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torch.hsplit¶

torch.hsplit(input, indices_or_sections) List of Tensors

Splits input, a tensor with one or more dimensions, into multiple tensors horizontally according to indices_or_sections. Each split is a view of input.

If input is one dimensional this is equivalent to calling torch.tensor_split(input, indices_or_sections, dim=0) (the split dimension is zero), and if input has two or more dimensions it’s equivalent to calling torch.tensor_split(input, indices_or_sections, dim=1) (the split dimension is 1), 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.hsplit().

Parameters:
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.hsplit(t, 2)
(tensor([[ 0.,  1.],
[ 4.,  5.],
[ 8.,  9.],
[12., 13.]]),
tensor([[ 2.,  3.],
[ 6.,  7.],
[10., 11.],
[14., 15.]]))
>>> torch.hsplit(t, [3, 6])
(tensor([[ 0.,  1.,  2.],
[ 4.,  5.,  6.],
[ 8.,  9., 10.],
[12., 13., 14.]]),
tensor([[ 3.],
[ 7.],
[11.],
[15.]]),
tensor([], size=(4, 0)))


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