Returns element-wise division of the input arrays with broadcasting.

    Equivalent to ``lhs / rhs`` and ``mx.nd.broadcast_div(lhs, rhs)``.

    .. note::

       If the corresponding dimensions of two arrays have the same size or one of them has size 1,
       then the arrays are broadcastable to a common shape.

    Parameters
    ----------
    lhs : scalar or mxnet.ndarray.array
        First array in division.
    rhs : scalar or mxnet.ndarray.array
         Second array in division.
        The arrays to be divided. If ``lhs.shape != rhs.shape``, they must be
        broadcastable to a common shape.

    Returns
    -------
    NDArray
        The element-wise division of the input arrays.

    Examples
    --------
    >>> x = mx.nd.ones((2,3))*6
    >>> y = mx.nd.ones((2,1))*2
    >>> x.asnumpy()
    array([[ 6.,  6.,  6.],
           [ 6.,  6.,  6.]], dtype=float32)
    >>> y.asnumpy()
    array([[ 2.],
           [ 2.]], dtype=float32)
    >>> x/2
    <NDArray 2x3 @cpu(0)>
    >>> (x/3).asnumpy()
    array([[ 2.,  2.,  2.],
           [ 2.,  2.,  2.]], dtype=float32)
    >>> (x/y).asnumpy()
    array([[ 3.,  3.,  3.],
           [ 3.,  3.,  3.]], dtype=float32)
    >>> mx.nd.divide(x,y).asnumpy()
    array([[ 3.,  3.,  3.],
           [ 3.,  3.,  3.]], dtype=float32)

def divide(lhs, rhs):
    """Returns element-wise division of the input arrays with broadcasting.

    Equivalent to ``lhs / rhs`` and ``mx.nd.broadcast_div(lhs, rhs)``.

    .. note::

       If the corresponding dimensions of two arrays have the same size or one of them has size 1,
       then the arrays are broadcastable to a common shape.

    Parameters
    ----------
    lhs : scalar or mxnet.ndarray.array
        First array in division.
    rhs : scalar or mxnet.ndarray.array
         Second array in division.
        The arrays to be divided. If ``lhs.shape != rhs.shape``, they must be
        broadcastable to a common shape.

    Returns
    -------
    NDArray
        The element-wise division of the input arrays.

    Examples
    --------
    >>> x = mx.nd.ones((2,3))*6
    >>> y = mx.nd.ones((2,1))*2
    >>> x.asnumpy()
    array([[ 6.,  6.,  6.],
           [ 6.,  6.,  6.]], dtype=float32)
    >>> y.asnumpy()
    array([[ 2.],
           [ 2.]], dtype=float32)
    >>> x/2
    <NDArray 2x3 @cpu(0)>
    >>> (x/3).asnumpy()
    array([[ 2.,  2.,  2.],
           [ 2.,  2.,  2.]], dtype=float32)
    >>> (x/y).asnumpy()
    array([[ 3.,  3.,  3.],
           [ 3.,  3.,  3.]], dtype=float32)
    >>> mx.nd.divide(x,y).asnumpy()
    array([[ 3.,  3.,  3.],
           [ 3.,  3.,  3.]], dtype=float32)
    """
    # pylint: disable= no-member, protected-access
    return _ufunc_helper(
        lhs,
        rhs,
        op.broadcast_div,
        operator.truediv,
        _internal._div_scalar,
        _internal._rdiv_scalar)