code: def setUp(self):
      # Suppose given below are the topics which two different LdaModels come up with.
      # `topics1` is clearly better as it has a clear distinction between system-human
      # interaction and graphs. Hence both the coherence measures for `topics1` should be
      # greater.
      self.topics1 = [
          ["human", "computer", "system", "interface"],
          ["graph", "minors", "trees", "eps"],
      ]
      self.topics2 = [
          ["user", "graph", "minors", "system"],
          ["time", "graph", "survey", "minors"],
      ]
      self.topics3 = [
          ["token", "computer", "system", "interface"],
          ["graph", "minors", "trees", "eps"],
      ]
      # using this list the model should be unable to interpret topic
      # as either a list of tokens or a list of ids
      self.topics4 = [
          ["not a token", "not an id", "tests using", "this list"],
          ["should raise", "an error", "to pass", "correctly"],
      ]
      # list of topics with unseen words in the dictionary
      self.topics5 = [
          ["aaaaa", "bbbbb", "ccccc", "eeeee"],
          ["ddddd", "fffff", "ggggh", "hhhhh"],
      ]
      self.topicIds1 = []
      for topic in self.topics1:
          self.topicIds1.append(
              [self.dictionary.token2id[token] for token in topic]
          )
  
      self.ldamodel = LdaModel(
          corpus=self.corpus,
          id2word=self.dictionary,
          num_topics=2,
          passes=0,
          iterations=0,
      )
  
imports: import logging
  import unittest
  import multiprocessing
  from functools import partial
  import numpy
  from gensim.matutils import argsort
  from gensim.models.coherencemodel import CoherenceModel, BOOLEAN_DOCUMENT_BASED
  from gensim.models.ldamodel import LdaModel
  from gensim.test.utils import get_tmpfile, common_texts, common_dictionary, common_corpus
label_desc: Use image node_id 1 for calling the TestCoherenceModel obj's underlying member method code with example usage: obj.setUp() without return types