torch.dsplit#

torch.dsplit(input,indices_or_sections)→ListofTensors#

Splitsinput, a tensor with three or more dimensions, into multiple tensorsdepthwise according toindices_or_sections. Each split is a view ofinput.

This is equivalent to calling torch.tensor_split(input, indices_or_sections, dim=2)(the split dimension is 2), except that ifindices_or_sections is an integerit must evenly divide the split dimension or a runtime error will be thrown.

This function is based on NumPy’snumpy.dsplit().

Parameters

• input (Tensor) – tensor to split.

• indices_or_sections (int orlist ortuple ofints) – See argument intorch.tensor_split().

Example:

>>>t=torch.arange(16.0).reshape(2,2,4)>>>ttensor([[[ 0.,  1.,  2.,  3.],         [ 4.,  5.,  6.,  7.]],        [[ 8.,  9., 10., 11.],         [12., 13., 14., 15.]]])>>>torch.dsplit(t,2)(tensor([[[ 0.,  1.],        [ 4.,  5.]],       [[ 8.,  9.],        [12., 13.]]]), tensor([[[ 2.,  3.],          [ 6.,  7.]],         [[10., 11.],          [14., 15.]]]))>>>torch.dsplit(t,[3,6])(tensor([[[ 0.,  1.,  2.],          [ 4.,  5.,  6.]],         [[ 8.,  9., 10.],          [12., 13., 14.]]]), tensor([[[ 3.],          [ 7.]],         [[11.],          [15.]]]), tensor([], size=(2, 2, 0)))