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)