This example is mainly to demonstrate:
- How to train an RNN with persistent state between iterations. Here it simply manages the state inside the graph.
- How to use a TF reader pipeline instead of a DataFlow, for both training & inference.
It trains an language model on PTB dataset, basically an equivalent of the PTB example in tensorflow/models with its "medium" config. It has the same performance & speed as the original example as well.
Note that the data pipeline is completely copied from the tensorflow example.
To Train:
./PTB-LSTM.py