This repo contains the code and data of the following paper:

"Style Transfer from Non-Parallel Text by Cross-Alignment". Tianxiao Shen, Tao Lei, Regina Barzilay, and Tommi Jaakkola. NIPS 2017. arXiv

The method learns to perform style transfer between two non-parallel corpora. For example, given positive and negative reviews as two corpora, the model can learn to reverse the sentiment of a sentence.

Please name the corpora of two styles by "x.0" and "x.1" respectively, and use "x" to refer to them in options. Each file should consist of one sentence per line with tokens separated by a space.

The data/yelp/ directory contains an example Yelp review dataset.

To train a model, first create a tmp/ folder, then go to the code/ folder and run the following command:

python style_transfer.py --train ../data/yelp/sentiment.train --dev ../data/yelp/sentiment.dev --output ../tmp/sentiment.dev --vocab ../tmp/yelp.vocab --model ../tmp/model

To test the model, run the following command:

python style_transfer.py --test ../data/yelp/sentiment.test --output ../tmp/sentiment.test --vocab ../tmp/yelp.vocab --model ../tmp/model --load_model true

The model and results will be saved in the tmp/ folder.

Check code/options.py for all running options.

Python >= 2.7, TensorFlow 1.3.0