Method get_cost

nlp_class2/recursive_tensorflow.py:140–149

(self, logits, labels, reg)

        plt.show()

    def get_cost(self, logits, labels, reg):
        cost = tf.reduce_mean(
            input_tensor=tf.nn.sparse_softmax_cross_entropy_with_logits(
                logits=logits,
                labels=labels
            )
        )
        rcost = sum(tf.nn.l2_loss(p) for p in self.params)
        cost += reg*rcost
        return cost

    # list_of_logits is an output!
    # it is added to using post-order traversal