"input" is sparse the result will have the same layout and if "out"
   is provided it must have the same layout as "input".
Warning:
 Sparse support is a beta feature and some layout(s)/dtype/device
 combinations may not be supported, or may not have autograd
 support. If you notice missing functionality please open a
 feature request.

This operator supports TensorFloat32.
On certain ROCm devices, when using float16 inputs this module will
   use different precision for backward.
Parameters:
      * input (Tensor) -- matrix to be added
  * **mat1** (*Tensor*) -- the first matrix to be matrix
    multiplied

  * **mat2** (*Tensor*) -- the second matrix to be matrix
    multiplied

Keyword Arguments:
      * beta (Number, optional) -- multiplier for "input"
        (\beta)
  * **alpha** (*Number**, **optional*) -- multiplier for mat1 @
    mat2 (\alpha)

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

Example: