                                 l_inf_norm=losses.LInfNorm(),
                                 ssim=losses.DSSIMObjective(),
                                 gmsd=losses.GMSDLoss(),
                                 pixel_gradient_diff=losses.GradientLoss())
          self._inputs = inputs
          self._names = self._get_loss_names(outputs)
          self._funcs = self._get_loss_functions()
          self._names.insert(0, "total")
          logger.debug("Initialized: %s", self.__class__.__name__)
  
      @property
      def names(self):
          """ list: The list of loss names for the model. """
 
</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     """ 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         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"]]
        self._inputs = None
        self._names = None
        self._funcs = None
                                 l_inf_norm=losses.LInfNorm(),
                                 ssim=losses.DSSIMObjective(),
                                 gmsd=losses.GMSDLoss(),
                                 pixel_gradient_diff=losses.GradientLoss())
        self._inputs = None
        self._names = None
        self._funcs = None
        self._inputs = None
        self._names = None
        self._funcs = None
        self._inputs = None
        self._names = None
        self._funcs = None
        self._inputs = None
        self._names = None
        self._funcs = None
          logger.debug("Initialized: %s", self.__class__.__name__)
  
      @property
      def names(self):
          """ list: The list of loss names for the model. """
keep keep keep keep replace replace replace replace keep keep keep keep keep
 Training Config - Split Loss to it's own section 
plugins/train/model/_base.py