Sequence Model (Work-In-Progress)

A code base for creating and running sequence models of language. Including language modeling, definition modeling, and common encoder-decoder stuffs. Required python 3.6.

Requirements:

• python 3.6
• tensorflow 1.1
• numpy 1.12
• nltk 3.2.4
• six 1.10

Overview

• dstruct.py: basic data structures and tuples
• generator.py: functions data reader and batch generator
• graph.py: functions to create various types of graphs
• model.py: runnable models from configuration
• run.py: functions to train and evaluate model (data + model -> result)
• util.py: utility functions (dictionary, array, logging, and cmd arguments)

TODO

Model

• Value Network and A2C

Run

• TD(lambda)
• Bootstrap last state if not terminal

Generator

• Option to randomly select sequences of the same encode input

Scripts

• Option to select reward function from CLI

TensorFlow

• Take advantage of tf.Session.make_callable (need benchmark)

Bucket list

• Compile my own TensorFlow
• Use tf.summary for tensorboard.
• It would be nice if we do not need to fecth state and feed it back in when training a langauge model (sentence dependent).
• Ensure the indices of </s> and <s> are 0 and 1, and index of _ is 0 for char-level data