About Trainers

A Trainer is the core interface to the DeepQA code. Trainers specify data, a model, and a way to train the model with the data. This module groups all of the common code related to these things, making only minimal assumptions about what kind of data you’re using or what the structure of your model is. Really, a Trainer is just a nicer interface to a Keras Model, we just call it something else to not create too much naming confusion, and because the Trainer class provides a lot of functionality around training the model that a Keras Model doesn’t.

On top of Trainer, which is a nicer interface to a Keras Model, this module provides a TextTrainer, which adds a lot of functionality for building Keras Models that work with text. We provide APIs around word embeddings, sentence encoding, reading and padding datasets, and similar things. All of the concrete models that we have so far in DeepQA inherit from TextTrainer, so understanding how to use this class is pretty important to understanding DeepQA.

We also deal with the notion of pre-training in this module. A Pretrainer is a Trainer that depends on another Trainer, building its model using pieces of the enclosed Trainer, so that training the Pretrainer updates the weights in the enclosed Trainer object.