stephantul
commented
4 years ago The term transformer is used in the same way in the sklearn library. See: https://scikit-learn.org/stable/modules/generated/sklearn.base.TransformerMixin.html#sklearn.base.TransformerMixin. Originally, the transformers in wordkit inherited from the transformer base class in sklearn. They are still fully compatible with the sklearn transformer API. All this is to say that I think the usage of the term transformer is justified in this case.
In any case, name collisions are to be expected if you go through code bases and/or scientific papers, especially if you switch between fields.
The word 'Transformer' has been used extensively throughout the module. This terminology is a cause of great confusion because the same term is used for the Transformer Model introduced in Attention is all you need which has been popular for various NLP applications in the past years. Though, that's not what the term means to refer to here.