import tensorflow as tf

        graph_results = _train_step(inputs, labels, training=True)

        init_op = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer())

        restore_op = list()
        for i, embedding_weight in enumerate(tf_sparse_demo.embedding_weights):
            restore_op.append(embedding_weight.assign(tf.concat(init_tensors[i], axis=0)))

        emb_values = list()
        for embedding_weight in tf_sparse_demo.embedding_weights:
            if args.save_params:
                filepath = r"./embedding_variables/"
