(self, skip_first_n_batches=None)
| 1340 | return ret |
| 1341 | |
| 1342 | def _create_dataloader(self, skip_first_n_batches=None): |
| 1343 | if skip_first_n_batches is not None: |
| 1344 | sampler = SkipFirstNSampler(skip_first_n_batches, len(self.dataset)) |
| 1345 | else: |
| 1346 | sampler = None |
| 1347 | self.dataloader = torch.utils.data.DataLoader( |
| 1348 | self.dataset, |
| 1349 | pin_memory=False, |
| 1350 | batch_size=None, |
| 1351 | sampler=sampler, |
| 1352 | num_workers=self.num_dataloader_workers, |
| 1353 | persistent_workers=(self.num_dataloader_workers > 0), |
| 1354 | prefetch_factor=2 if self.num_dataloader_workers > 0 else None, |
| 1355 | ) |
| 1356 | |
| 1357 | def _pull_batches_from_dataloader(self): |
| 1358 | for batch in self.dataloader: |
no test coverage detected