(batch)
| 993 | def launch_data_process_task(model: DiffusionTrainingModule, dataset, cache_folder, num_shards: int = 16, skip_first_batches: int = 0, num_workers: int = 0, prefetch_factor: int = 4): |
| 994 | accelerator = Accelerator() |
| 995 | def collate_first_valid(batch): |
| 996 | for b in batch: |
| 997 | if b is not None: |
| 998 | return b |
| 999 | return {"__skip__": torch.tensor(True)} |
| 1000 | dataloader = torch.utils.data.DataLoader( |
| 1001 | dataset, |
| 1002 | # sampler=sampler, |
nothing calls this directly
no outgoing calls
no test coverage detected