Yes, DataLoader doesn’t have any conditions on the number of outputs of your Dataset as seen here:
class MyDataset(Dataset):
    def __init__(self):
        self.data = torch.randn(100, 1)
        
    def __getitem__(self, index):
        x = self.data[index]
        return x
    
    def __len__(self):
        return len(self.data)

dataset = MyDataset()
loader = DataLoader(
    dataset,
    batch_size=5,
    num_workers=2,
    shuffle=True
)

for data in loader:
    print(data.shape)