def METHOD_NAME(input, mat1, mat2, alpha=1, beta=1):
    """addmm(beta=1, input, alpha=1, mat1, mat2, out=None) -> Tensor
    Performs a matrix multiplication of the matrices :attr:`mat1` and :attr:`mat2`.
    The matrix :attr:`input` is added to the final result.
    If :attr:`mat1` is a :math:`(n \\times m)` tensor, :attr:`mat2` is a
    :math:`(m \\times p)` tensor, then :attr:`input` must be
    broadcastable with a :math:`(n \\times p)` tensor
    and :attr:`out` will be a :math:`(n \\times p)` tensor.
    :attr:`alpha` and :attr:`beta` are scaling factors on matrix-vector product between
    :attr:`mat1` and :attr:`mat2` and the added matrix :attr:`input` respectively.
    .. math::
        \\text{out} = \\beta\\ \\text{input} + \\alpha\\ (\\text{mat1}_i \\mathbin{@} \\text{mat2}_i)
    For inputs of type `float` or `double`, arguments :attr:`beta` and
    :attr:`alpha` must be real numbers, otherwise they should be integers.
    Args:
        beta (Number, optional): multiplier for :attr:`input` (:math:`\\beta`)
        input (Tensor): matrix to be added
        alpha (Number, optional): multiplier for :math:`mat1 @ mat2` (:math:`\\alpha`)
        mat1 (Tensor): the first matrix to be multiplied
        mat2 (Tensor): the second matrix to be multiplied
        out (Tensor, optional): the output tensor.
    For example:
        >>> import numpy as np
        >>> import oneflow as flow
        >>> input = flow.tensor(np.array([[1,2,4],[5,11,9.1]]))
        >>> mat1 = flow.tensor(np.array([[7.3,1.9,7.3],[10.2,1,5.5]])) 
        >>> mat2 = flow.tensor(np.array([[7.3,1.9,7.3],[10.2,1,5.5],[3.7,2.2,8.1]])) 
        >>> output = flow.addmm(input, mat1, mat2)
        >>> output
        tensor([[100.6800,  33.8300, 126.8700],
                [110.0100,  43.4800, 133.6100]], dtype=oneflow.float64)
        >>> output.shape
        oneflow.Size([2, 3])
        >>> input2 = flow.tensor(np.array([1.7]))
        >>> mat1 = flow.tensor(np.array([[1,2],[5,9.1],[7.7,1.4]]))
        >>> mat2 = flow.tensor(np.array([[1,2,3.7],[5,9.1,6.8]]))
        >>> output2 = flow.addmm(input2, mat1, mat2, alpha=1, beta=2)
        >>> output2
        tensor([[14.4000, 23.6000, 20.7000],
                [53.9000, 96.2100, 83.7800],
                [18.1000, 31.5400, 41.4100]], dtype=oneflow.float64)
        >>> output2.shape
        oneflow.Size([3, 3])
    """
    return addmm(input, mat1, mat2, alpha, beta)