          Parameters
          ----------
          outputs: list
              A list of output tensors from the model plugin
  
          Returns
          -------
          list
              A list of names for the losses to be applied to the model
          """
          # TODO Use output names if/when these are fixed upstream
          split_outputs = [outputs[:len(outputs) // 2], outputs[len(outputs) // 2:]]
          retval = []
          for side, side_output in zip(("a", "b"), split_outputs):
 
</s> remove         retval = []
 </s> add  </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         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")
 </s> add         model: :class:`keras.models.Model`
            The model that is to be trained </s> remove         self._inputs = inputs
        self._names = self._get_loss_names(outputs)
        self._funcs = self._get_loss_functions()
 </s> add         self._inputs = model.inputs
        self._get_loss_names(model.outputs)
        self._get_loss_functions(model.output_names) </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):
          Parameters
          ----------
          outputs: list
              A list of output tensors from the model plugin





          """
          # TODO Use output names if/when these are fixed upstream
          split_outputs = [outputs[:len(outputs) // 2], outputs[len(outputs) // 2:]]
          retval = []
          for side, side_output in zip(("a", "b"), split_outputs):
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 training - Use explicit loss dictionaries to map to outputs 
plugins/train/model/_base.py