Splits input, a tensor with two or more dimensions, into multiple tensors vertically according to indices_or_sections. Each split is a view of input.
This is equivalent to calling torch.tensor_split(input, indices_or_sections, dim=0) (the split dimension is 0), except that if indices_or_sections is an integer it must evenly divide the split dimension or a runtime error will be thrown.
>>> t = torch.arange(16.0).reshape(4,4)
>>> t
tensor([[ 0., 1., 2., 3.],
[ 4., 5., 6., 7.],
[ 8., 9., 10., 11.],
[12., 13., 14., 15.]])
>>> torch.vsplit(t, 2)
(tensor([[0., 1., 2., 3.],
[4., 5., 6., 7.]]),
tensor([[ 8., 9., 10., 11.],
[12., 13., 14., 15.]]))
>>> torch.vsplit(t, [3, 6])
(tensor([[ 0., 1., 2., 3.],
[ 4., 5., 6., 7.],
[ 8., 9., 10., 11.]]),
tensor([[12., 13., 14., 15.]]),
tensor([], size=(0, 4)))
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