[Python] Classify Text with Gensim LDA Model

For reference, I already looked at the following questions:

1. Gensim LDA for text classification
2. Python Gensim LDA Model show_topics funciton

I am looking to have my LDA model trained from Gensim classify a sentence under one of the topics that the model creates. Something long the lines of

lda = models.LdaModel(corpus=corpus, id2word=id2word, num_topics=7, passes=20)
lda.print_topics()
for line in document: # where each line in the document is its own sentence for simplicity
print('Sentence: ', line)
topic = lda.parse(line) # where the classification would occur
print('Topic: ', topic)


I know gensim does not have a parse function, but how would one go about accomplishing this? Here is the documentation that I've been following but I haven't gotten anywhere with it:

https://radimrehurek.com/gensim/aut...amples-core-run-topics-and-transformations-py

Thanks in advance.

edit: More documentation- https://radimrehurek.com/gensim/models/ldamodel.html

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