def parse_args():
    'PARAMETERS'
    parser = argparse.ArgumentParser('training')
    parser.add_argument('--use_cpu', action='store_true', default=False, help='use cpu mode')
    parser.add_argument('--gpu', type=str, default='0', help='specify gpu device')
    parser.add_argument('--batch_size', type=int, default=8, help='batch size in training')
    parser.add_argument('--model', default='pointnet_cls', help='model name [default: pointnet_cls]')
    parser.add_argument('--num_category', default=12, type=int, help='training on real dataset')
    parser.add_argument('--epoch', default=20, type=int, help='number of epoch in training')
    parser.add_argument('--learning_rate', default=0.001, type=float, help='learning rate in training')
    parser.add_argument('--num_point', type=int, default=1024, help='Point Number')
    parser.add_argument('--optimizer', type=str, default='Adam', help='optimizer for training')
    parser.add_argument('--log_dir', type=str, default=None, help='experiment root')
    parser.add_argument('--decay_rate', type=float, default=0.0001, help='decay rate')
    parser.add_argument('--use_normals', action='store_true', default=False, help='use normals')
    parser.add_argument('--process_data', action='store_true', default=False, help='save data offline')
    parser.add_argument('--use_uniform_sample', action='store_true', default=False, help='use uniform sampiling')
    parser.add_argument('--num_sparse_point', type=int, default=50, help='Point Number for domain loss')
    parser.add_argument('--random_choose_sparse', type=bool, default=False, help='Random select num_sparse_point from [10,20,30,40,50]')
    parser.add_argument('--SO3_Rotation', action='store_true', default=False, help='arbitrary rotation in SO3')
    parser.add_argument('--DA_method', type=str, default='multi_coral_mmd', help='choose the DA loss function')
    parser.add_argument('--alpha', type=float, default=10, help='set the value of classification loss')
    parser.add_argument('--lamda', type=float, default=10, help='set the value of CORAL loss')
    parser.add_argument('--beta', type=float, default=10, help='set the value of MMD loss')
    return parser.parse_args()
PARAMETERS
def parse_args():
    
    parser = argparse.ArgumentParser('training')
    parser.add_argument('--use_cpu', action='store_true', default=False, help='use cpu mode')
    parser.add_argument('--gpu', type=str, default='0', help='specify gpu device')
    parser.add_argument('--batch_size', type=int, default=8, help='batch size in training')
    parser.add_argument('--model', default='pointnet_cls', help='model name [default: pointnet_cls]')
    parser.add_argument('--num_category', default=12, type=int, help='training on real dataset')
    parser.add_argument('--epoch', default=20, type=int, help='number of epoch in training')
    parser.add_argument('--learning_rate', default=0.001, type=float, help='learning rate in training')
    parser.add_argument('--num_point', type=int, default=1024, help='Point Number')
    parser.add_argument('--optimizer', type=str, default='Adam', help='optimizer for training')
    parser.add_argument('--log_dir', type=str, default=None, help='experiment root')
    parser.add_argument('--decay_rate', type=float, default=0.0001, help='decay rate')
    parser.add_argument('--use_normals', action='store_true', default=False, help='use normals')
    parser.add_argument('--process_data', action='store_true', default=False, help='save data offline')
    parser.add_argument('--use_uniform_sample', action='store_true', default=False, help='use uniform sampiling')
    parser.add_argument('--num_sparse_point', type=int, default=50, help='Point Number for domain loss')
    parser.add_argument('--random_choose_sparse', type=bool, default=False, help='Random select num_sparse_point from [10,20,30,40,50]')
    parser.add_argument('--SO3_Rotation', action='store_true', default=False, help='arbitrary rotation in SO3')
    parser.add_argument('--DA_method', type=str, default='multi_coral_mmd', help='choose the DA loss function')
    parser.add_argument('--alpha', type=float, default=10, help='set the value of classification loss')
    parser.add_argument('--lamda', type=float, default=10, help='set the value of CORAL loss')
    parser.add_argument('--beta', type=float, default=10, help='set the value of MMD loss')
    return parser.parse_args()