In the method we are deleting ngrams and reducing history counts, i think vocabulary needs to be cleaned up too (when word history becomes zero, for instance).
The main idea of this method is to get rid of tokens and their sequences that we find irrelevant, in order to speed up reading from file or lookup within the model. And in this case always keeping all the vocabulary entries defeats the purpose.
In the method we are deleting ngrams and reducing history counts, i think vocabulary needs to be cleaned up too (when word history becomes zero, for instance).
The main idea of this method is to get rid of tokens and their sequences that we find irrelevant, in order to speed up reading from file or lookup within the model. And in this case always keeping all the vocabulary entries defeats the purpose.