          -------
          list
              A list of loss functions to apply to the model
          """
          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"]:
 
</s> remove                 loss_funcs.append(self._selected_mask_loss)
 </s> add                 loss_funcs.append(mask_loss) </s> remove     """ Holds loss names and functions for an Autoencoder.

    Parameters
    ----------
    inputs: list
        A list of input tensors to the model in the order ("a", "b")
    outputs: list
        A list of output tensors to the model in the order ("a", "b")
    """
    def __init__(self, inputs, outputs):
        logger.debug("Initializing %s: (inputs: %s, outputs: %s)",
                     self.__class__.__name__, inputs, outputs)
 </s> add     """ Holds loss names and functions for an Autoencoder. """
    def __init__(self):
        logger.debug("Initializing %s", self.__class__.__name__) </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  </s> remove             self._state.add_session_loss_names(loss.names)
 </s> add             self._state.add_session_loss_names(self._loss.names)
        selected_loss = self._loss_dict[self._config["loss_function"]]
        mask_loss = self._loss_dict[self._config["mask_loss_function"]]
          -------
          list
              A list of loss functions to apply to the model
          """
        selected_loss = self._loss_dict[self._config["loss_function"]]
        mask_loss = self._loss_dict[self._config["mask_loss_function"]]
          loss_funcs = []
          for name in self._names:
              if name.startswith("mask"):
                  loss_funcs.append(self._selected_mask_loss)
              elif self._config["penalized_mask_loss"]:
keep keep keep keep replace keep keep keep keep keep
 Training Config - Split Loss to it's own section 
plugins/train/model/_base.py