class_docstr: Metric class for coherence evaluation.
  
  See Also
  --------
  :class:`~gensim.models.coherencemodel.CoherenceModel`
class_docstr_tok: ["Metric","class","for","coherence","evaluation",".","See","Also","--","--","--","--",":","class",":","`","~gensim.models.coherencemodel.CoherenceModel","`"]
docstr: Get the coherence score.
  
  Parameters
  ----------
  **kwargs
      Key word arguments to override the object's internal attributes.
      One of the following parameters are expected:
  
          * `model` - pre-trained topic model of type :class:`~gensim.models.ldamodel.LdaModel`.
          * `topics` - list of tokenized topics.
  
  Returns
  -------
  float
      The coherence score.
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code: def get_value(self, **kwargs):
      """Get the coherence score.
  
      Parameters
      ----------
      **kwargs
          Key word arguments to override the object's internal attributes.
          One of the following parameters are expected:
  
              * `model` - pre-trained topic model of type :class:`~gensim.models.ldamodel.LdaModel`.
              * `topics` - list of tokenized topics.
  
      Returns
      -------
      float
          The coherence score.
  
      """
      # only one of the model or topic would be defined
      self.model = None
      self.topics = None
      super(CoherenceMetric, self).set_parameters(**kwargs)
  
      cm = gensim.models.CoherenceModel(
          model=self.model,
          topics=self.topics,
          texts=self.texts,
          corpus=self.corpus,
          dictionary=self.dictionary,
          window_size=self.window_size,
          coherence=self.coherence,
          topn=self.topn,
      )
  
      return cm.get_coherence()
  
imports: import gensim
  import logging
  import copy
  import sys
  import numpy
label_desc: Use image node_id 2 for calling the CoherenceMetric obj's underlying member method code with example usage: obj.get_value() and returns: cm