torch.addmv — PyTorch 2.7 documentation (original) (raw)

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×m)(n \times m) tensor, vec is a 1-D tensor of size m, then input must bebroadcastable with a 1-D tensor of size n andout will be 1-D tensor of size n.

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

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

If beta is 0, then the content of input will be ignored, and nan and inf in it will not be propagated.

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

Parameters

• input (Tensor) – vector to be added
• mat (Tensor) – matrix to be matrix multiplied
• vec (Tensor) – vector to be matrix multiplied

Keyword Arguments

• beta (Number , optional) – multiplier for input (β\beta)
• alpha (Number , optional) – multiplier for mat@vecmat @ vec (α\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])