Given a 4-dim tensor X
X = torch.tensor([[[[0, 2]], [[1, 3]]]])
of shape
 torch.Size([1, 2, 1, 2])
and stack, which stacks along a new dimension (here the last)
Y = torch.stack((X[:, :1], X[:, 1:]), dim= -1)
results in a shape
Y.shape torch.Size([1, 1, 1, 2, 2])
but why are the elements arranged in this way?
Y tensor([[[[[0, 1],
           [2, 3]]]]])

I am thinking about explanations as to why this specific order results, but cant seem to find one