def run(self, args):
"""
Run the challenge mode
"""
route_indexer = RouteIndexer(args.routes, args.scenarios, args.repetitions)
if args.resume:
route_indexer.resume(args.checkpoint)
self.statistics_manager.resume(args.checkpoint)
else:
self.statistics_manager.clear_record(args.checkpoint)
route_indexer.save_state(args.checkpoint)
while route_indexer.peek():
# setup
config = route_indexer.next()
# run
self._load_and_run_scenario(args, config)
route_indexer.save_state(args.checkpoint)
# save global statistics
print("\033[1m> Registering the global statistics\033[0m")
global_stats_record = self.statistics_manager.compute_global_statistics(route_indexer.total)
StatisticsManager.save_global_record(global_stats_record, self.sensor_icons, route_indexer.total, args.checkpoint)
def run(self, args, customized_data):
"""
Run the challenge mode
"""
route_indexer = RouteIndexer(args.routes, args.scenarios,
args.repetitions)
if args.resume:
route_indexer.resume(self.save_path)
self.statistics_manager.resume(self.save_path)
else:
self.statistics_manager.clear_record(self.save_path)
while route_indexer.peek():
# setup
config = route_indexer.next()
# run
self._load_and_run_scenario(args, config, customized_data)
self._cleanup(ego=True)
route_indexer.save_state(self.save_path)
# save global statistics
# modification
global_stats_record = self.statistics_manager.compute_global_statistics(
route_indexer.total)
StatisticsManager.save_global_record(global_stats_record, self.sensors,
self.save_path)
def run(self, args, filename, data_folder, route_folder, model_path):
"""
Run the challenge mode
"""
route_indexer = RouteIndexer(args.routes, args.scenarios,
args.repetitions, route_folder)
if args.resume:
route_indexer.resume(args.checkpoint)
self.statistics_manager.resume(args.checkpoint)
else:
self.statistics_manager.clear_record(args.checkpoint)
k = 0
while route_indexer.peek():
#x = time.time()
k += 1
# setup
config = route_indexer.next()
# run
self._load_and_run_scenario(args, config, data_folder,
route_folder, k, model_path)
self._cleanup(ego=True)
route_indexer.save_state(args.checkpoint)
# save global statistics
global_stats_record, route_in_km = self.statistics_manager.compute_global_statistics(
route_indexer.total)
StatisticsManager.save_global_record(global_stats_record,
route_in_km, self.sensors,
args.checkpoint, filename,
config)
def run(self, args):
"""
Run the challenge mode
"""
# agent_class_name = getattr(self.module_agent, 'get_entry_point')()
# self.agent_instance = getattr(self.module_agent, agent_class_name)(args.agent_config)
route_indexer = RouteIndexer(args.routes, args.scenarios, args.repetitions)
if args.resume:
route_indexer.resume(args.checkpoint)
self.statistics_manager.resume(args.checkpoint)
else:
self.statistics_manager.clear_record(args.checkpoint)
route_indexer.save_state(args.checkpoint)
while route_indexer.peek():
# setup
config = route_indexer.next()
# run
self._load_and_run_scenario(args, config)
for obj in gc.get_objects():
try:
if torch.is_tensor(obj) or (hasattr(obj, 'data') and torch.is_tensor(obj.data)):
print(type(obj), obj.size())
except:
pass
route_indexer.save_state(args.checkpoint)
# save global statistics
print("\033[1m> Registering the global statistics\033[0m")
global_stats_record = self.statistics_manager.compute_global_statistics(route_indexer.total)
StatisticsManager.save_global_record(global_stats_record, self.sensor_icons, route_indexer.total, args.checkpoint)