class_docstr: Ensemble Latent Dirichlet Allocation (eLDA), a method of training a topic model ensemble.
  
  Extracts stable topics that are consistently learned across multiple LDA models. eLDA has the added benefit that
  the user does not need to know the exact number of topics the topic model should extract ahead of time.
class_docstr_tok: ["Ensemble","Latent","Dirichlet","Allocation","(","eLDA",")",",","a","method","of","training","a","topic","model","ensemble",".","Extracts","stable","topics","that","are","consistently","learned","across","multiple","LDA","models",".","eLDA","has","the","added","benefit","that","the","user","does","not","need","to","know","the","exact","number","of","topics","the","topic","model","should","extract","ahead","of","time","."]
docstr: Get the class that is used for :meth:`gensim.models.EnsembleLda.generate_gensim_representation`.
docstr_tok: ["Get","the","class","that","is","used","for",":","meth",":","`","gensim.models.EnsembleLda.generate_gensim_representation","`","."]
code: def get_topic_model_class(self):
      """Get the class that is used for :meth:`gensim.models.EnsembleLda.generate_gensim_representation`."""
      if self.topic_model_class is None:
          instruction = (
              "Try setting topic_model_class manually to what the individual models were based on, "
              "e.g. LdaMulticore."
          )
          try:
              module = importlib.import_module(
                  self.topic_model_module_string
              )
              self.topic_model_class = getattr(
                  module, self.topic_model_class_string
              )
              del self.topic_model_module_string
              del self.topic_model_class_string
          except ModuleNotFoundError:
              logger.error(
                  f'Could not import the "{self.topic_model_class_string}" module in order to provide the '
                  f'"{self.topic_model_class_string}" class as "topic_model_class" attribute. {instruction}'
              )
          except AttributeError:
              logger.error(
                  f'Could not import the "{self.topic_model_class_string}" class from the '
                  f'"{self.topic_model_module_string}" module in order to set the "topic_model_class" attribute. '
                  f"{instruction}"
              )
      return self.topic_model_class
  
imports: import logging
  import os
  from multiprocessing import Process, Pipe, ProcessError
  import importlib
  from typing import Set, Optional, List
  import numpy
  from scipy.spatial.distance import cosine
  from dataclasses import dataclass
  from gensim import utils
  from gensim.models import ldamodel, ldamulticore, basemodel
  from gensim.utils import SaveLoad
label_desc: Use image node_id 2 for calling the EnsembleLda obj's underlying member method code with example usage: obj.get_topic_model_class() and returns: self