import tensorflow as tf

    metrics.append(tf.summary.scalar('training/pred_dist', mean_pred_error))
    metrics.append(tf.summary.scalar('training/improvement', improvement))
    metrics.append(tf.summary.scalar('training/improvement_abs', tf.nn.relu(improvement)))
    metrics.append(tf.summary.histogram('training/improvement_abs_hist', nut.nan_to_zero(improvement)))
    metrics.append(tf.summary.scalar('training/improvement_pairwise', tf.reduce_mean(pairwise_improvement_bool)))
    metrics.append(tf.summary.histogram('training/improvement_pairwise_hist', pairwise_improvement_bool))
    self.eval_summs = tf.summary.merge(metrics)


  def _build_embedding_saver(self, sess):
