08ea995b1fa9922e9f69c7ecac8cbb1d5055d22e,Models/ItemRanking/CML.py,CML,build_network,#CML#,38

Before Change

        neg_item_embedding = tf.nn.embedding_lookup(Q, self.neg_item_id)

        self.pred_distance = tf.reduce_sum(tf.squared_difference(user_embedding, item_embedding), 1)
        self.pred_distance_neg = tf.reduce_sum(tf.squared_difference(user_embedding, neg_item_embedding), 1)


        self.loss = tf.reduce_sum(tf.maximum(self.pred_distance - self.pred_distance_neg + margin, 0))

After Change

        neg_item_embedding = tf.nn.embedding_lookup(Q, self.neg_item_id)

        self.pred_distance = tf.reduce_sum(tf.nn.dropout(tf.squared_difference(user_embedding, item_embedding),self.keep_rate), 1)
        self.pred_distance_neg = tf.reduce_sum(tf.nn.dropout(tf.squared_difference(user_embedding, neg_item_embedding),self.keep_rate), 1)


        self.loss = tf.reduce_sum(tf.maximum(self.pred_distance - self.pred_distance_neg + margin, 0))

Instances