def process(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) torch.save(self.collate([data]), self.processed_paths[0])
def process(self): data = read_planetoid_data(self.raw_dir, 'nell.0.001') data = data if self.pre_transform is None else self.pre_transform(data) torch.save(self.collate([data]), self.processed_paths[0])