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

Arguments

self (Tensor) vector to be added (Tensor) matrix to be multiplied (Tensor) vector to be multiplied (Number, optional) multiplier for input ($$\beta$$) (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))
#> [ CPUFloatType{2} ]