import tensorflow as tf

    metrics = []

    metrics.append(tf.summary.histogram('point_distance', dists))
    metrics.append(tf.summary.scalar('training/trajectory_length', tf.reduce_sum(dists)))
    self.blur_ph = tf.placeholder(dtype=tf.float32)
    metrics.append(tf.summary.scalar('training/blur_sigma', self.blur_ph))

    pred = self.embedding_test[1:-1]*2 - self.embedding_test[0:-2]
    pred_error = l2(pred - self.embedding_test[2:])

    mean_dist, mean_pred_error = tf.reduce_mean(dists), tf.reduce_mean(pred_error)
    improvement = (mean_dist-mean_pred_error)/mean_dist

    pairwise_improvement = tf.nn.relu(dists[1:] - pred_error)
    pairwise_improvement_bool = tf.cast(pairwise_improvement > 0, pairwise_improvement.dtype)
    self.pairwise_improvement_bool = pairwise_improvement_bool

    metrics.append(tf.summary.scalar('training/avg_dist', mean_dist))
    metrics.append(tf.summary.scalar('training/pred_dist', mean_pred_error))
    metrics.append(tf.summary.scalar('training/improvement', improvement))
