torch.addmv
torch.addmv(input, mat, vec, *, beta=1, alpha=1, out=None) -> 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.
  \text{out} = \beta\ \text{input} + \alpha\ (\text{mat}
  \mathbin{@} \text{vec})

If "beta" is 0, then "input" will be ignored, and nan and inf
   in it will not be propagated.
For inputs of type FloatTensor or DoubleTensor, arguments
   "beta" and "alpha" must be real numbers, otherwise they should be
   integers.
Parameters:
      * input (Tensor) -- vector to be added
  * **mat** (*Tensor*) -- matrix to be matrix multiplied
