torch_qr {torch} | R Documentation |
Qr
Description
Qr
Usage
torch_qr(self, some = TRUE)
Arguments
self |
(Tensor) the input tensor of size |
some |
(bool, optional) Set to |
qr(input, some=TRUE, out=NULL) -> (Tensor, Tensor)
Computes the QR decomposition of a matrix or a batch of matrices input
,
and returns a namedtuple (Q, R) of tensors such that
with
being an orthogonal matrix or batch of orthogonal matrices and
being an upper triangular matrix or batch of upper triangular matrices.
If some
is TRUE
, then this function returns the thin (reduced) QR factorization.
Otherwise, if some
is FALSE
, this function returns the complete QR factorization.
Note
precision may be lost if the magnitudes of the elements of input
are large
While it should always give you a valid decomposition, it may not give you the same one across platforms - it will depend on your LAPACK implementation.
Examples
if (torch_is_installed()) {
a = torch_tensor(matrix(c(12., -51, 4, 6, 167, -68, -4, 24, -41), ncol = 3, byrow = TRUE))
out = torch_qr(a)
q = out[[1]]
r = out[[2]]
torch_mm(q, r)$round()
torch_mm(q$t(), q)$round()
}