def sgc_objective(space):
if args.K:
model = get_model(args.model, features[0][0].size(1), labels.max().item()+1, args.hidden, args.decay, args.L, args.K, args.dropout, args.cuda)
else:
model = get_model(args.model, features.size(1), labels.max().item()+1, args.hidden, args.decay, args.L, args.K, args.dropout, args.cuda)
if args.model != 'GCN':
if args.K:
model, acc_val, _, _ = train_regression(model, features[0], labels[idx_train], features[1], labels[idx_val], features[2], labels[idx_test], idx_test, adj,
args.epochs, space['weight_decay'], args.lr, args.dropout)
else:
model, acc_val, _, _ = train_regression(model, features[idx_train], labels[idx_train], features[idx_val], labels[idx_val], features[idx_test], labels[idx_test], idx_test, adj,
args.epochs, space['weight_decay'], args.lr, args.dropout)
else:
model, acc_val, _ = train_gcn(model, features, labels, idx_train, idx_val, idx_test, adj,
args.epochs, args.weight_decay, args.lr, args.dropout)
print('weight decay: {:.2e} '.format(space['weight_decay']) + 'accuracy: {:.4f}'.format(acc_val))
return {'loss': -acc_val, 'status': STATUS_OK}
def sgc_objective(space):
model = get_model(args.model, features.size(1),
labels.max().item() + 1, args.hidden, args.dropout,
args.cuda)
model, acc_val, _ = train_regression(model, features[idx_train],
labels[idx_train], features[idx_val],
labels[idx_val], args.epochs,
space['weight_decay'], args.lr,
args.dropout)
print('weight decay: {:.2e} '.format(space['weight_decay']) +
'accuracy: {:.4f}'.format(acc_val))
return {'loss': -acc_val, 'status': STATUS_OK}