What's the difference between passing numpy to Dataloader and converting to tensors and passing to TensorDataset then Dataloader?

As above. I tried passing numpy to Dataloader directly, it worked. How does this contrast with converting numpy to tensor and passing it to TensorDataset then pass the dataset to Dataloader?

How did you pass the numpy arrays to the DataLoader?
Did you get the expected batches for both, the data and target?

I would personally see it as a bit of a hack, if that’s working.
This simple example won’t throw an error, but doesn’t yield the expected results:

data, target = np.zeros((100, 1)), np.ones((100, 1))
loader_np = DataLoader((data, target), batch_size=1)
for x in loader_np: