torch: torch_qr – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

torch_qr

Description

Usage

torch_qr(self, some = TRUE)

Arguments

`self`	(Tensor) the input tensor of size (, m, n)* where `` is zero or more batch dimensions consisting of matrices of dimension m \times n*.
`some`	(bool, optional) Set to `TRUE` for reduced QR decomposition and `FALSE` for complete QR decomposition.

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 \mbox{input} = Q R with Q being an orthogonal matrix or batch of orthogonal matrices and R 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()
}

torch

Tensors and Neural Networks with 'GPU' Acceleration

v0.3.0

MIT + file LICENSE

Authors

Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], Christophe Regouby [ctb], Krzysztof Joachimiak [ctb], RStudio [cph]

Initial release