This is an implementation of the DeleteOnly and DeleteAndRetrieve models from Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer
pip3 install -r requirements.txt
This code uses python 3.
python3 train.py --config yelp_config.json --bleu
This will reproduce the delete model on a dataset of yelp reviews:
Checkpoints, logs, model outputs, and TensorBoard summaries are written in the config's working_dir.
See yelp_config.json for all of the training options. The most important parameter is model_type, which can be set to delete, delete_retrieve, or seq2seq (which is a standard translation-style model).
Given two pre-tokenized corpus files, use the scripts in tools/ to generate a vocabulary and attribute vocabulary:
python tools/make_vocab.py [entire corpus file (src + tgt cat'd)] [vocab size] > vocab.txt
python tools/make_attribute_vocab.py vocab.txt [corpus src file] [corpus tgt file] [salience ratio] > attribute_vocab.txt
python tools/make_ngram_attribute_vocab.py vocab.txt [corpus src file] [corpus tgt file] [salience ratio] > attribute_vocab.txt
If you use this code as part of your own research can you please cite
(1) the original paper:
@inproceedings{li2018transfer,
author = {Juncen Li and Robin Jia and He He and Percy Liang},
booktitle = {North American Association for Computational Linguistics (NAACL)},
title = {Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer},
url = {https://nlp.stanford.edu/pubs/li2018transfer.pdf},
year = {2018}
}
(2) The paper that this implementation was developed for:
@inproceedings{pryzant2020bias,
author = {Pryzant, Reid and Richard, Diehl Martinez and Dass, Nathan and Kurohashi, Sadao and Jurafsky, Dan and Yang, Diyi},
booktitle = {Association for the Advancement of Artificial Intelligence (AAAI)},
link = {https://nlp.stanford.edu/pubs/pryzant2020bias.pdf},
title = {Automatically Neutralizing Subjective Bias in Text},
url = {https://nlp.stanford.edu/pubs/pryzant2020bias.pdf},
year = {2020}
}
Thanks lots to Karishma Mandyam for contributing!