corpus = [dictionary.doc2bow(text) for text in final_text]
corpora.MmCorpus.serialize('questions.mm', corpus)
corpora.SvmLightCorpus.serialize('questions.svmlight', corpus)
corpora.BleiCorpus.serialize('questions.lda-c', corpus)
corpora.LowCorpus.serialize('questions.low', corpus)
mm = corpora.MmCorpus('questions.mm')
lda = gensim.models.ldamodel.LdaModel(corpus=mm, id2word=dictionary,
    num_topics=100, update_every=0, chunksize=19188, passes=20)
Can we use a self made corpus for training for LDA using gensim?