def METHOD_NAME(x1, x2, out=None, where=None, **kwargs):
    """
    Multiply arguments element-wise.
    Parameters
    ----------
    x1, x2 : array_like
        Input arrays to be multiplied.
    out : Tensor, None, or tuple of Tensor and None, optional
        A location into which the result is stored. If provided, it must have
        a shape that the inputs broadcast to. If not provided or `None`,
        a freshly-allocated tensor is returned. A tuple (possible only as a
        keyword argument) must have length equal to the number of outputs.
    where : array_like, optional
        Values of True indicate to calculate the ufunc at that position, values
        of False indicate to leave the value in the output alone.
    **kwargs
    Returns
    -------
    y : Tensor
        The product of `x1` and `x2`, element-wise. Returns a scalar if
        both  `x1` and `x2` are scalars.
    Notes
    -----
    Equivalent to `x1` * `x2` in terms of array broadcasting.
    Examples
    --------
    >>> import mars.tensor as mt
    >>> mt.multiply(2.0, 4.0).execute()
    8.0
    >>> x1 = mt.arange(9.0).reshape((3, 3))
    >>> x2 = mt.arange(3.0)
    >>> mt.multiply(x1, x2).execute()
    array([[  0.,   1.,   4.],
           [  0.,   4.,  10.],
           [  0.,   7.,  16.]])
    """
    op = TensorMultiply(**kwargs)
    return op(x1, x2, out=out, where=where)