import tensorflow as tf

            self.predictions = tf.argmax(self.fc3, 1, name="predictions")
            losses = tf.nn.softmax_cross_entropy_with_logits(logits=self.fc3, labels=self.input_y)
            regularization_losses = tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)
            self.loss = tf.reduce_mean(losses) + sum(regularization_losses)

        # Accuracy
        with tf.name_scope("accuracy"):
            correct_predictions = tf.equal(self.predictions, tf.argmax(self.input_y, 1))
            self.accuracy = tf.reduce_mean(tf.cast(correct_predictions, "float"), name="accuracy")
