import tensorflow as tf

    tf.set_random_seed(111)
    random.seed(111)
    np.random.seed(111)

    with self.test_session() as sess:
      # We use sampled softmax so we keep output projection separate.
      w = tf.get_variable("proj_w", [24, classes])
      w_t = tf.transpose(w)
      b = tf.get_variable("proj_b", [classes])
      # Here comes a sample Seq2Seq model using GRU cells.
      def SampleGRUSeq2Seq(enc_inp, dec_inp, weights):
        """Example sequence-to-sequence model that uses GRU cells."""
        def GRUSeq2Seq(enc_inp, dec_inp):
          cell = tf.nn.rnn_cell.MultiRNNCell([tf.nn.rnn_cell.GRUCell(24)] * 2,
                                             state_is_tuple=True)
          return tf.nn.seq2seq.embedding_attention_seq2seq(
