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# torch.addcmul

torch.addcmul(input, tensor1, tensor2, *, value=1, out=None) → Tensor

  Performs the element-wise multiplication of `tensor1` by `tensor2`, multiplies the result by the scalar `value` and adds it to `input`.

  out i=input i+value×tensor1 i×tensor2 i\text{out}_i = \text{input}_i + \text{value} \times \text{tensor1}_i \times \text{tensor2}_i out i​=input i​+value×tensor1 i​×tensor2 i​

  The shapes of `tensor`, `tensor1`, and `tensor2` must be broadcastable.

  For inputs of type FloatTensor or DoubleTensor, `value` must be a real number, otherwise an integer.

  Parameters:

    - input (Tensor) – the tensor to be added

    - tensor1 (Tensor) – the tensor to be multiplied

    - tensor2 (Tensor) – the tensor to be multiplied

  Keyword Arguments:

    - value (Number, optional) – multiplier for t e n s o r 1.∗t e n s o r 2 tensor1 .* tensor2 t e n sor 1.∗t e n sor 2

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

  Example:

      >>> t = torch.randn(1, 3)
      >>> t1 = torch.randn(3, 1)
      >>> t2 = torch.randn(1, 3)
      >>> torch.addcmul(t, t1, t2, value=0.1)
      tensor([[-0.8635, -0.6391,  1.6174],
              [-0.7617, -0.5879,  1.7388],
              [-0.8353, -0.6249,  1.6511]])

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