torch_lstsq function

Lstsq

Arguments

• self: (Tensor) the matrix $B$
• A: (Tensor) the $m$ by $n$ matrix $A$

Note

The case when \eqn{m < n} is not supported on the GPU.

lstsq(input, A, out=NULL) -> Tensor

Computes the solution to the least squares and least norm problems for a full rank matrix $A$ of size $(m \times n)$ and a matrix $B$ of size $(m \times k)$.

If $m \geq n$, torch_lstsq() solves the least-squares problem:

If $m < n$, torch_lstsq() solves the least-norm problem:

Returned tensor $X$ has shape $(\mbox{max}(m, n) \times k)$. The first $n$

rows of $X$ contains the solution. If $m \geq n$, the residual sum of squares for the solution in each column is given by the sum of squares of elements in the remaining $m - n$ rows of that column.