torch_addmm function

Addmm

Addmm

torch_addmm(self, mat1, mat2, beta = 1L, alpha = 1L)

Arguments

  • self: (Tensor) matrix to be added
  • mat1: (Tensor) the first matrix to be multiplied
  • mat2: (Tensor) the second matrix to be multiplied
  • beta: (Number, optional) multiplier for input (β\beta)
  • alpha: (Number, optional) multiplier for mat1@mat2mat1 @ mat2 (α\alpha)

addmm(input, mat1, mat2, *, beta=1, alpha=1, out=NULL) -> Tensor

Performs a matrix multiplication of the matrices mat1 and mat2. The matrix input is added to the final result.

If mat1 is a (n×m)(n \times m) tensor, mat2 is a (m×p)(m \times p) tensor, then input must be broadcastable with a (n×p)(n \times p) tensor and out will be a (n×p)(n \times p) tensor.

alpha and beta are scaling factors on matrix-vector product between mat1 and mat2 and the added matrix input respectively.

\mboxout=β \mboxinput+α (\mboxmat1i@\mboxmat2i) \mbox{out} = \beta\ \mbox{input} + \alpha\ (\mbox{mat1}_i \mathbin{@} \mbox{mat2}_i)

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, 3)) mat1 = torch_randn(c(2, 3)) mat2 = torch_randn(c(3, 3)) torch_addmm(M, mat1, mat2) }
  • Maintainer: Daniel Falbel
  • License: MIT + file LICENSE
  • Last published: 2025-02-14