TextAttack VS OpenAttack

Could have a look at what's available in the augmentor here https://github.com/QData/TextAttack. I'm not experienced with NLP so I may be way off here

Text data augmentation - negate words, replace words with similes, perturb word embeddings (nice github repo for this)

Similar to TextAttack, OpenAttack adopts modular design to assemble various attack models, in order to enable quick implementation of existing or new attack models. But OpenAttack is different from and complementary to TextAttack mainly in the following three aspects: 1) Support for all attacks. TextAttack utilizes a relatively rigorous framework to unify different attack models. However, this framework is naturally not suitable for sentence-level adversarial attacks, an important and typical kind of textual adversarial attacks. Thus, no sentence-level attack models are included in TextAttack. In contrast, OpenAttack adopts a more flexible framework that supports all types of attacks including sentence-level attacks. 2) Multilinguality. TextAttack only covers English textual attacks while OpenAttack supports English and Chinese now. And its extensible design enables quick support for more languages. 3) Parallel processing. Running some attack models maybe very time-consuming, e.g., it takes over 100 seconds to attack an instance with the SememePSO attack model (Zang et al., 2020). To address this issue, OpenAttack additionally provides support for multi-process running of attack models to improve attack efficiency.