class_docstr: Base Metric class for topic model evaluation metrics.
  
  Concrete implementations include:
  
      * :class:`~gensim.models.callbacks.CoherenceMetric`
      * :class:`~gensim.models.callbacks.PerplexityMetric`
      * :class:`~gensim.models.callbacks.DiffMetric`
      * :class:`~gensim.models.callbacks.ConvergenceMetric`
class_docstr_tok: ["Base","Metric","class","for","topic","model","evaluation","metrics",".","Concrete","implementations","include",":","*",":","class",":","`","~gensim.models.callbacks.CoherenceMetric","`","*",":","class",":","`","~gensim.models.callbacks.PerplexityMetric","`","*",":","class",":","`","~gensim.models.callbacks.DiffMetric","`","*",":","class",":","`","~gensim.models.callbacks.ConvergenceMetric","`"]
docstr: Get a string representation of Metric class.
  
  Returns
  -------
  str
      Human readable representation of the metric.
docstr_tok: ["Get","a","string","representation","of","Metric","class",".","Returns","--","--","--","-","str","Human","readable","representation","of","the","metric","."]
code: def __str__(self):
      """Get a string representation of Metric class.
  
      Returns
      -------
      str
          Human readable representation of the metric.
  
      """
      if self.title is not None:
          return self.title
      else:
          return type(self).__name__[:-6]
  
imports: import gensim
  import logging
  import copy
  import sys
  import numpy
label_desc: Use image node_id 1 for calling the Metric obj's underlying member method code with example usage: obj.__str__() and returns: self, type