You can think of TensorDataset as combining all your tensors as a single tensor. And then you can index them collectively,
x = torch.ones(10, 10)
y = torch.zeros(10, 5)
data = torch.utils.data.TensorDataset(x, y)
data[0]

(tensor([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]),
 tensor([0., 0., 0., 0., 0.]))