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 toindices_or_sections
. Each split is a view ofinput
.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 ifinput
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 ifindices_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:
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.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)))