This function implement the computation of the triplet loss function for the face recognition application

FaceNet_triplet_loss.py

def triplet_loss_function(im_anchor, im_positive, im_negative, alpha = 0.2):
    """
    Implementation of the triplet loss function
    
    Source: https://arxiv.org/pdf/1503.03832.pdf
    
    Arguments:
    y_pred -- python list containing three objects:
            anchor -- the encodings for the anchor images, of shape (None, 128)
            positive -- the encodings for the positive images, of shape (None, 128)
            negative -- the encodings for the negative images, of shape (None, 128)
    
    Returns:
    loss -- real number, value of the loss
    """
   
   
    # Compute the (encoding) distance between the anchor and the positive, then negative images
    pos_dist = tf.reduce_sum(tf.square(tf.subtract(im_anchor, im_positive)), axis=-1)
    neg_dist = tf.reduce_sum(tf.square(tf.subtract(im_anchor, im_negative)), axis=-1)
    
    basic_loss = tf.add(tf.subtract(pos_dist, neg_dist), alpha)
    
    return tf.reduce_sum(tf.maximum(basic_loss, 0.0))