train_utils.py 文件源码

def triplet_loss(anchor, positive, negative, alpha):
    """Calculate the triplet loss according to the FaceNet paper

    args:
      anchor: the embeddings for the anchor images.
      positive: the embeddings for the positive images.
      negative: the embeddings for the negative images.

    returns:
      the triplet loss according to the FaceNet paper as a float tensor.
    """
    pos_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, positive)), 1)
    neg_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, negative)), 1)
    tot_dist = tf.sum(tf.subtract(pos_dist, neg_dist), alpha)
    loss = tf.reduce_mean(tf.maximum(tot_dist, 0.0), 0)
    return loss