class_docstr: Encapsulate information for distributed computation of :class:`~gensim.models.ldamodel.LdaModel` objects.
  
  Objects of this class are sent over the network, so try to keep them lean to
  reduce traffic.
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docstr: Get the parameters of the posterior over the topics, also referred to as "the topics".
  
  Returns
  -------
  numpy.ndarray
      Parameters of the posterior probability over topics.
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code: def get_lambda(self):
      """Get the parameters of the posterior over the topics, also referred to as "the topics".
  
      Returns
      -------
      numpy.ndarray
          Parameters of the posterior probability over topics.
  
      """
      return self.eta + self.sstats
  
imports: import logging
  import numbers
  import os
  import time
  from collections import defaultdict
  import numpy
  from scipy.special import gammaln, psi
  from scipy.special import polygamma
  from gensim import interfaces, utils, matutils
  from gensim.matutils import kullback_leibler, hellinger, jaccard_distance, jensen_shannon, dirichlet_expectation, logsumexp, mean_absolute_difference
  from gensim.models import basemodel, CoherenceModel
  from gensim.models.callbacks import Callback
label_desc: Use image node_id 6 for calling the LdaState obj's underlying member method code with example usage: obj.get_lambda() and returns: unknown