Not sure if this is the right board, but here goes. At https://github.com/glinscott/leela-chess we’re working on an open source chess engine based on the published work from DeepMind: AlphaZero and AlphaGoZero. Since we are on the edge of training our first (relatively small) neural network through millions of selfplay games, I wanted to investigate the use of TensorRT.
I skimmed the API documentation at http://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html and my main question is whether this is possible given our neural network architecture which consists of 64 filters and 6 residual blocks with 2 output heads:
Our model is trained using tensorflow. All the TensorRT examples use a single head and I was wondering how portable is the TensorRT solution?