          logger.debug("Adding loss: (function: %s, weight: %s, mask_channel: %s)",
                       function, weight, mask_channel)
          self._loss_functions.append(compile_utils.LossesContainer(function))
          self._loss_weights.append(weight)
          self._mask_channels.append(mask_channel)
  
 
</s> remove     def call(self, y_true, y_pred):
 </s> add     def __call__(self, y_true: tf.Tensor, y_pred: tf.Tensor) -> tf.Tensor: </s> remove             self._names.extend(["{}_{}{}".format(name, side,
                                                 "" if output_types.count(name) == 1
                                                 else f"_{idx}")
                                for idx, name in enumerate(output_types)])
 </s> add             for idx, name in enumerate(output_types):
                suffix = "" if output_types.count(name) == 1 else f"_{idx}"
                self._names.append(f"{name}_{side}{suffix}") </s> remove     def add_loss(self, function, weight=1.0, mask_channel=-1):
 </s> add     def add_loss(self,
                 function: tf.keras.losses.Loss,
                 weight: float = 1.0,
                 mask_channel: int = -1) -> None: </s> remove         function: :class:`keras.losses.Loss`
 </s> add         function: :class:`tf.keras.losses.Loss` </s> remove         tensor
            The final loss value
 </s> add         :class:`tensorflow.Tensor`
            The final weighted loss
        # Loss must be compiled inside LossContainer for keras to handle distibuted strategies
          logger.debug("Adding loss: (function: %s, weight: %s, mask_channel: %s)",
                       function, weight, mask_channel)
        # Loss must be compiled inside LossContainer for keras to handle distibuted strategies
          self._loss_functions.append(compile_utils.LossesContainer(function))
          self._loss_weights.append(weight)
          self._mask_channels.append(mask_channel)
  
keep add keep keep keep keep
 bugfix: distibuted training with dssim 
lib/model/losses_tf.py