torch_addmv: Addmv

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Addmv

Description

Addmv

Usage

torch_addmv(self, mat, vec, beta = 1L, alpha = 1L)

Arguments

self	(Tensor) vector to be added
mat	(Tensor) matrix to be multiplied
vec	(Tensor) vector to be multiplied
beta	(Number, optional) multiplier for input (\beta)
alpha	(Number, optional) multiplier for mat @ vec (\alpha)

addmv(input, mat, vec, *, beta=1, alpha=1, out=NULL) -> Tensor

Performs a matrix-vector product of the matrix mat and the vector vec. The vector input is added to the final result.

If mat is a (n \times m) tensor, vec is a 1-D tensor of size m, then input must be broadcastable with a 1-D tensor of size n and out will be 1-D tensor of size n.

alpha and beta are scaling factors on matrix-vector product between mat and vec and the added tensor input respectively.

\mbox{out} = \beta\ \mbox{input} + \alpha\ (\mbox{mat} \mathbin{@} \mbox{vec})

For inputs of type FloatTensor or DoubleTensor, arguments beta and alpha must be real numbers, otherwise they should be integers

Examples

if (torch_is_installed()) {

M = torch_randn(c(2))
mat = torch_randn(c(2, 3))
vec = torch_randn(c(3))
torch_addmv(M, mat, vec)
}

torch documentation built on June 7, 2023, 6:19 p.m.