Python - Use LDA Topics as Classification Model Input to Predict Document Category (domain)

-Workflow: train LDA model (gensim) -> get topics distribution per document -> feed them to neural classifier to predict document category -> evaluate the model (accuracy, f1, recall, confusion matrix)
-Neural classifier can be either RNN model (with LSTM or GRU) or BERT model.
-Corpus attached