torch.diagflat — PyTorch 2.7 documentation (original) (raw)

torch.diagflat(input, offset=0) → Tensor¶

• If input is a vector (1-D tensor), then returns a 2-D square tensor with the elements of input as the diagonal.
• If input is a tensor with more than one dimension, then returns a 2-D tensor with diagonal elements equal to a flattened input.

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.
• offset (int, optional) – the diagonal to consider. Default: 0 (main diagonal).

Examples:

a = torch.randn(3) a tensor([-0.2956, -0.9068, 0.1695]) torch.diagflat(a) tensor([[-0.2956, 0.0000, 0.0000], [ 0.0000, -0.9068, 0.0000], [ 0.0000, 0.0000, 0.1695]]) torch.diagflat(a, 1) tensor([[ 0.0000, -0.2956, 0.0000, 0.0000], [ 0.0000, 0.0000, -0.9068, 0.0000], [ 0.0000, 0.0000, 0.0000, 0.1695], [ 0.0000, 0.0000, 0.0000, 0.0000]])

a = torch.randn(2, 2) a tensor([[ 0.2094, -0.3018], [-0.1516, 1.9342]]) torch.diagflat(a) tensor([[ 0.2094, 0.0000, 0.0000, 0.0000], [ 0.0000, -0.3018, 0.0000, 0.0000], [ 0.0000, 0.0000, -0.1516, 0.0000], [ 0.0000, 0.0000, 0.0000, 1.9342]])