SingleLayerCAE.py 文件源码

def loss(self, predictions, real_values):
        """Return the loss operation between predictions and real_values.
        Add L2 weight decay term if any.
        Args:
            predictions: predicted values
            real_values: real values
        Returns:
            Loss tensor of type float.
        """
        with tf.variable_scope('loss'):
            # 1/2n \sum^{n}_{i=i}{(x_i - x'_i)^2}
            mse = tf.divide(
                tf.reduce_mean(
                    tf.square(tf.subtract(predictions, real_values))),
                2.,
                name="mse")
            tf.add_to_collection(LOSSES, mse)

            # mse + weight_decay per layer
            error = tf.add_n(tf.get_collection(LOSSES), name='total_loss')

        return error