Wraps a dataset so that PyTorch Lightning's validation step can be turned into a visualization step.
| 5 | |
| 6 | |
| 7 | class ValidationWrapper(Dataset): |
| 8 | """Wraps a dataset so that PyTorch Lightning's validation step can be turned into a |
| 9 | visualization step. |
| 10 | """ |
| 11 | |
| 12 | dataset: Dataset |
| 13 | dataset_iterator: Optional[Iterator] |
| 14 | length: int |
| 15 | |
| 16 | def __init__(self, dataset: Dataset, length: int) -> None: |
| 17 | super().__init__() |
| 18 | self.dataset = dataset |
| 19 | self.length = length |
| 20 | self.dataset_iterator = None |
| 21 | |
| 22 | def __len__(self): |
| 23 | return self.length |
| 24 | |
| 25 | def __getitem__(self, index: int): |
| 26 | if isinstance(self.dataset, IterableDataset): |
| 27 | if self.dataset_iterator is None: |
| 28 | self.dataset_iterator = iter(self.dataset) |
| 29 | return next(self.dataset_iterator) |
| 30 | |
| 31 | random_index = torch.randint(0, len(self.dataset), tuple()) |
| 32 | return self.dataset[random_index.item()] |