Pinverse

torch_pinverse(self, rcond = 0)

## Arguments

self (Tensor) The input tensor of size $$(*, m, n)$$ where $$*$$ is zero or more batch dimensions (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 -7.4506e-09  1.8626e-09
#>  -1.1176e-08  1.0000e+00 -1.3039e-08
#>  -1.6391e-07  1.4901e-08  1.0000e+00
#>
#> (2,.,.) =
#>   1.0000e+00  4.1723e-07 -1.7881e-07
#>  -1.7881e-07  1.0000e+00 -1.4901e-07
#>   2.0862e-07 -2.0117e-07  1.0000e+00
#> [ CPUFloatType{2,3,3} ]