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Showing content from https://docs.pytorch.org/docs/stable/generated/torch.diagonal_scatter.html below:

torch.diagonal_scatter — PyTorch 2.7 documentation

torch.diagonal_scatter(input, src, offset=0, dim1=0, dim2=1) → Tensor¶

Embeds the values of the src tensor into input along the diagonal elements of input, with respect to dim1 and dim2.

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 into input. Specifically, it should have the same shape as torch.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.]])

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