Solved by sparseinference in post #2 
              
              
                from itertools import permutations
torch.stack([torch.cat(rows,0) for rows in permutations(T, 2)])

results in: 
tensor([[0, 1, 2, 3],
        [0, 1, 4, 5],
        [2, 3, 0, 1],
        [2, 3, 4, 5],
        [4, 5, 0, 1],
        [4, 5, 2, 3]])