def __init__(self, bodies, ctrl, *args, **kargs):
MultiTask.__init__(self, *args, **kargs)
self._bodies = bodies
self._ctrl = ctrl
com_args = [ctrl.zmp_ctrl, ctrl.cdof, 1, 0, True, "CoM"]
if len(bodies):
self._subtask.append( CoMTask(bodies, *com_args) )
else:
self._subtask.append( LQPCoMTask(*com_args) )
self._subtask.append( ctrl.l_foot_task )
self._subtask.append( ctrl.r_foot_task )
def update(self, rstate, dt):
MultiTask.update(self, rstate, dt)
self._ctrl.update(rstate, dt)
def init(self, world, LQP_ctrl):
MultiTask.init(self, world, LQP_ctrl)
self._ctrl.init(world, LQP_ctrl)
import traceback
from task import build_tasks_from_file, MultiTask
from util import get_logger
from argparse import ArgumentParser
logger = get_logger(__name__)
arg_parser = ArgumentParser()
# arg_parser.add_argument('-d', '--device',
# type=int, default=0, help='GPU index')
# arg_parser.add_argument('-t', '--thread',
# type=int, default=5, help='Thread number')
arg_parser.add_argument('-c', '--config', help='Configuration file')
args = arg_parser.parse_args()
# torch.cuda.set_device(args.device)
# torch.set_num_threads(args.thread)
config_file = args.config
tasks, conf, _ = build_tasks_from_file(config_file, options=None)
multitask = MultiTask(tasks, eval_freq=conf.training.eval_freq)
try:
for step in range(1, conf.training.max_step + 1):
multitask.step()
except Exception:
traceback.print_exc()
