(self, opt, is_for_train)
| 12 | >>> dataloader = dataset.load_data() |
| 13 | """ |
| 14 | def __init__(self, opt, is_for_train): |
| 15 | self.opt = opt |
| 16 | if opt.dataset_mode.lower() == 'iharmony4': |
| 17 | self.dataset = Iharmony4Dataset(opt, is_for_train) |
| 18 | print("dataset [%s] was created" % type(self.dataset).__name__) |
| 19 | else: |
| 20 | raise ValueError(opt.dataset_mode, "not implmented.") |
| 21 | |
| 22 | self.dataloader = torch.utils.data.DataLoader( |
| 23 | self.dataset, |
| 24 | batch_size=opt.batch_size, |
| 25 | shuffle=is_for_train, |
| 26 | num_workers=int(opt.num_threads), |
| 27 | drop_last=False) |
| 28 | |
| 29 | def load_data(self): |
| 30 | return self.dataloader |
nothing calls this directly
no test coverage detected