import tensorflow as tf


        # Define LSTM cell of first hidden layer:
        lstm_cell = tf.nn.rnn_cell.BasicLSTMCell(config.n_hidden, forget_bias=1.0)

        # Stack two LSTM layers, both layers has the same shape
        lsmt_layers = tf.nn.rnn_cell.MultiRNNCell([lstm_cell] * 2)

        # Get LSTM outputs, the states are internal to the LSTM cells,they are not our attention here
        outputs, _ = tf.nn.rnn(lsmt_layers, hidden, dtype=tf.float32)
        # outputs' shape: a list of lenght "time_step" containing tensors of shape [batch_size, n_hidden]
