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.

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

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 multiplied

• vec (Tensor) – vector to be multiplied

• beta (Number, optional) – multiplier for input ($\beta$ )

• alpha (Number, optional) – multiplier for $mat @ vec$ ($\alpha$ )

• out (Tensor, optional) – the output tensor.

Example:

>>> M = torch.randn(2)
>>> mat = torch.randn(2, 3)
>>> vec = torch.randn(3)
>>> torch.addmv(M, mat, vec)
tensor([-0.3768, -5.5565])