train_utils.py 文件源码

def center_loss(features, label, alpha, num_classes):
    """Center loss based on the paper "A Discriminative Feature Learning Approach for Deep Face Recognition"
       (http://ydwen.github.io/papers/WenECCV16.pdf)
    """
    dim_features = features.get_shape()[1]
    centers = tf.get_variable('centers', [num_classes, dim_features], dtype=tf.float32,
                              initializer=tf.constant_initializer(0), trainable=False)
    label = tf.reshape(label, [-1])
    center_feats = tf.gather(centers, label)
    diff = (1 - alpha) * tf.subtract(center_feats, features)
    centers = tf.scatter_sub(centers, label, diff)
    loss = tf.nn.l2_loss(features - center_feats)
    return loss, centers