Document embeddings are not calculated during inference in neuralcoref.pyx, but they are left at zeros.

This causes a mismatch between inference and training input features (doc embeddings during training are correctly calculated in document.py). Is it a bug or is it intentional? There is a call to a method get_average_embedding as a comment but it does not exist.