code: def sle(actual, predicted):
      
      return (np.power(np.log(np.array(actual)+1) - 
              np.log(np.array(predicted)+1), 2))
docs: Computes the squared log error.
  
      This function computes the squared log error between two numbers,
      or for element between a pair of lists or numpy arrays.
  
      Parameters
      ----------
      actual : int, float, list of numbers, numpy array
               The ground truth value
      predicted : same type as actual
                  The predicted value
  
      Returns
      -------
      score : double or list of doubles
              The squared log error between actual and predicted