import numpy as np
from numpy import ndarray


def mae(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Mean Absoulte Error
    """
    return np.mean(np.abs(y_preds - y_actual))


def rmse(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Root Mean Squared Error
    """
    return np.sqrt(np.mean(np.power(y_preds - y_actual, 2)))

10344e02035c3e8d968d74e91b085c4a93ff5abd
<mask token>

<mask token>


def mae(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Mean Absoulte Error
    """
    return np.mean(np.abs(y_preds - y_actual))


<mask token>

<mask token>


def mae(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Mean Absoulte Error
    """
    return np.mean(np.abs(y_preds - y_actual))


def rmse(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Root Mean Squared Error
    """
    return np.sqrt(np.mean(np.power(y_preds - y_actual, 2)))

import numpy as np
from numpy import ndarray


def mae(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Mean Absoulte Error
    """
    return np.mean(np.abs(y_preds - y_actual))


def rmse(y_preds: ndarray, y_actual: ndarray) ->float:
    """
    Root Mean Squared Error
    """
    return np.sqrt(np.mean(np.power(y_preds - y_actual, 2)))
