# Diag_embed

Source:`R/gen-namespace-docs.R`

, `R/gen-namespace-examples.R`

, `R/gen-namespace.R`

`torch_diag_embed.Rd`

Diag_embed

## Arguments

- self
(Tensor) the input tensor. Must be at least 1-dimensional.

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

- dim1
(int, optional) first dimension with respect to which to take diagonal. Default: -2.

- dim2
(int, optional) second dimension with respect to which to take diagonal. Default: -1.

## diag_embed(input, offset=0, dim1=-2, dim2=-1) -> Tensor

Creates a tensor whose diagonals of certain 2D planes (specified by
`dim1`

and `dim2`

) are filled by `input`

.
To facilitate creating batched diagonal matrices, the 2D planes formed by
the last two dimensions of the returned tensor are chosen by default.

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.

The size of the new matrix will be calculated to make the specified diagonal
of the size of the last input dimension.
Note that for `offset`

other than \(0\), the order of `dim1`

and `dim2`

matters. Exchanging them is equivalent to changing the
sign of `offset`

.

Applying `torch_diagonal`

to the output of this function with
the same arguments yields a matrix identical to input. However,
`torch_diagonal`

has different default dimensions, so those
need to be explicitly specified.

## Examples

```
if (torch_is_installed()) {
a = torch_randn(c(2, 3))
torch_diag_embed(a)
torch_diag_embed(a, offset=1, dim1=1, dim2=3)
}
#> torch_tensor
#> (1,.,.) =
#> 0.0000 -0.6389 0.0000 0.0000
#> 0.0000 0.8825 0.0000 0.0000
#>
#> (2,.,.) =
#> 0.0000 0.0000 0.6883 0.0000
#> 0.0000 0.0000 0.1435 0.0000
#>
#> (3,.,.) =
#> 0.0000 0.0000 0.0000 1.5566
#> 0.0000 0.0000 0.0000 -0.4684
#>
#> (4,.,.) =
#> 0 0 0 0
#> 0 0 0 0
#> [ CPUFloatType{4,2,4} ]
```