import tensorflow as tf

                other_grads = strategy.reduce("sum", other_grads)
            other_train_op = dense_opt.apply_gradients(zip(other_grads, other_var))

            with tf.control_dependencies([emb_train_op, other_train_op]):
                total_loss = strategy.reduce("sum", loss)
                total_loss = tf.identity(total_loss)
