          selected_loss = self._loss_dict[self._config.get("loss_function", "mae")]
          loss_funcs = []
          for name in self._names:
              if name.startswith("mask"):
                  loss_funcs.append(self._selected_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         selected_loss = self._loss_dict[self._config.get("loss_function", "mae")]
 </s> add         selected_loss = self._loss_dict[self._config["loss_function"]]
        mask_loss = self._loss_dict[self._config["mask_loss_function"]] </s> remove         for sect in ("global", self.section):
 </s> add         sections = [sect for sect in self.config.sections() if sect.startswith("global")]
        sections.append(self.section)
        for sect in sections: </s> remove         self.set_globals()
 </s> add         self._set_globals()
        self._set_loss() </s> remove     @property
    def _selected_mask_loss(self):
        """ :func:`keras.losses.Loss`: The selected mask loss function. Currently returns mean
        standard error as the default function. """
        loss_func = self._loss_dict["mse"]
        logger.debug("loss_func: %s", loss_func)
        return loss_func

 </s> add 
                loss_funcs.append(mask_loss)
          selected_loss = self._loss_dict[self._config.get("loss_function", "mae")]
          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])
keep keep keep keep replace keep keep keep keep keep
 Training Config - Split Loss to it's own section 
plugins/train/model/_base.py