Pinverse

## Usage

torch_pinverse(self, rcond = 1e-15)

## Arguments

self

(Tensor) The input tensor of size $$(*, m, n)$$ where $$*$$ is zero or more batch dimensions

rcond

(float) A floating point value to determine the cutoff for small singular values. Default: 1e-15

## Note

This method is implemented using the Singular Value Decomposition.

The pseudo-inverse is not necessarily a continuous function in the elements of the matrix [1]_.
Therefore, derivatives are not always existent, and exist for a constant rank only [2]_.
However, this method is backprop-able due to the implementation by using SVD results, and
could be unstable. Double-backward will also be unstable due to the usage of SVD internally.
See ~torch.svd for more details.

## pinverse(input, rcond=1e-15) -> Tensor

Calculates the pseudo-inverse (also known as the Moore-Penrose inverse) of a 2D tensor. Please look at Moore-Penrose inverse_ for more details

## Examples

if (torch_is_installed()) {

input = torch_randn(c(3, 5))
input
torch_pinverse(input)
# Batched pinverse example
a = torch_randn(c(2,6,3))
b = torch_pinverse(a)
torch_matmul(b, a)
}
#> torch_tensor
#> (1,.,.) =
#>   1.0000e+00 -4.2841e-08 -8.9407e-08
#>  -8.3819e-09  1.0000e+00 -1.3411e-07
#>  -1.0245e-07 -9.6858e-08  1.0000e+00
#>
#> (2,.,.) =
#>   1.0000e+00 -3.4459e-07  9.6858e-08
#>  -1.7881e-07  1.0000e+00 -2.4587e-07
#>   1.4901e-07  1.7043e-07  1.0000e+00
#> [ CPUFloatType{2,3,3} ]