TextAttack: Lessons learned in designing Python frameworks for NLP
John X. Morris, Jin Yong Yoo, Yanjun Qi · 2020
TextAttack is an open-source Python toolkit for adversarial attacks, adversarial training, and data augmentation in NLP.TextAttack unites 15+ papers from the NLP adversarial attack literature into a single framework, with many components reused across attacks.This framework allows both researchers and developers to test and study the weaknesses of their NLP models.To build such an open-source NLP toolkit requires solving some common problems: How do we enable users to supply models from different deep learning frameworks?How can we build tools to support as many different datasets as possible?We share our insights into developing a well-written, well-documented NLP Python framework in hope that they can aid future development of similar packages.