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])
