print train label num
@@ -80,8 +80,11 @@ if __name__ == '__main__':
dropout_ratio=args.dropout)
predictor = NodeClassifier(gnn, device=args.device)
+ train_label_num = int(data.n_nodes * args.train_data_ratio)
train_mask, valid_mask = generate_random_mask(
- data.n_nodes, int(data.n_nodes * args.train_data_ratio))
+ data.n_nodes, train_label_num)
+ print("train label: {}, validation label: {}".format(
+ train_label_num, data.n_nodes - train_label_num))
run_node_classification_train(
predictor, data, train_mask, valid_mask,
epoch=args.epoch, device=args.device)
