def parse_args():
    parser = argparse.ArgumentParser('gnn')
    parser.add_argument('--train_path', type=str, default='./data/diginetica/train.txt', help='dir of training data')
    parser.add_argument('--config_path', type=str, default='./data/diginetica/config.txt', help='dir of config')
    parser.add_argument('--model_path', type=str, default='./saved_model', help='path of model parameters')
    parser.add_argument('--epoch_num', type=int, default=30, help='number of epochs to train for')
    parser.add_argument('--batch_size', type=int, default=100, help='input batch size')
    parser.add_argument('--hidden_size', type=int, default=100, help='hidden state size')
    parser.add_argument('--l2', type=float, default=1e-05, help='l2 penalty')
    parser.add_argument('--lr', type=float, default=0.001, help='learning rate')
    parser.add_argument('--step', type=int, default=1, help='gnn propogation steps')
    parser.add_argument('--lr_dc', type=float, default=0.1, help='learning rate decay rate')
    parser.add_argument('--lr_dc_step', type=int, default=3, help='the number of steps after which the learning rate decay')
    parser.add_argument('--use_cuda', type=int, default=0, help='whether to use gpu')
    parser.add_argument('--use_parallel', type=int, default=1, help='whether to use parallel executor')
    parser.add_argument('--enable_ce', action='store_true', help='If set, run the task with continuous evaluation logs.')
    return parser.parse_args()
def parse_args():
    parser = argparse.ArgumentParser('gnn')
    parser.add_argument('--train_path', type=str, default='./data/diginetica/train.txt', help='dir of training data')
    parser.add_argument('--config_path', type=str, default='./data/diginetica/config.txt', help='dir of config')
    parser.add_argument('--model_path', type=str, default='./saved_model', help='path of model parameters')
    parser.add_argument('--epoch_num', type=int, default=30, help='number of epochs to train for')
    parser.add_argument('--batch_size', type=int, default=100, help='input batch size')
    parser.add_argument('--hidden_size', type=int, default=100, help='hidden state size')
    parser.add_argument('--l2', type=float, default=1e-05, help='l2 penalty')
    parser.add_argument('--lr', type=float, default=0.001, help='learning rate')
    parser.add_argument('--step', type=int, default=1, help='gnn propogation steps')
    parser.add_argument('--lr_dc', type=float, default=0.1, help='learning rate decay rate')
    parser.add_argument('--lr_dc_step', type=int, default=3, help='the number of steps after which the learning rate decay')
    parser.add_argument('--use_cuda', type=int, default=0, help='whether to use gpu')
    parser.add_argument('--use_parallel', type=int, default=1, help='whether to use parallel executor')
    parser.add_argument('--enable_ce', action='store_true', help='If set, run the task with continuous evaluation logs.')
    return parser.parse_args()