with tf.variable_scope('encoder') as scope:

        # Encoder RNN cell
        self.encoder_lstm_cell = tf.nn.rnn_cell.BasicLSTMCell(hidden_units, forget_bias=0.0, state_is_tuple=True)
        self.encoder_cell = tf.nn.rnn_cell.MultiRNNCell([self.encoder_lstm_cell] * num_layers, state_is_tuple=True)

        # Embed encoder RNN inputs
        with tf.device("/cpu:0"):
          embedding = tf.get_variable(
              "embedding", [self.vocab_size_en, hidden_units], dtype=data_type)
          self.embedded_encoder_inputs = tf.nn.embedding_lookup(embedding, self.encoder_inputs)

        # Outputs from encoder RNN
        self.encoder_outputs, self.encoder_state = tf.nn.dynamic_rnn(
            cell=self.encoder_cell,
            inputs=self.embedded_encoder_inputs,
            sequence_length=self.seq_lens_en, time_major=False, dtype=tf.float32)