code: def create_composite_loss(self,
                              losses,
                              regularize=True,
                              include_marked=True,
                              name='cost'):
      
      all_losses = []
      if losses:
        all_losses.extend(losses)
      if include_marked:
        all_losses.extend(self.marked_losses)
      if not all_losses:
        raise ValueError('No losses specified!')
      if regularize:
        all_losses.extend(self.regularization_losses)
      with self._g.as_default():
        result = tf.add_n(all_losses, name=name)
        self.add_scalar_summary(result)
        return result
docs: Creates a loss that is the sum of all specified losses.
  
      Args:
        losses: A sequence of losses to include.
        regularize: Whether or not to include regularization losses.
        include_marked: Whether or not to use the marked losses.
        name: The name for this variable.
      Returns:
        A single tensor that is the sum of all losses.
      Raises:
        ValueError: if there are no losses.