deeppavlov/metrics/log_loss.py
def sk_log_loss(y_true: Union[List[List[float]], List[List[int]], np.ndarray],
                y_predicted: Union[List[List[float]], List[List[int]], np.ndarray]) -> float:
    """
    Calculates log loss.

    Args:
        y_true: list or array of true values
        y_predicted: list or array of predicted values

    Returns:
        Log loss
    """
    return log_loss(y_true, y_predicted)
def sk_log_loss(y_true: Union[List[List[float]], List[List[int]], np.ndarray],
                y_predicted: Union[List[List[float]], List[List[int]], np.ndarray]) -> float:
    return log_loss(y_true, y_predicted)
def sk_log_loss ( y_true : Union [ List [ List [ float ] ] , List [ List [ int ] ] , np . ndarray ] , y_predicted : Union [ List [ List [ float ] ] , List [ List [ int ] ] , np . ndarray ] ) -> float : return log_loss ( y_true , y_predicted )
Calculates log loss.

    Args:
        y_true: list or array of true values
        y_predicted: list or array of predicted values

    Returns:
        Log loss
Calculates log loss .