              output_shapes = [K.int_shape(output)[1:] for output in side_output]
              output_types = ["mask" if shape[-1] == 1 else "face" for shape in output_shapes]
              logger.debug("side: %s, output names: %s, output_shapes: %s, output_types: %s",
                           side, output_names, output_shapes, output_types)
              retval.extend(["{}_{}{}".format(name, side,
                                              "" if output_types.count(name) == 1
                                              else "_{}".format(idx))
                             for idx, name in enumerate(output_types)])
          logger.debug(retval)
          return retval
  
      def _get_loss_functions(self):
          """ Set the loss functions.
  
          Returns
 
</s> remove         retval = []
 </s> add  </s> remove     def _get_loss_functions(self):
 </s> add     def _get_loss_functions(self, output_names): </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 
        Returns
        -------
        list
            A list of names for the losses to be applied to the model
 </s> add  </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
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
              output_shapes = [K.int_shape(output)[1:] for output in side_output]
              output_types = ["mask" if shape[-1] == 1 else "face" for shape in output_shapes]
              logger.debug("side: %s, output names: %s, output_shapes: %s, output_types: %s",
                           side, output_names, output_shapes, output_types)
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
            self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else "_{}".format(idx))
                                for idx, name in enumerate(output_types)])
        logger.debug(self._names)
  
      def _get_loss_functions(self):
          """ Set the loss functions.
  
          Returns
keep keep keep keep replace replace replace replace replace replace keep keep keep keep keep
 training - Use explicit loss dictionaries to map to outputs 
plugins/train/model/_base.py