frame_level_models.py 文件源码

def calculate_loss(self, predictions, labels, **unused_params):
        with tf.name_scope("loss_frames"):
            epsilon = 10e-6
            float_labels = tf.cast(labels, tf.float32)
            cross_entropy_loss = float_labels * tf.log(predictions + epsilon) + (
                1 - float_labels) * tf.log(1 - predictions + epsilon)

        return tf.reduce_sum(cross_entropy_loss, 2)