too many values to unpack (expected 2) lda - lda

Question

I received error : too many values to unpack (expected 2) , when running the below code. anyone can help me? I added more details.
import gensim
import gensim.corpora as corpora
dictionary = corpora.Dictionary(doc_clean)
doc_term_matrix = [dictionary.doc2bow(doc) for doc in doc_clean]
Lda = gensim.models.ldamodel.LdaModel
ldamodel = Lda(doc_term_matrix, num_topics=3, id2word = dictionary, passes=50, per_word_topics = True, eval_every = 1)
print(ldamodel.print_topics(num_topics=3, num_words=20))
for i in range (0,46):
for index, score in sorted(ldamodel[doc_term_matrix[i]], key=lambda tup: -1*tup[1]):
print("subject", i)
print("\n")
print("Score: {}\t \nTopic: {}".format(score, ldamodel.print_topic(index, 6)))

Answer 1

Focusing on the loop, since this is where the error is being raised. Let's take it one iteration at a time.
>>> import numpy as np # just so we can use np.shape()
>>> i = 0 # value in first loop
>>> x = sorted( ldamodel[doc_term_matrix[i]], key=lambda tup: -1*tup[1] )
>>> np.shape(x)
(3, 3, 2)
>>> for index, score in x:
... pass
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ValueError: too many values to unpack (expected 2)
Here is where your error is coming from. You are expecting this returned matrix to have 2 elements, however it is a multislice matrix with no simple infer-able way to unpack it. I do not personally have enough experience with this subject material to be able to infer what you might mean to be doing, I can only show you where your problem is coming from. Hope this helps!