 1000)
self.observation_space = config.get("observation_space",
DEFAULT_OBSERVATION_SPACE)
self.action_space = config.get("action_space", DEFAULT_ACTION_SPACE)
self.state_space = config.get("state_space", DEFAULT_STATE_SPACE)
self._agent_ids = ["Agent %i" % i for i in range(self.n_agents)]
self._reward_adapter = config.get("reward_adapter",
default_reward_adapter)
self._observation_adapter = config.get("observation_adapter",
default_obs_adapter)
self._action_adapter = config.get("action_adapter",
default_action_adapter)
self._done_adapter = config.get("done_adapter",
lambda dones: list(dones.values()))
self._state_adapter = config.get("state_adapter",
default_state_adapter)
self._headless = config.get("headless", False)
self._timestep_sec = config.get("timestep_sec", 0.01)
self._observations = None
self._state = None
self._steps = 0
seed = self._config.get("seed", 42)
smarts.core.seed(seed)
self._scenarios_iterator = Scenario.scenario_variations(
config["scenarios"], self._agent_ids)
agent_interfaces = {
agent_id: AgentInterface.from_type(
config.get("agent_type", AgentType.Laner),
max_episode_steps=self.episode_limit,
debug=config.get("debug", False),
)
for i, agent_id, in enumerate(self._agent_ids)
}
envision = None
if not self._headless:
envision = Envision(
endpoint=config.get("envision_endpoint", None),
output_dir=config.get("envision_record_data_replay_path",
None),
)
self._smarts = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=SumoTrafficSimulation(
time_resolution=self._timestep_sec),
envision=envision,
timestep_sec=self._timestep_sec,
)
def _smarts_with_agent(agent) -> SMARTS:
agents = {AGENT_ID: agent}
return SMARTS(
agents,
traffic_sim=SumoTrafficSimulation(headless=True),
envision=None,
)
def main(scenarios, headless, seed):
agent_spec = AgentSpec(
interface=AgentInterface.from_type(AgentType.Laner,
max_episode_steps=None),
agent_builder=None,
observation_adapter=None,
)
smarts = SMARTS(
agent_interfaces={},
traffic_sim=SumoTrafficSimulation(headless=True, auto_start=True),
envision=Envision(),
)
scenarios_iterator = Scenario.scenario_variations(
scenarios,
list([]),
)
smarts.reset(next(scenarios_iterator))
for _ in range(5000):
smarts.step({})
smarts.attach_sensors_to_vehicles(
agent_spec, smarts.vehicle_index.social_vehicle_ids())
obs, _, _, _ = smarts.observe_from(
smarts.vehicle_index.social_vehicle_ids())
def _build_smarts(self):
agent_interfaces = {
agent_id: spec.interface
for agent_id, spec in self._agent_specs.items()
}
envision = None
if not self._headless or self._envision_record_data_replay_path:
envision = Envision(
endpoint=self._envision_endpoint,
sim_name=self._sim_name,
output_dir=self._envision_record_data_replay_path,
headless=self._headless,
)
sim = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=SumoTrafficSimulation(
headless=self._sumo_headless,
time_resolution=self._fixed_timestep_sec,
num_external_sumo_clients=self._num_external_sumo_clients,
sumo_port=self._sumo_port,
auto_start=self._sumo_auto_start,
endless_traffic=self._endless_traffic,
),
envision=envision,
fixed_timestep_sec=self._fixed_timestep_sec,
)
return sim
def main(scenarios, headless, seed):
scenarios_iterator = Scenario.scenario_variations(scenarios, [])
for _ in scenarios:
scenario = next(scenarios_iterator)
agent_missions = scenario.discover_missions_of_traffic_histories()
for agent_id, mission in agent_missions.items():
scenario.set_ego_missions({agent_id: mission})
agent_spec = AgentSpec(
interface=AgentInterface.from_type(AgentType.Laner,
max_episode_steps=None),
agent_builder=KeepLaneAgent,
)
agent = agent_spec.build_agent()
smarts = SMARTS(
agent_interfaces={agent_id: agent_spec.interface},
traffic_sim=SumoTrafficSimulation(headless=True,
auto_start=True),
envision=Envision(),
)
observations = smarts.reset(scenario)
dones = {agent_id: False}
while not dones[agent_id]:
agent_obs = observations[agent_id]
agent_action = agent.act(agent_obs)
observations, rewards, dones, infos = smarts.step(
{agent_id: agent_action})
def reset(self, choose=True):
if choose:
try:
self.current_observations = self._reset()
except:
self.close()
self._smarts = SMARTS(
agent_interfaces=self.agent_interfaces,
traffic_sim=SumoTrafficSimulation(
headless=self.all_args.sumo_headless,
time_resolution=self.all_args.timestep_sec,
num_external_sumo_clients=self.all_args.
num_external_sumo_clients,
sumo_port=self.all_args.sumo_port,
auto_start=self.all_args.sumo_auto_start,
endless_traffic=self.all_args.endless_traffic,
),
envision=self.envision_client,
visdom=self.visdom_client,
timestep_sec=self.all_args.timestep_sec,
zoo_workers=self.all_args.zoo_workers,
auth_key=self.all_args.auth_key,
)
self.current_observations = self._reset()
return self.get_obs()
else:
return [np.zeros(self.obs_dim) for agent_id in self.agent_ids]
def test_data_replay(agent_spec, scenarios_iterator, data_replay_path, monkeypatch):
"""We stub out the websocket the Envision client writes to and store the sent data.
We do the same under Envision client's replay feature and compare that the data
sent to the websocket is the same as before.
"""
def step_through_episodes(agent_spec, smarts, scenarios_iterator):
for i in range(NUM_EPISODES):
agent = agent_spec.build_agent()
scenario = next(scenarios_iterator)
obs = smarts.reset(scenario)
done = False
while not done:
obs = agent_spec.observation_adapter(obs[AGENT_ID])
action = agent.act(obs)
action = agent_spec.action_adapter(action)
obs, _, dones, _ = smarts.step({AGENT_ID: action})
done = dones[AGENT_ID]
# 1. Inspect sent data during SMARTS simulation
# Mock WebSocketApp so we can inspect the websocket frames being sent
FakeWebSocketApp, original_sent_data = fake_websocket_app_class()
monkeypatch.setattr(websocket, "WebSocketApp", FakeWebSocketApp)
assert original_sent_data.qsize() == 0
envision = Envision(output_dir=data_replay_path)
smarts = SMARTS(
agent_interfaces={AGENT_ID: agent_spec.interface},
traffic_sim=SumoTrafficSimulation(time_resolution=TIMESTEP_SEC),
envision=envision,
timestep_sec=TIMESTEP_SEC,
)
step_through_episodes(agent_spec, smarts, scenarios_iterator)
smarts.destroy()
data_replay_path = Path(data_replay_path)
data_replay_run_paths = [x for x in data_replay_path.iterdir() if x.is_dir()]
assert len(data_replay_run_paths) == 1
jsonl_paths = list(data_replay_run_paths[0].glob("*.jsonl"))
assert len(jsonl_paths) == 1
assert original_sent_data.qsize() > 0
# 2. Inspect replay data
# Mock WebSocketApp so we can inspect the websocket frames being sent
FakeWebSocketApp, new_sent_data = fake_websocket_app_class()
monkeypatch.setattr(websocket, "WebSocketApp", FakeWebSocketApp)
assert new_sent_data.qsize() == 0
# Now read data replay
Envision.read_and_send(jsonl_paths[0], timestep_sec=TIMESTEP_SEC)
# Verify the new data matches the original data
assert original_sent_data.qsize() == new_sent_data.qsize()
for _ in range(new_sent_data.qsize()):
assert original_sent_data.get() == new_sent_data.get()
def __init__(
self,
scenarios: Sequence[str],
agent_specs,
shuffle_scenarios=True,
headless=False,
visdom=False,
timestep_sec=0.1,
seed=42,
num_external_sumo_clients=0,
sumo_headless=True,
sumo_port=None,
sumo_auto_start=True,
endless_traffic=True,
envision_endpoint=None,
envision_record_data_replay_path=None,
zoo_workers=None,
auth_key=None,
):
self._log = logging.getLogger(self.__class__.__name__)
smarts.core.seed(seed)
self._agent_specs = agent_specs
self._dones_registered = 0
self._scenarios_iterator = Scenario.scenario_variations(
scenarios, list(agent_specs.keys()), shuffle_scenarios,
)
agent_interfaces = {
agent_id: agent.interface for agent_id, agent in agent_specs.items()
}
envision_client = None
if not headless:
envision_client = Envision(
endpoint=envision_endpoint, output_dir=envision_record_data_replay_path
)
visdom_client = None
if visdom:
visdom_client = VisdomClient()
self._smarts = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=SumoTrafficSimulation(
headless=sumo_headless,
time_resolution=timestep_sec,
num_external_sumo_clients=num_external_sumo_clients,
sumo_port=sumo_port,
auto_start=sumo_auto_start,
endless_traffic=endless_traffic,
),
envision=envision_client,
visdom=visdom_client,
timestep_sec=timestep_sec,
zoo_workers=zoo_workers,
auth_key=auth_key,
)
def smarts(scenarios, mock_provider):
smarts_ = SMARTS(
agent_interfaces={}, traffic_sim=SumoTrafficSimulation(time_resolution=0.1),
)
smarts_.add_provider(mock_provider)
smarts_.reset(next(scenarios))
yield smarts_
smarts_.destroy()
def smarts():
smarts_ = SMARTS(
agent_interfaces={
AGENT_ID: AgentInterface.from_type(AgentType.Laner, max_episode_steps=30)
},
traffic_sim=SumoTrafficSimulation(time_resolution=0.1),
)
yield smarts_
smarts_.destroy()
def spawn_sumo(worker_idx, batch_id):
sumo_sim = SumoTrafficSimulation(headless=True)
scenarios_iterator = Scenario.scenario_variations(
["scenarios/loop"],
["Agent007"],
)
sumo_sim.setup(Scenario.next(scenarios_iterator, f"{batch_id}-{worker_idx}"))
sumo_sim.teardown()
def smarts():
laner = AgentInterface(max_episode_steps=1000, action=ActionSpaceType.Lane,)
buddha = AgentInterface(max_episode_steps=1000, action=ActionSpaceType.Lane,)
agents = {AGENT_1: laner, AGENT_2: buddha}
smarts = SMARTS(
agents, traffic_sim=SumoTrafficSimulation(headless=True), envision=None,
)
yield smarts
smarts.destroy()
def __init__(
self,
scenarios: Sequence[str],
agent_specs,
visdom=False,
headless=False,
timestep_sec=0.1,
seed=42,
num_external_sumo_clients=0,
sumo_headless=True,
sumo_port=None,
sumo_auto_start=True,
endless_traffic=True,
envision_endpoint=None,
envision_record_data_replay_path=None,
):
self._log = logging.getLogger(self.__class__.__name__)
smarts.core.seed(seed)
self._visdom_obs_queue = None
if visdom:
self._log.debug("Running with visdom")
self._visdom_obs_queue = build_visdom_watcher_queue()
self._agent_specs = agent_specs
self._dones_registered = 0
self._scenarios_iterator = Scenario.scenario_variations(
scenarios,
list(agent_specs.keys()),
)
agent_interfaces = {
agent_id: agent.interface
for agent_id, agent in agent_specs.items()
}
envision = None
if not headless:
envision = Envision(endpoint=envision_endpoint,
output_dir=envision_record_data_replay_path)
self._smarts = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=SumoTrafficSimulation(
headless=sumo_headless,
time_resolution=timestep_sec,
num_external_sumo_clients=num_external_sumo_clients,
sumo_port=sumo_port,
auto_start=sumo_auto_start,
endless_traffic=endless_traffic,
),
envision=envision,
timestep_sec=timestep_sec,
)
def smarts():
buddha = AgentInterface(
max_episode_steps=1000, neighborhood_vehicles=True, action=ActionSpaceType.Lane,
)
smarts = SMARTS(
agent_interfaces={"Agent-007": buddha},
traffic_sim=SumoTrafficSimulation(headless=True),
envision=None,
)
yield smarts
smarts.destroy()
def main(scenarios: Sequence[str], headless: bool, seed: int):
agent_spec = AgentSpec(
interface=AgentInterface.from_type(AgentType.Laner,
max_episode_steps=None),
agent_builder=None,
observation_adapter=None,
)
smarts = SMARTS(
agent_interfaces={},
traffic_sim=SumoTrafficSimulation(headless=headless, auto_start=True),
envision=None if headless else Envision(),
)
scenarios_iterator = Scenario.scenario_variations(
scenarios,
list([]),
)
scenario = next(scenarios_iterator)
obs = smarts.reset(scenario)
collected_data = {}
_record_data(smarts.elapsed_sim_time, obs, collected_data)
# could also include "motorcycle" or "truck" in this set if desired
vehicle_types = frozenset({"car"})
while True:
smarts.step({})
current_vehicles = smarts.vehicle_index.social_vehicle_ids(
vehicle_types=vehicle_types)
if collected_data and not current_vehicles:
print("no more vehicles. exiting...")
break
smarts.attach_sensors_to_vehicles(agent_spec, current_vehicles)
obs, _, _, dones = smarts.observe_from(current_vehicles)
_record_data(smarts.elapsed_sim_time, obs, collected_data)
# an example of how we might save the data per car
for car, data in collected_data.items():
outfile = f"data_{scenario.name}_{scenario.traffic_history.name}_{car}.pkl"
with open(outfile, "wb") as of:
pickle.dump(data, of)
smarts.destroy()
def sim(request):
shared_interface = AgentInterface(done_criteria=DoneCriteria(
agents_alive=request.param))
agents = {
AGENT1: shared_interface,
AGENT2: shared_interface,
AGENT3: shared_interface,
}
smarts = SMARTS(
agents,
traffic_sim=SumoTrafficSimulation(headless=True),
envision=None,
)
yield smarts
smarts.destroy()
def main(scenarios, headless, seed):
agent_spec = AgentSpec(
interface=AgentInterface.from_type(AgentType.Laner,
max_episode_steps=None),
agent_builder=None,
observation_adapter=None,
)
smarts = SMARTS(
agent_interfaces={},
traffic_sim=SumoTrafficSimulation(headless=headless, auto_start=True),
envision=None if headless else Envision(),
)
scenarios_iterator = Scenario.scenario_variations(
scenarios,
list([]),
)
smarts.reset(next(scenarios_iterator))
prev_vehicles = set()
done_vehicles = set()
for _ in range(5000):
smarts.step({})
current_vehicles = smarts.vehicle_index.social_vehicle_ids()
# We explicitly watch for which agent/vehicles left the simulation here
# since we don't have a "done criteria" that detects when a vehicle's
# traffic history has played itself out.
done_vehicles = prev_vehicles - current_vehicles
prev_vehicles = current_vehicles
smarts.attach_sensors_to_vehicles(agent_spec, current_vehicles)
obs, _, _, dones = smarts.observe_from(current_vehicles)
# The `dones` returned above should be empty for traffic histories
# where all vehicles are assumed to stay on the road and not collide.
# TODO: add the following assert once the maps are accurate enough that
# we don't have any agents accidentally go off-road.
# assert not done
for v in done_vehicles:
dones[f"Agent-{v}"] = True
# TODO: save observations for imitation learning
smarts.destroy()
def setup_smarts(
self,
headless: bool = True,
seed: int = 42,
time_ratio: float = 1.0,
sumo_traffic: bool = False,
):
"""Do the setup of the underlying SMARTS instance."""
assert not self._smarts
if not self._state_publisher:
raise RuntimeError("must call setup_ros() first.")
self._zoo_module = rospy.get_param("~zoo_module", "zoo")
headless = rospy.get_param("~headless", headless)
seed = rospy.get_param("~seed", seed)
time_ratio = rospy.get_param("~time_ratio", time_ratio)
assert time_ratio > 0.0
self._time_ratio = time_ratio
traffic_sim = None
if rospy.get_param("~sumo_traffic", sumo_traffic):
from smarts.core.sumo_traffic_simulation import SumoTrafficSimulation
# Note that Sumo uses a fixed timestep, so if we have a highly-variable step rate,
# we may want to set time_resolution to a mutiple of the target_freq?
time_resolution = 1.0 / self._target_freq if self._target_freq else None
traffic_sim = SumoTrafficSimulation(
headless=headless,
time_resolution=time_resolution,
)
self._smarts = SMARTS(
agent_interfaces={},
traffic_sim=traffic_sim,
fixed_timestep_sec=None,
envision=None if headless else Envision(),
external_provider=True,
)
assert self._smarts.external_provider
self._last_step_time = None
def main(scenarios, headless, seed):
scenarios_iterator = Scenario.scenario_variations(scenarios, [])
smarts = SMARTS(
agent_interfaces={},
traffic_sim=SumoTrafficSimulation(headless=True, auto_start=True),
envision=Envision(),
)
for _ in scenarios:
scenario = next(scenarios_iterator)
agent_missions = scenario.discover_missions_of_traffic_histories()
for agent_id, mission in agent_missions.items():
agent_spec = AgentSpec(
interface=AgentInterface.from_type(AgentType.Laner,
max_episode_steps=None),
agent_builder=KeepLaneAgent,
)
agent = agent_spec.build_agent()
smarts.switch_ego_agent({agent_id: agent_spec.interface})
# required: get traffic_history_provider and set time offset
traffic_history_provider = smarts.get_provider_by_type(
TrafficHistoryProvider)
assert traffic_history_provider
traffic_history_provider.set_start_time(mission.start_time)
modified_mission = replace(mission, start_time=0.0)
scenario.set_ego_missions({agent_id: modified_mission})
observations = smarts.reset(scenario)
dones = {agent_id: False}
while not dones[agent_id]:
agent_obs = observations[agent_id]
agent_action = agent.act(agent_obs)
observations, rewards, dones, infos = smarts.step(
{agent_id: agent_action})
smarts.destroy()
def __init__(self,
scenarios: Sequence[str],
agent_specs: Dict,
shuffle_scenarios=True,
headless=False,
visdom=False,
timestep_sec=0.1,
seed=42,
num_external_sumo_clients=0,
sumo_headless=True,
sumo_port=None,
sumo_auto_start=True,
endless_traffic=True,
envision_endpoint=None,
envision_record_data_replay_path=None,
zoo_addrs=None):
self._metircs = Metric(1)
self.has_connection = False
self._log = logging.getLogger(self.__class__.__name__)
smarts.core.seed(seed) # Set seed for np and random module.
self._agent_specs = agent_specs
self._dones_registered = 0
# Setup ego.
self._ego = agent_specs[EGO_ID].build_agent()
# Setup sceanrios for benchmark.
self._scenarios_iterator = Scenario.scenario_variations(
scenarios,
list(agent_specs.keys()),
shuffle_scenarios,
)
# Setup envision and visdom.
envision_client = None
if not headless:
envision_client = Envision(
endpoint=envision_endpoint,
output_dir=envision_record_data_replay_path)
visdom_client = None
if visdom:
visdom_client = VisdomClient()
# Setup SMARTS
agent_interfaces = {
agent_id: agent.interface
for agent_id, agent in agent_specs.items()
}
self._smarts = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=SumoTrafficSimulation(
headless=sumo_headless,
time_resolution=timestep_sec,
num_external_sumo_clients=num_external_sumo_clients,
sumo_port=sumo_port,
auto_start=sumo_auto_start,
endless_traffic=endless_traffic,
),
envision=envision_client,
visdom=visdom_client,
timestep_sec=timestep_sec,
zoo_addrs=zoo_addrs)
def traffic_sim():
return SumoTrafficSimulation(headless=True,
num_external_sumo_clients=1,
sumo_port=SUMO_PORT)
def main(script: str, scenarios: Sequence[str], headless: bool, seed: int):
logger = logging.getLogger(script)
logger.setLevel(logging.INFO)
agent_spec = AgentSpec(
interface=AgentInterface.from_type(AgentType.Laner, max_episode_steps=None),
agent_builder=None,
observation_adapter=None,
)
smarts = SMARTS(
agent_interfaces={},
traffic_sim=SumoTrafficSimulation(headless=headless, auto_start=True),
envision=None if headless else Envision(),
)
scenario_list = Scenario.get_scenario_list(scenarios)
scenarios_iterator = Scenario.variations_for_all_scenario_roots(scenario_list, [])
for scenario in scenarios_iterator:
obs = smarts.reset(scenario)
collected_data = {}
_record_data(smarts.elapsed_sim_time, obs, collected_data)
# could also include "motorcycle" or "truck" in this set if desired
vehicle_types = frozenset({"car"})
# filter off-road vehicles from observations
vehicles_off_road = set()
while True:
smarts.step({})
current_vehicles = smarts.vehicle_index.social_vehicle_ids(
vehicle_types=vehicle_types
)
if collected_data and not current_vehicles:
print("no more vehicles. exiting...")
break
for veh_id in current_vehicles:
try:
smarts.attach_sensors_to_vehicles(agent_spec.interface, {veh_id})
except ControllerOutOfLaneException:
logger.warning(f"{veh_id} out of lane, skipped attaching sensors")
vehicles_off_road.add(veh_id)
valid_vehicles = {v for v in current_vehicles if v not in vehicles_off_road}
obs, _, _, dones = smarts.observe_from(valid_vehicles)
_record_data(smarts.elapsed_sim_time, obs, collected_data)
# an example of how we might save the data per car
observation_folder = "collected_observations"
if not os.path.exists(observation_folder):
os.makedirs(observation_folder)
for car, data in collected_data.items():
outfile = f"{observation_folder}/{scenario.name}_{scenario.traffic_history.name}_{car}.pkl"
with open(outfile, "wb") as of:
pickle.dump(data, of)
smarts.destroy()
def __init__(
self,
scenarios: Sequence[str],
agent_specs: Dict[str, AgentSpec],
sim_name=None,
shuffle_scenarios=True,
headless=False,
visdom=False,
fixed_timestep_sec=None,
seed=42,
num_external_sumo_clients=0,
sumo_headless=True,
sumo_port=None,
sumo_auto_start=True,
endless_traffic=True,
envision_endpoint=None,
envision_record_data_replay_path=None,
zoo_addrs=None,
timestep_sec=None, # for backwards compatibility (deprecated)
):
self._log = logging.getLogger(self.__class__.__name__)
self.seed(seed)
if timestep_sec and not fixed_timestep_sec:
warnings.warn(
"timestep_sec has been deprecated in favor of fixed_timestep_sec. Please update your code.",
category=DeprecationWarning,
)
if not fixed_timestep_sec:
fixed_timestep_sec = timestep_sec or 0.1
self._agent_specs = agent_specs
self._dones_registered = 0
self._scenarios_iterator = Scenario.scenario_variations(
scenarios,
list(agent_specs.keys()),
shuffle_scenarios,
)
agent_interfaces = {
agent_id: agent.interface
for agent_id, agent in agent_specs.items()
}
envision_client = None
if not headless or envision_record_data_replay_path:
envision_client = Envision(
endpoint=envision_endpoint,
sim_name=sim_name,
output_dir=envision_record_data_replay_path,
headless=headless,
)
visdom_client = None
if visdom:
visdom_client = VisdomClient()
all_sumo = Scenario.supports_traffic_simulation(scenarios)
traffic_sim = None
if not all_sumo:
# We currently only support the Native SUMO Traffic Provider and Social Agents for SUMO maps
if zoo_addrs:
warnings.warn(
"`zoo_addrs` can only be used with SUMO scenarios")
zoo_addrs = None
warnings.warn(
"We currently only support the Native SUMO Traffic Provider and Social Agents for SUMO maps."
"All scenarios passed need to be of SUMO, to enable SUMO Traffic Simulation and Social Agents."
)
pass
else:
from smarts.core.sumo_traffic_simulation import SumoTrafficSimulation
traffic_sim = SumoTrafficSimulation(
headless=sumo_headless,
time_resolution=fixed_timestep_sec,
num_external_sumo_clients=num_external_sumo_clients,
sumo_port=sumo_port,
auto_start=sumo_auto_start,
endless_traffic=endless_traffic,
)
zoo_addrs = zoo_addrs
self._smarts = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=traffic_sim,
envision=envision_client,
visdom=visdom_client,
fixed_timestep_sec=fixed_timestep_sec,
zoo_addrs=zoo_addrs,
)
def __init__(self, all_args):
self.all_args = all_args
self._dones_registered = 0
self.neighbor_num = all_args.neighbor_num
self.rews_mode = all_args.rews_mode
self.n_agents = all_args.num_agents
self.use_proximity = all_args.use_proximity
self.use_discrete = all_args.use_discrete # default True
self.use_centralized_V = all_args.use_centralized_V
self.scenarios = [(all_args.scenario_path + all_args.scenario_name)]
self.agent_ids = ["Agent %i" % i for i in range(self.n_agents)]
self.obs_space_dict = self.get_obs_space_dict()
self.obs_dim = self.get_obs_dim()
# ! TODO:
self.share_obs_dim = self.get_state_dim(
) if self.use_centralized_V else self.get_obs_dim()
self.observation_space = [
gym.spaces.Box(low=-1e10, high=1e10, shape=(self.obs_dim, ))
] * self.n_agents
self.share_observation_space = [
gym.spaces.Box(low=-1e10, high=1e10, shape=(self.share_obs_dim, ))
] * self.n_agents
if self.use_discrete:
self.act_dim = 4
self.action_space = [gym.spaces.Discrete(self.act_dim)
] * self.n_agents
self.agent_type = AgentType.Vulner_with_proximity if self.use_proximity else AgentType.Vulner
else:
# TODO Add continous action space
self.agent_type = AgentType.VulnerCon_with_proximity if self.use_proximity else AgentType.VulnerCon
raise NotImplementedError
self._agent_specs = {
agent_id: AgentSpec(
interface=AgentInterface.from_type(
self.agent_type, max_episode_steps=all_args.horizon),
observation_adapter=self.get_obs_adapter(),
reward_adapter=self.get_rew_adapter(self.rews_mode,
self.neighbor_num),
action_adapter=self.get_act_adapter(),
)
for agent_id in self.agent_ids
}
self._scenarios_iterator = Scenario.scenario_variations(
self.scenarios,
list(self._agent_specs.keys()),
all_args.shuffle_scenarios,
)
self.agent_interfaces = {
agent_id: agent.interface
for agent_id, agent in self._agent_specs.items()
}
self.envision_client = None
if not all_args.headless:
self.envision_client = Envision(
endpoint=all_args.envision_endpoint,
output_dir=all_args.envision_record_data_replay_path)
self.visdom_client = None
if all_args.visdom:
self.visdom_client = VisdomClient()
self._smarts = SMARTS(
agent_interfaces=self.agent_interfaces,
traffic_sim=SumoTrafficSimulation(
headless=all_args.sumo_headless,
time_resolution=all_args.timestep_sec,
num_external_sumo_clients=all_args.num_external_sumo_clients,
sumo_port=all_args.sumo_port,
auto_start=all_args.sumo_auto_start,
endless_traffic=all_args.endless_traffic,
),
envision=self.envision_client,
visdom=self.visdom_client,
timestep_sec=all_args.timestep_sec,
zoo_workers=all_args.zoo_workers,
auth_key=all_args.auth_key,
)
client.configureDebugVisualizer(pybullet.COV_ENABLE_WIREFRAME, 1)
while True:
client.resetSimulation()
client.setGravity(0, 0, -9.8)
client.setPhysicsEngineParameter(
fixedTimeStep=TIMESTEP_SEC,
numSubSteps=int(TIMESTEP_SEC / (1 / 240)),
# enableConeFriction=False,
# erp=0.1,
# contactERP=0.1,
# frictionERP=0.1,
)
path = Path(__file__).parent / "../smarts/core/models/plane.urdf"
path = str(path.absolute())
plane_body_id = client.loadURDF(path, useFixedBase=True)
vehicle_config = VEHICLE_CONFIGS["passenger"]
traffic_sim = SumoTrafficSimulation(headless=False,
time_resolution=0.1,
debug=True)
run(
client,
traffic_sim,
plane_body_id,
n_steps=int(1e6),
)
def __init__(
self,
scenarios: Sequence[str],
agent_specs: Dict[str, AgentSpec],
sim_name: Optional[str] = None,
shuffle_scenarios: bool = True,
headless: bool = True,
visdom: bool = False,
fixed_timestep_sec: Optional[float] = None,
seed: int = 42,
num_external_sumo_clients: int = 0,
sumo_headless: bool = True,
sumo_port: Optional[str] = None,
sumo_auto_start: bool = True,
endless_traffic: bool = True,
envision_endpoint: Optional[str] = None,
envision_record_data_replay_path: Optional[str] = None,
zoo_addrs: Optional[str] = None,
timestep_sec: Optional[
float
] = None, # for backwards compatibility (deprecated)
):
"""
Args:
scenarios (Sequence[str]): A list of scenario directories that
will be simulated.
agent_specs (Dict[str, AgentSpec]): Specification of the agents
that will run in the environment.
sim_name (Optional[str], optional): Simulation name. Defaults to
None.
shuffle_scenarios (bool, optional): If true, order of scenarios
will be randomized, else it will be maintained. Defaults to
True.
headless (bool, optional): If True, disables visualization in
Envision. Defaults to False.
visdom (bool, optional): If True, enables visualization of observed
RGB images in Visdom. Defaults to False.
fixed_timestep_sec (Optional[float], optional): Step duration for
all components of the simulation. May be None if time deltas
are externally-driven. Defaults to None.
seed (int, optional): Random number generator seed. Defaults to 42.
num_external_sumo_clients (int, optional): Number of SUMO clients
beyond SMARTS. Defaults to 0.
sumo_headless (bool, optional): If True, disables visualization in
SUMO GUI. Defaults to True.
sumo_port (Optional[str], optional): SUMO port. Defaults to None.
sumo_auto_start (bool, optional): Automatic starting of SUMO.
Defaults to True.
endless_traffic (bool, optional): SUMO's endless traffic setting.
Defaults to True.
envision_endpoint (Optional[str], optional): Envision's uri.
Defaults to None.
envision_record_data_replay_path (Optional[str], optional):
Envision's data replay output directory. Defaults to None.
zoo_addrs (Optional[str], optional): List of (ip, port) tuples of
zoo server, used to instantiate remote social agents. Defaults
to None.
timestep_sec (Optional[float], optional): [description]. Defaults
to None.
"""
self._log = logging.getLogger(self.__class__.__name__)
self.seed(seed)
if timestep_sec and not fixed_timestep_sec:
warnings.warn(
"timestep_sec has been deprecated in favor of fixed_timestep_sec. Please update your code.",
category=DeprecationWarning,
)
if not fixed_timestep_sec:
fixed_timestep_sec = timestep_sec or 0.1
self._agent_specs = agent_specs
self._dones_registered = 0
self._scenarios_iterator = Scenario.scenario_variations(
scenarios,
list(agent_specs.keys()),
shuffle_scenarios,
)
agent_interfaces = {
agent_id: agent.interface for agent_id, agent in agent_specs.items()
}
envision_client = None
if not headless or envision_record_data_replay_path:
envision_client = Envision(
endpoint=envision_endpoint,
sim_name=sim_name,
output_dir=envision_record_data_replay_path,
headless=headless,
)
visdom_client = None
if visdom:
visdom_client = VisdomClient()
all_sumo = Scenario.supports_traffic_simulation(scenarios)
traffic_sim = None
if not all_sumo:
# We currently only support the Native SUMO Traffic Provider and Social Agents for SUMO maps
if zoo_addrs:
warnings.warn("`zoo_addrs` can only be used with SUMO scenarios")
zoo_addrs = None
warnings.warn(
"We currently only support the Native SUMO Traffic Provider and Social Agents for SUMO maps."
"All scenarios passed need to be of SUMO, to enable SUMO Traffic Simulation and Social Agents."
)
pass
else:
from smarts.core.sumo_traffic_simulation import SumoTrafficSimulation
traffic_sim = SumoTrafficSimulation(
headless=sumo_headless,
time_resolution=fixed_timestep_sec,
num_external_sumo_clients=num_external_sumo_clients,
sumo_port=sumo_port,
auto_start=sumo_auto_start,
endless_traffic=endless_traffic,
)
zoo_addrs = zoo_addrs
self._smarts = SMARTS(
agent_interfaces=agent_interfaces,
traffic_sim=traffic_sim,
envision=envision_client,
visdom=visdom_client,
fixed_timestep_sec=fixed_timestep_sec,
zoo_addrs=zoo_addrs,
)
def smarts():
smarts = SMARTS({}, traffic_sim=SumoTrafficSimulation())
yield smarts
smarts.destroy()