import tensorflow as tf

        dense_opt = utils.get_dense_optimizer(args.optimizer)(learning_rate=0.1)

    sok_saver = sok.Saver()
    restore_op = list()
    for i, embedding_layer in enumerate(sok_sparse_demo.embedding_layers):
        control_inputs = [restore_op[-1]] if restore_op else None
        with tf.control_dependencies(control_inputs):
            if args.restore_params:
                filepath = r"./embedding_variables"
                op = sok_saver.restore_from_file(embedding_layer.embedding_variable, filepath)
            else:
                op = sok_saver.load_embedding_values(embedding_layer.embedding_variable, init_tensors[i])
