import tensorflow as tf

          transformer_output = self.transparent_merger[0].FProp(
              theta.transparent_merger[0], outputs_list)
        else:
          transformer_output = []
          for i in range(p.num_transparent_outputs):
            merged_outputs = self.transparent_merger[i].FProp(
                theta.transparent_merger[i], outputs_list)
            transformer_output.append(merged_outputs)
          if p.is_eval:
            transformer_output = tf.stack(transformer_output, 3)

      return transformer_output, paddings, src_segment_id
