quant/data/data_loaders.py [165:185]:
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            root=self.dataset_path,
            train=True,
            download=self.download,
            transform=transform_train,
        )

        train_loader = torch.utils.data.DataLoader(
            dataset_train,
            batch_size=self.train_batch_size,
            shuffle=True,
            num_workers=self.workers,
            pin_memory=True,
        )

        return train_loader

    def get_test_loader(self) -> DataLoader:
        """Get a PyTorch data loader for the test set."""
        transform_test = transforms.Compose(
            [transforms.ToTensor(), transforms.Normalize(self.mean_val, self.std_val)]
        )
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quant/data/data_loaders.py [246:266]:
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            root=self.dataset_path,
            train=True,
            download=self.download,
            transform=transform_train,
        )

        train_loader = torch.utils.data.DataLoader(
            dataset_train,
            batch_size=self.train_batch_size,
            shuffle=True,
            num_workers=self.workers,
            pin_memory=True,
        )

        return train_loader

    def get_test_loader(self) -> DataLoader:
        """Get a PyTorch data loader for the test set."""
        transform_test = transforms.Compose(
            [transforms.ToTensor(), transforms.Normalize(self.mean_val, self.std_val)]
        )
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