I’m following this example on doc 1
In [42]: x = torch.tensor([1,2,3])


In [45]: x.repeat(4,2) 
Out[45]: tensor([[1, 2, 3, 1, 2, 3],
        [1, 2, 3, 1, 2, 3],
        [1, 2, 3, 1, 2, 3],
        [1, 2, 3, 1, 2, 3]])

In [46]: x.repeat(4,2).shape 
Out[46]: torch.Size([4, 6])

So far, so good.
But why does repeating just 1 time on 3rd dimension expand 3rd dim to 3 (not 1)?
[On the doc]

>>> x.repeat(4, 2, 1).size()
torch.Size([4, 2, 3])

Double checking.
In [43]: x.repeat(4,2,1)
Out[43]:
tensor([[[1, 2, 3],
         [1, 2, 3]],

        [[1, 2, 3],
         [1, 2, 3]],

        [[1, 2, 3],
         [1, 2, 3]],

        [[1, 2, 3],
         [1, 2, 3]]])

Why does it behave this way?