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: Return a dictionary of statistics collected during creation of the
  model. These statistics are also available with the ``get`` method and
  are described in more detail in that method's documentation.
  
  Returns
  -------
  out : dict
      Dictionary of statistics compiled during creation of the
      TopicModel.
  
  See Also
  --------
  summary
  
  Examples
  --------
  >>> docs = turicreate.SArray('https://static.turi.com/datasets/nips-text')
  >>> m = turicreate.topic_model.create(docs)
  >>> m._training_stats()
  {'training_iterations': 20,
   'training_time': 20.5034}
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code: def _training_stats(self):
      """
      Return a dictionary of statistics collected during creation of the
      model. These statistics are also available with the ``get`` method and
      are described in more detail in that method's documentation.
  
      Returns
      -------
      out : dict
          Dictionary of statistics compiled during creation of the
          TopicModel.
  
      See Also
      --------
      summary
  
      Examples
      --------
      >>> docs = turicreate.SArray('https://static.turi.com/datasets/nips-text')
      >>> m = turicreate.topic_model.create(docs)
      >>> m._training_stats()
      {'training_iterations': 20,
       'training_time': 20.5034}
      """
  
      fields = self._list_fields()
      stat_fields = ["training_time", "training_iterations"]
      if "validation_perplexity" in fields:
          stat_fields.append("validation_perplexity")
  
      ret = {k: self._get(k) for k in stat_fields}
      return ret
  
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 7 for calling the TopicModel obj's underlying member method code with example usage: obj._training_stats() and returns: ret