Diagonal

torch_diagonal(self, outdim, dim1 = 1L, dim2 = 2L, offset = 0L)

Arguments

self

(Tensor) the input tensor. Must be at least 2-dimensional.

outdim

dimension name if self is a named tensor.

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.

offset

(int, optional) which diagonal to consider. Default: 0 (main diagonal).

diagonal(input, offset=0, dim1=0, dim2=1) -> Tensor

Returns a partial view of input with the its diagonal elements with respect to dim1 and dim2 appended as a dimension at the end of the shape.

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.

Applying torch_diag_embed to the output of this function with the same arguments yields a diagonal matrix with the diagonal entries of the input. However, torch_diag_embed has different default dimensions, so those need to be explicitly specified.

Examples

if (torch_is_installed()) { a = torch_randn(c(3, 3)) a torch_diagonal(a, offset = 0) torch_diagonal(a, offset = 1) x = torch_randn(c(2, 5, 4, 2)) torch_diagonal(x, offset=-1, dim1=1, dim2=2) }
#> torch_tensor #> (1,.,.) = #> 0.7483 #> 0.7505 #> #> (2,.,.) = #> -0.7690 #> 1.5591 #> #> (3,.,.) = #> 0.7832 #> 1.0473 #> #> (4,.,.) = #> -1.9936 #> 0.3438 #> [ CPUFloatType{4,2,1} ]