Args: filename: a list of pickle files that stores the processed HAR data (after FFT) batch_size: batch size train: is for training? target: encoder method for the label: "hot": one-hot encoding, else int number
(filename, batch_size, train=True, target="logits")
| 41 | |
| 42 | |
| 43 | def dataloader_gen(filename, batch_size, train=True, target="logits"): |
| 44 | """ |
| 45 | Args: |
| 46 | filename: a list of pickle files that stores the processed HAR data (after FFT) |
| 47 | batch_size: batch size |
| 48 | train: is for training? |
| 49 | target: encoder method for the label: "hot": one-hot encoding, else int number |
| 50 | """ |
| 51 | dataset = data_loader.heter_data(filename, target=target) |
| 52 | dataloader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=train, num_workers=2, |
| 53 | drop_last=True) |
| 54 | return dataloader |
| 55 | |
| 56 | |
| 57 | def dataloader_gen2(filename, batch_size, train=True, target="logits"): |
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