def __init__(self,
configuration=None,
dynamic_model=None,
agents_to_observe=None):
DynamicBehaviorModel.__init__(self, dynamic_model,
configuration._params)
self._configuration = configuration
self._dynamic_model = dynamic_model
self._agents_to_observe = agents_to_observe
class BARKMLBehaviorModel(BehaviorModel):
"""This class makes a trained agent available as BehaviorModel
in BARK.
"""
def __init__(self, configuration=None):
BehaviorModel.__init__(self, configuration._params)
self._configuration = configuration
self._dynamic_behavior_model = DynamicBehaviorModel(
self._configuration._behavior_model._dynamic_model,
configuration._params)
def Plan(self, delta_time, observed_world):
self._configuration._observer.reset(observed_world, [0])
observed_state = self._configuration._observer.observe(observed_world)
action = self._configuration._agent.act(observed_state)
self._dynamic_behavior_model.SetLastAction(action)
trajectory = self._dynamic_behavior_model.Plan(delta_time,
observed_world)
super(BARKMLBehaviorModel, self).SetLastTrajectory(trajectory)
return trajectory
def Clone(self):
return self
def __getstate__(self):
try:
del self.__dict__['_configuration']
except:
pass
try:
del self.__dict__['_dynamic_behavior_model']
except:
pass
odict = self.__dict__.copy()
return odict
def __setstate__(self, sdict):
# HACK
base_dir = "/home/hart/Dokumente/2020/bark-ml"
params = ParameterServer(filename=base_dir +
"/configurations/highway/config.json")
scenario_generation = params["Scenario"]["Generation"][
"ConfigurableScenarioGeneration"]
map_filename = scenario_generation["MapFilename"]
scenario_generation["MapFilename"] = base_dir + "/" + map_filename
params["BaseDir"] = base_dir
sdict['_configuration'] = HighwayConfiguration(params)
sdict['_dynamic_behavior_model'] = DynamicBehaviorModel(
sdict['_configuration']._behavior_model._dynamic_model,
sdict['_configuration']._params)
BehaviorModel.__init__(self, sdict['_configuration']._params)
self.__dict__.update(sdict)
def test_python_model(self):
param_server = ParameterServer(
filename="modules/runtime/tests/data/deterministic_scenario.json")
scenario_generation = DeterministicScenarioGeneration(num_scenarios=3,
random_seed=0,
params=param_server)
viewer = MPViewer(params=param_server,
follow_agent_id=False,
use_world_bounds=True)
env = Runtime(0.2,
viewer,
scenario_generation,
render=True)
single_track_model = SingleTrackModel(param_server)
behavior_model = DynamicBehaviorModel(single_track_model, param_server)
env.reset()
env._world.get_agent(0).behavior_model = behavior_model
env._world.get_agent(0).behavior_model.clone()
env.reset()
env._world.get_agent(0).behavior_model = behavior_model
env._world.get_agent(0).behavior_model.set_last_action(np.array([1., 2.]))
print(env._world.get_agent(0).behavior_model.get_last_action())
env._world.step(0.2)
print(env._world.get_agent(0).behavior_model.get_last_action())
def __setstate__(self, sdict):
# HACK
base_dir = "/home/hart/Dokumente/2020/bark-ml"
params = ParameterServer(filename=base_dir +
"/configurations/highway/config.json")
scenario_generation = params["Scenario"]["Generation"][
"ConfigurableScenarioGeneration"]
map_filename = scenario_generation["MapFilename"]
scenario_generation["MapFilename"] = base_dir + "/" + map_filename
params["BaseDir"] = base_dir
sdict['_configuration'] = HighwayConfiguration(params)
sdict['_dynamic_behavior_model'] = DynamicBehaviorModel(
sdict['_configuration']._behavior_model._dynamic_model,
sdict['_configuration']._params)
BehaviorModel.__init__(self, sdict['_configuration']._params)
self.__dict__.update(sdict)
def reset(self, world, agents_to_act):
"""see base class
"""
super(DynamicModel, self).reset(world=world,
agents_to_act=agents_to_act)
self._input_count = 0
self._behavior_models = []
for agent_id in agents_to_act:
self._behavior_models.append(
DynamicBehaviorModel(self._dynamic_model, self._params))
if agent_id in world.agents:
world.agents[agent_id].behavior_model = self._behavior_models[
-1]
world.agents[agent_id].set_move_automatically(False)
else:
raise ValueError("AgentID does not exist in world.")
return world
def reset(self, world, agents_to_act):
"""see base class
"""
super(DynamicModel, self).reset(world=world,
agents_to_act=agents_to_act)
self._behavior_models = []
self._controlled_agents = agents_to_act
for agent_id in agents_to_act:
self._behavior_models.append(
DynamicBehaviorModel(self._dynamic_model, self._params))
if agent_id in world.agents:
actions = np.zeros(shape=(self._control_inputs),
dtype=np.float32)
self._behavior_models[-1].SetLastAction(actions)
world.agents[agent_id].behavior_model = self._behavior_models[
-1]
else:
raise ValueError("AgentID does not exist in world.")
return world
def __init__(self, configuration=None):
BehaviorModel.__init__(self, configuration._params)
self._configuration = configuration
self._dynamic_behavior_model = DynamicBehaviorModel(
self._configuration._behavior_model._dynamic_model,
configuration._params)