r"""
    Compute the root mean squared error between two SArrays.

    Parameters
    ----------
    targets : SArray[float or int]
        An Sarray of ground truth target values.

    predictions : SArray[float or int]
        The prediction that corresponds to each target value.
        This vector must have the same length as ``targets``.

    Returns
    -------
    out : float
        The RMSE between the two SArrays.

    See Also
    --------
    max_error

    Notes
    -----
    The root mean squared error between two vectors, x and y, is defined as:

    .. math::

        RMSE = \sqrt{\frac{1}{N} \sum_{i=1}^N (x_i - y_i)^2}

    References
    ----------
    - `Wikipedia - root-mean-square deviation
      <http://en.wikipedia.org/wiki/Root-mean-square_deviation>`_

    Examples
    --------
    >>> targets = turicreate.SArray([3.14, 0.1, 50, -2.5])
    >>> predictions = turicreate.SArray([3.1, 0.5, 50.3, -5])

    >>> turicreate.evaluation.rmse(targets, predictions)
    1.2749117616525465

def rmse(targets, predictions):
    r"""
    Compute the root mean squared error between two SArrays.

    Parameters
    ----------
    targets : SArray[float or int]
        An Sarray of ground truth target values.

    predictions : SArray[float or int]
        The prediction that corresponds to each target value.
        This vector must have the same length as ``targets``.

    Returns
    -------
    out : float
        The RMSE between the two SArrays.

    See Also
    --------
    max_error

    Notes
    -----
    The root mean squared error between two vectors, x and y, is defined as:

    .. math::

        RMSE = \sqrt{\frac{1}{N} \sum_{i=1}^N (x_i - y_i)^2}

    References
    ----------
    - `Wikipedia - root-mean-square deviation
      <http://en.wikipedia.org/wiki/Root-mean-square_deviation>`_

    Examples
    --------
    >>> targets = turicreate.SArray([3.14, 0.1, 50, -2.5])
    >>> predictions = turicreate.SArray([3.1, 0.5, 50.3, -5])

    >>> turicreate.evaluation.rmse(targets, predictions)
    1.2749117616525465
    """

    _supervised_evaluation_error_checking(targets, predictions)
    return _turicreate.extensions._supervised_streaming_evaluator(targets,
                                       predictions, "rmse", {})