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: Merge the result of an E step from one node with that of another node (summing up sufficient statistics).
  
  The merging is trivial and after merging all cluster nodes, we have the
  exact same result as if the computation was run on a single node (no
  approximation).
  
  Parameters
  ----------
  other : :class:`~gensim.models.ldamodel.LdaState`
      The state object with which the current one will be merged.
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code: def merge(self, other):
      """Merge the result of an E step from one node with that of another node (summing up sufficient statistics).
  
      The merging is trivial and after merging all cluster nodes, we have the
      exact same result as if the computation was run on a single node (no
      approximation).
  
      Parameters
      ----------
      other : :class:`~gensim.models.ldamodel.LdaState`
          The state object with which the current one will be merged.
  
      """
      assert other is not None
      self.sstats += other.sstats
      self.numdocs += other.numdocs
  
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 3 for calling the LdaState obj's underlying member method code with example usage: obj.merge(other) without return types