class_docstr: A class representing routines called reactively at specific phases during trained.
  
  These can be used to log or visualize the training progress using any of the metric scores developed before.
  The values are stored at the end of each training epoch. The following metric scores are currently available:
  
      * :class:`~gensim.models.callbacks.CoherenceMetric`
      * :class:`~gensim.models.callbacks.PerplexityMetric`
      * :class:`~gensim.models.callbacks.DiffMetric`
      * :class:`~gensim.models.callbacks.ConvergenceMetric`
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docstr: Parameters
  ----------
  metrics : list of :class:`~gensim.models.callbacks.Metric`
      The list of metrics to be reported by the callback.
docstr_tok: ["Parameters","--","--","--","--","--","metrics",":","list","of",":","class",":","`","~gensim.models.callbacks.Metric","`","The","list","of","metrics","to","be","reported","by","the","callback","."]
code: def __init__(self, metrics):
      """
  
      Parameters
      ----------
      metrics : list of :class:`~gensim.models.callbacks.Metric`
          The list of metrics to be reported by the callback.
  
      """
      self.metrics = metrics
  
imports: import gensim
  import logging
  import copy
  import sys
  import numpy
label_desc: Use image node_id 1 to create a new Callback object  with example: obj = Callback(metrics)