          mask_loss = self._loss_dict[self._config["mask_loss_function"]]
          loss_funcs = []
          for name in self._names:
              if name.startswith("mask"):
                  loss_funcs.append(mask_loss)
              elif self._config["penalized_mask_loss"]:
                  loss_funcs.append(losses.PenalizedLoss(selected_loss))
              else:
                  loss_funcs.append(selected_loss)
              logger.debug("%s: %s", name, loss_funcs[-1])
 
</s> remove                 loss_funcs.append(losses.PenalizedLoss(selected_loss))
 </s> add                 loss_func = losses.PenalizedLoss(selected_loss)
            else:
                loss_func = selected_loss
            logger.debug("%s: (output_name: '%s', function: %s)", name, output_name, loss_func)
            if get_backend() == "amd":
                self._funcs[output_name] = loss_func </s> remove         mask_loss = self._loss_dict[self._config["mask_loss_function"]]
        loss_funcs = []
        for name in self._names:
 </s> add         for name, output_name in zip(self._names, output_names): </s> remove                 loss_funcs.append(selected_loss)
            logger.debug("%s: %s", name, loss_funcs[-1])
        logger.debug(loss_funcs)
        return loss_funcs
 </s> add                 self._funcs.setdefault(output_name, []).append(loss_func)
        logger.debug(self._funcs) </s> remove         Returns
        -------
        list
            A list of loss functions to apply to the model
 </s> add         Adds the loss functions to the :attr:`functions` dictionary.

        Parameters
        ----------
        output_names: list
            The output names from the model </s> remove         retval = []
 </s> add 
                loss_func = self._loss_dict[self._config["mask_loss_function"]]
          mask_loss = self._loss_dict[self._config["mask_loss_function"]]
          loss_funcs = []
          for name in self._names:
              if name.startswith("mask"):
                loss_func = self._loss_dict[self._config["mask_loss_function"]]
              elif self._config["penalized_mask_loss"]:
                  loss_funcs.append(losses.PenalizedLoss(selected_loss))
              else:
                  loss_funcs.append(selected_loss)
              logger.debug("%s: %s", name, loss_funcs[-1])
keep keep keep keep replace keep keep keep keep keep
 training - Use explicit loss dictionaries to map to outputs 
plugins/train/model/_base.py