Exploring Stack Augmented Neural Networks for Transduction — CMPUT 651 Term Project

By: Sarah Davis and Henry Tang

The objective of this project is to solve the transduction problem. This work is a fork from the original repository where we add a Seq2Seq model and use the provided RNN implementations to replace the encoder of the Seq2Seq.

Introduction

This repository contains all the code, instructions, and data for our term project. The data directory contains the datasets used for the experiments. For full output files, see our CMPUT 651 specific repository

Installation and execution

1. Activate virtual environment and install dependencies

   python3 -m venv venv
   
   venv\Scripts\activate.bat  # windows
   source venv/bin/activate  # unix
   
   pip install -r requirements.txt

2. Run the program with

   python seq2seq.py

3. To test the different datasets, the source code needs to be modified

   # seq2seq.py line 463   
   
   input_lang, output_lang, pairs = prepareData("data/dataset_len_35_40.tsv", "infix", 'postfix')