def METHOD_NAME(self, bottleneck, scope="head"):
    """Appends the serving signature of the model to the current graph.
    Bottleneck tensor is connected as an input to the added model.
    All model variables are converted to placeholders and returned
    in a list.
    Args:
      bottleneck: tensor in the current graph to be connected as input.
      scope: name of the scope to load the model into.
    Returns:
      (head model output tensor, list of variable placeholders)
    """
    logits, variables, _ = self._logits(bottleneck, scope)
    predictions = tf.nn.softmax(logits)
    return predictions, variables