Load and preprocess a single sample. Returns: dict with keys: {{key_1}}: {{description}} — shape: {{shape}} {{key_2}}: {{description}} — shape: {{shape}}
(self, idx: int)
| 74 | return len(self.samples) |
| 75 | |
| 76 | def __getitem__(self, idx: int) -> Dict[str, torch.Tensor]: |
| 77 | """Load and preprocess a single sample. |
| 78 | |
| 79 | Returns: |
| 80 | dict with keys: |
| 81 | {{key_1}}: {{description}} — shape: {{shape}} |
| 82 | {{key_2}}: {{description}} — shape: {{shape}} |
| 83 | """ |
| 84 | # TODO: Implement sample loading |
| 85 | # sample = self.samples[idx] |
| 86 | # processed = self._preprocess(sample) |
| 87 | # return processed |
| 88 | raise NotImplementedError("Implement __getitem__ for your data format") |
| 89 | |
| 90 | |
| 91 | def build_dataloader( |
nothing calls this directly
no outgoing calls
no test coverage detected