hard margin smooth hinge triplet loss

triplet_loss.py

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.
    """
    with tf.variable_scope('triplet_loss'):
        pos_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, positive)), 1)
        neg_dist = tf.reduce_sum(tf.square(tf.subtract(anchor, negative)), 1)

        diff = tf.subtract(pos_dist, neg_dist)
        loss = tf.relu(tf.add(diff, alpha))
        quad = tf.minimum(loss, 2*alpha)
        loss = tf.square(quad) + 4 * alpha *(loss - quad)
        loss = tf.reduce_mean(loss )
                 
    return loss