class_docstr: TopicModel objects can be used to predict the underlying topic of a
  document.
  
  This model cannot be constructed directly.  Instead, use
  :func:`turicreate.topic_model.create` to create an instance
  of this model. A detailed list of parameter options and code samples
  are available in the documentation for the create function.
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docstr: Returns a structured description of the model, including (where relevant)
  the schema of the training data, description of the training data,
  training statistics, and model hyperparameters.
  
  Returns
  -------
  sections : list (of list of tuples)
      A list of summary sections.
        Each section is a list.
          Each item in a section list is a tuple of the form:
            ('<label>','<field>')
  section_titles: list
      A list of section titles.
        The order matches that of the 'sections' object.
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code: def _get_summary_struct(self):
      """
      Returns a structured description of the model, including (where relevant)
      the schema of the training data, description of the training data,
      training statistics, and model hyperparameters.
  
      Returns
      -------
      sections : list (of list of tuples)
          A list of summary sections.
            Each section is a list.
              Each item in a section list is a tuple of the form:
                ('<label>','<field>')
      section_titles: list
          A list of section titles.
            The order matches that of the 'sections' object.
      """
      section_titles = ["Schema", "Settings"]
  
      vocab_length = len(self.vocabulary)
      verbose = self.verbose == 1
  
      sections = [
          [("Vocabulary Size", _precomputed_field(vocab_length))],
          [
              ("Number of Topics", "num_topics"),
              ("alpha", "alpha"),
              ("beta", "beta"),
              ("Iterations", "num_iterations"),
              ("Training time", "training_time"),
              ("Verbose", _precomputed_field(verbose)),
          ],
      ]
      return (sections, section_titles)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import turicreate
  from turicreate.toolkits._model import Model
  from turicreate.data_structures.sframe import SFrame
  from turicreate.data_structures.sarray import SArray
  from turicreate.toolkits.text_analytics._util import _check_input
  from turicreate.toolkits.text_analytics._util import random_split
  from turicreate.toolkits._internal_utils import _check_categorical_option_type, _precomputed_field, _toolkit_repr_print
  import sys
  import operator
  import array
label_desc: Use image node_id 4 for calling the TopicModel obj's underlying member method code with example usage: obj._get_summary_struct() and returns: sections,  section_titles