| 9 | |
| 10 | |
| 11 | class LitDataModule(pl.LightningDataModule): |
| 12 | |
| 13 | def __init__(self, batch_size=16): |
| 14 | super().__init__() |
| 15 | |
| 16 | self.batch_size = batch_size |
| 17 | |
| 18 | def setup(self, stage=None): |
| 19 | X_train = torch.rand(100, 1, 28, 28) |
| 20 | y_train = torch.randint(0, 10, size=(100,)) |
| 21 | X_valid = torch.rand(20, 1, 28, 28) |
| 22 | y_valid = torch.randint(0, 10, size=(20,)) |
| 23 | |
| 24 | self.train_ds = TensorDataset(X_train, y_train) |
| 25 | self.valid_ds = TensorDataset(X_valid, y_valid) |
| 26 | |
| 27 | def train_dataloader(self): |
| 28 | return DataLoader(self.train_ds, batch_size=self.batch_size, shuffle=True, num_workers=1) |
| 29 | |
| 30 | def val_dataloader(self): |
| 31 | return DataLoader(self.valid_ds, batch_size=self.batch_size, shuffle=False, num_workers=1) |
| 32 | |
| 33 | |
| 34 | class LitClassifier(pl.LightningModule): |