stopped_tokens = [i for i in tokens if not i in en_stop]
tdm.append(stopped_tokens)
dictionary = corpora.Dictionary(tdm)
corpus = [dictionary.doc2bow(i) for i in tdm]
ldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=8, id2word=
    dictionary)
for t in range(ldamodel.num_topics):
    plt.figure()
plt.imshow(WordCloud().fit_words(ldamodel.show_topic(t, 200)))
plt.axis('off')
plt.title('Topic #' + str(t))
plt.show()
How do I print lda topic model and the word cloud of each of the topics