multiplication
  * **mat1** (*Tensor*) -- a dense matrix of shape *(m, k)* to be
    multiplied

  * **mat2** (*Tensor*) -- a dense matrix of shape *(k, n)* to be
    multiplied

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

  * **out** (*Tensor**, **optional*) -- output tensor. Ignored if
    *None*. Default: *None*.

Examples:
  >>> input = torch.eye(3, device='cuda').to_sparse_csr()
  >>> mat1 = torch.randn(3, 5, device='cuda')
  >>> mat2 = torch.randn(5, 3, device='cuda')
  >>> torch.sparse.sampled_addmm(input, mat1, mat2)
  tensor(crow_indices=tensor([0, 1, 2, 3]),
      col_indices=tensor([0, 1, 2]),
      values=tensor([ 0.2847, -0.7805, -0.1900]), device='cuda:0',
      size=(3, 3), nnz=3, layout=torch.sparse_csr)
  >>> torch.sparse.sampled_addmm(input, mat1, mat2).to_dense()
