torch.vsplit

torch.vsplit(input, indices_or_sections) → List of Tensors

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.

This function is based on NumPy’s numpy.vsplit().

Parameters:

• input (Tensor) – tensor to split.

• indices_or_sections (int or list or tuple of ints) – See argument in torch.tensor_split().

Example::

>>> 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)))