(self)
| 234 | pass |
| 235 | |
| 236 | def process(self): |
| 237 | file_path = os.path.join(self.raw_dir, self.raw_file_names[0]) |
| 238 | if not osp.exists(file_path): |
| 239 | try: |
| 240 | shutil.copy(f'data/{self.name}', file_path) |
| 241 | except: |
| 242 | raise ValueError('source file does not exist!') |
| 243 | |
| 244 | data = load_graphs(file_path)[0][0] |
| 245 | features = data.ndata['feature'] |
| 246 | labels = data.ndata['label'] |
| 247 | train_mask = data.ndata['train_masks'] |
| 248 | val_mask = data.ndata['val_masks'] |
| 249 | test_mask = data.ndata['test_masks'] |
| 250 | |
| 251 | data = Data(x=features, edge_index=torch.vstack( |
| 252 | data.edges()), y=labels) |
| 253 | data.tran_mask = train_mask |
| 254 | data.val_mask = val_mask |
| 255 | data.test_mask = test_mask |
| 256 | data = data if self.pre_transform is None else self.pre_transform(data) |
| 257 | self.save([data], self.processed_paths[0]) |
| 258 | |
| 259 | |
| 260 | class TextDataset(InMemoryDataset): |
nothing calls this directly
no outgoing calls
no test coverage detected