def METHOD_NAME(self):
    data = read_planetoid_data(self.raw_dir, self.name)
    if self.split == 'geom-gcn':
        train_masks, val_masks, test_masks = [], [], []
        for i in range(10):
            name = f'{self.name.lower()}_split_0.6_0.2_{i}.npz'
            splits = np.load(osp.join(self.raw_dir, name))
            train_masks.append(torch.from_numpy(splits['train_mask']))
            val_masks.append(torch.from_numpy(splits['val_mask']))
            test_masks.append(torch.from_numpy(splits['test_mask']))
        data.train_mask = torch.stack(train_masks, dim=1)
        data.val_mask = torch.stack(val_masks, dim=1)
        data.test_mask = torch.stack(test_masks, dim=1)
    data = data if self.pre_transform is None else self.pre_transform(data)
    self.save([data], self.processed_paths[0])