Style-Transfer with Transformers

This repository contains the implementation of my summer thesis.

Requirements

You'll need python3, pytorch, spacy, numpy, pyemd, bayesian-optimisation, rouge, and pyTelegramBotAPI. You can install them via pip3 (but you'll want to make use of CUDA so you might want to look into that too).

To make life easier I've added a requirements.txt that'll allow you to install everything necessary (after installing python3.6+):

pip install -e .

Datasets

To make life easier, I've set up a one-command auto running program that'll deal with downloading all the necessary machine-translation datasets needed to make your model. You'll need wget however.

cd datasets
./init_enfr_dataset.sh
./political_data.sh

That being said, you'll have to compose your own newspaper dataset, since I'm near certain that releasing such a dataset is not allowed by the newspapers for a variety of reasons, ranging from ethical to legal. In the root directory there is a zip called newspapers. run the jupyter notebook called downloader_manual.ipynb to get the article dataset (you'll need to submit your login for The Times in times.json first).

If times.json isn't created use the following format:

{
    "action" : "login",
    "username": "TIMES_USERNAME",
    "password": "PASSWORD",
    "s" : 1,
    "rememberMe" : "on"
}

After running the notebook run convert_express.sh and it'll move it to the base directory.

Running

Once the datasets are downloaded, cd base/scripts and run the following:

cd prod
./train_nmt_models.sh
./train_pol_st_models.sh
./build_pub_corpus.sh
./train_pub_st_models.sh
./train_pub_naturalness_models.sh

It'll probably take quite a while to train the models.