import tensorflow as tf

          cell = tf.nn.rnn_cell.MultiRNNCell([tf.nn.rnn_cell.GRUCell(24)] * 2,
                                             state_is_tuple=True)
          return tf.nn.seq2seq.embedding_attention_seq2seq(
              enc_inp, dec_inp, cell, num_encoder_symbols=classes,
              num_decoder_symbols=classes, embedding_size=24)
        targets = [dec_inp[i+1] for i in range(len(dec_inp) - 1)] + [0]
        return tf.nn.seq2seq.model_with_buckets(
            enc_inp, dec_inp, targets, weights, buckets, GRUSeq2Seq,
            per_example_loss=per_example_loss)

      # Now we construct the copy model.
      inp = [tf.placeholder(tf.int32, shape=[None]) for _ in range(8)]
