def _define_mapping_graph_new(self): with tf.name_scope('seed_links_placeholder_new'): self.seed_entities1_new = tf.placeholder(tf.int32, shape=[None]) self.seed_entities2_new = tf.placeholder(tf.int32, shape=[None]) with tf.name_scope('seed_links_lookup_new'): tes1 = tf.nn.embedding_lookup(self.ent_embeds, self.seed_entities1_new) tes2 = tf.nn.embedding_lookup(self.ent_embeds, self.seed_entities2_new) with tf.name_scope('mapping_loss_new'): self.mapping_loss_new = self.args.new_param * mapping_loss(tes1, tes2, self.mapping_mat, self.eye_mat) self.mapping_optimizer_new = generate_optimizer(self.mapping_loss_new, self.args.learning_rate, opt=self.args.optimizer)
def add_mapping_module(model): with tf.name_scope('seed_links_placeholder'): model.seed_entities1 = tf.placeholder(tf.int32, shape=[None]) model.seed_entities2 = tf.placeholder(tf.int32, shape=[None]) with tf.name_scope('seed_links_lookup'): tes1 = tf.nn.embedding_lookup(model.ent_embeds, model.seed_entities1) tes2 = tf.nn.embedding_lookup(model.ent_embeds, model.seed_entities2) with tf.name_scope('mapping_loss'): model.mapping_loss = model.args.alpha * mapping_loss( tes1, tes2, model.mapping_mat, model.eye_mat) model.mapping_optimizer = generate_optimizer(model.mapping_loss, model.args.learning_rate, opt=model.args.optimizer)