code: def _construct_losses(self, data, predictions, ensemble_prediction):
          
  
          losses = []
          losses.append(self.loss_type(data, ensemble_prediction).sum()/data.shape[0])
          for model in range(len(self.model_list)):
              losses.append(self.loss_type(data, predictions[:,model]).sum()/data.shape[0])
          return losses
docs: Construct losses for the ensemble and each constitute model
          
          Parameters
          ----------
          data: np.ndarray
              The univariate time series
  
          predictions : np.ndarray
              The predictions of each constitute model
  
          ensemble_prediction : np.ndarray
              The prediction of the ensemble model
  
          Returns
          ----------
          - np.ndarray of the losses for each model