args.py

from argparse import ArgumentParser
def make_args():
    parser = ArgumentParser()
    # general
    parser.add_argument('--comment', dest='comment', default='0', type=str,
                        help='comment')
    parser.add_argument('--task', dest='task', default='link', type=str,
                        help='link; link_pair')
    parser.add_argument('--model', dest='model', default='GCN', type=str,
                        help='model class name. E.g., GCN, PGNN, ...')
    parser.add_argument('--dataset', dest='dataset', default='All', type=str,
                        help='All; Cora; grid; communities; ppi')
    parser.add_argument('--gpu', dest='gpu', action='store_true',
                        help='whether use gpu')
    parser.add_argument('--cache_no', dest='cache', action='store_false',
                        help='whether use cache')
    parser.add_argument('--cpu', dest='gpu', action='store_false',
                        help='whether use cpu')
    parser.add_argument('--cuda', dest='cuda', default='0', type=str)

    # dataset
    parser.add_argument('--remove_link_ratio', dest='remove_link_ratio', default=0.2, type=float)
    parser.add_argument('--rm_feature', dest='rm_feature', action='store_true',
                        help='whether rm_feature')
    parser.add_argument('--rm_feature_no', dest='rm_feature', action='store_false',
                        help='whether rm_feature')
    parser.add_argument('--permute', dest='permute', action='store_true',
                        help='whether permute subsets')
    parser.add_argument('--permute_no', dest='permute', action='store_false',
                        help='whether permute subsets')
    parser.add_argument('--feature_pre', dest='feature_pre', action='store_true',
                        help='whether pre transform feature')
    parser.add_argument('--feature_pre_no', dest='feature_pre', action='store_false',
                        help='whether pre transform feature')
    parser.add_argument('--dropout', dest='dropout', action='store_true',
                        help='whether dropout, default 0.5')
    parser.add_argument('--dropout_no', dest='dropout', action='store_false',
                        help='whether dropout, default 0.5')
    parser.add_argument('--approximate', dest='approximate', default=-1, type=int,
                        help='k-hop shortest path distance. -1 means exact shortest path') # -1, 2

    parser.add_argument('--batch_size', dest='batch_size', default=8, type=int) # implemented via accumulating gradient
    parser.add_argument('--layer_num', dest='layer_num', default=2, type=int)
    parser.add_argument('--feature_dim', dest='feature_dim', default=32, type=int)
    parser.add_argument('--hidden_dim', dest='hidden_dim', default=32, type=int)
    parser.add_argument('--output_dim', dest='output_dim', default=32, type=int)
    parser.add_argument('--anchor_num', dest='anchor_num', default=64, type=int)
    parser.add_argument('--normalize_adj', dest='normalize_adj', action='store_true',
                        help='whether normalize_adj')

    parser.add_argument('--lr', dest='lr', default=1e-2, type=float)
    parser.add_argument('--epoch_num', dest='epoch_num', default=2001, type=int)
    parser.add_argument('--repeat_num', dest='repeat_num', default=2, type=int) # 10
    parser.add_argument('--epoch_log', dest='epoch_log', default=10, type=int)

    parser.set_defaults(gpu=True, task='link', model='GCN', dataset='All',
                        cache=False, rm_feature=False,
                        permute=True, feature_pre=True, dropout=True,
                        approximate=-1, normalize_adj=False)
    args = parser.parse_args()
    return args