[P] When using LDA topics as input for predictions, is it normal to get exact same topics for both train and test data?

I have a dataset with, amongst others, a column with book descriptions and whether a book has gone viral. I want to extract the topics from the descriptions by first using TF-IDF (also I need TF-IDF because I need to use SMOTE, which needs numerical data), and then using LDA to get the topics. I have a few questions:

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1. Do I fit the TF-IDF on the training data and then transform the validation and test data with that? …

book column data dataset extract lda machinelearning normal predictions test tf-idf topics