Sequence-to-sequence learning

In the previous section, we saw a high-level overview of our network model. In this section, we want to look at a Keras implementation of a generative conversational model that uses sequence-to-sequence learning. Before we get into the theory of this form of generative model, let's get the sample running, since it can take a while. The sample we will explore is the Keras reference sample for sequence-to-sequence machine translation. It is currently configured to do English-to-French translation.

Open up the Chapter_4_1.py sample code listing and get it running using these steps:

1. Open up a shell or Anaconda window. Then run the following command:

python3 Chapter_4_1.py

2. This will run the sample, and it may take several hours to run. The sample can also consume a substantial amount of memory and this may force memory paging on lower memory systems...