torch.diagonal_scatter¶
-
torch.
diagonal_scatter
(input, src, offset=0, dim1=0, dim2=1) → Tensor¶ Embeds the values of the
src
tensor intoinput
along the diagonal elements ofinput
, with respect todim1
anddim2
.This function returns a tensor with fresh storage; it does not return a view.
The argument
offset
controls which diagonal to consider:If
offset
= 0, it is the main diagonal.If
offset
> 0, it is above the main diagonal.If
offset
< 0, it is below the main diagonal.
- Parameters
input (Tensor) – the input tensor. Must be at least 2-dimensional.
src (Tensor) – the tensor to embed into
input
.offset (int, optional) – which diagonal to consider. Default: 0 (main diagonal).
dim1 (int, optional) – first dimension with respect to which to take diagonal. Default: 0.
dim2 (int, optional) – second dimension with respect to which to take diagonal. Default: 1.
Note
src
must be of the proper size in order to be embedded intoinput
. Specifically, it should have the same shape astorch.diagonal(input, offset, dim1, dim2)
Examples:
>>> a = torch.zeros(3, 3) >>> a tensor([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.]]) >>> torch.diagonal_scatter(a, torch.ones(3), 0) tensor([[1., 0., 0.], [0., 1., 0.], [0., 0., 1.]]) >>> torch.diagonal_scatter(a, torch.ones(2), 1) tensor([[0., 1., 0.], [0., 0., 1.], [0., 0., 0.]])