How to implement a complete LSTM network with cudnn?

[cqiaoYc]

I am building a semi supervised learning system with GA + LSTM. I need to build a multi-layer LSTM network with cudnn, which contains several LSTM layers and a softmax output layer. The LSTM network only needs inference function and no training. In the RNN_example.cu, you show how to create LSTM layers, but how to connect a LSTM layer and a softmax layer. There should be a density layer in the middle. The output of LSTM layer is 3D, and the input of density layer is 2D. How to convert?