class ActionGiver(): def __init__(self, args): arg_parser = build_arg_parser(args) self.world = RLWorld(arg_parser) def get_ac(self, s, g): return self.world.get_action(s, g)
def build_world(args, enable_draw, playback_speed=1): arg_parser = build_arg_parser(args) # build env: core, seed env = DeepMimicEnv(args, enable_draw) # build world for agent world = RLWorld(env, arg_parser) world.env.set_playback_speed(playback_speed) return world
def build_world(args, enable_draw, playback_speed=1): arg_parser = build_arg_parser(args) env = DeepMimicEnv(args, enable_draw) world = RLWorld(env, arg_parser) world.env.set_playback_speed(playback_speed) return world
def __init__(self, args): arg_parser = build_arg_parser(args) self.world = RLWorld(arg_parser)
enable_draw = True timestep = 1. / 240. args = sys.argv[1:] arg_parser = ArgParser() arg_parser.load_args(args) arg_file = arg_parser.parse_string('arg_file', "run_humanoid3d_spinkick_args.txt") arg_parser.load_file(pybullet_data.getDataPath() + "/args/" + arg_file) motion_file = arg_parser.parse_strings('motion_file') fall_contact_bodies = arg_parser.parse_ints("fall_contact_bodies") env = PyBulletDeepMimicEnv(motion_file, enable_draw, fall_contact_bodies) world = RLWorld(env, arg_parser) world.reset() total_reward = 0 steps = 0 while True: world.update(timestep) total_reward += world.env.calc_reward(agent_id=0) steps += 1 if world.env.is_episode_end() or steps >= 1000: total_reward = 0