class_docstr: PUBDEV-2980: kmeans return the field model._model_json['output']['summary']
  as null sometimes.  Normally, it is twoDimensionTable.  Sometimes, it is None.
  
  
  This class is created to train a kmeans model with different parameters settings and re-create two
  models with different field type for debugging purposes.
class_docstr_tok: ["PUBDEV-2980",":","kmeans","return","the","field","model._model_json","[","'output","'","]","[","'summary","'","]","as","null","sometimes",".","Normally",",","it","is","twoDimensionTable",".","Sometimes",",","it","is","None",".","This","class","is","created","to","train","a","kmeans","model","with","different","parameters","settings","and","re-create","two","models","with","different","field","type","for","debugging","purposes","."]
docstr: This function performs all initializations necessary:
  load the data sets and set the training set indices
docstr_tok: ["This","function","performs","all","initializations","necessary",":","load","the","data","sets","and","set","the","training","set","indices"]
code: def setup_data(self):
      """
      This function performs all initializations necessary:
      load the data sets and set the training set indices
      """
      self.training1_data = h2o.import_file(
          path=pyunit_utils.locate(self.training1_filenames)
      )
      self.x_indices = list(range(self.training1_data.ncol))
  
file_path: h2o-3/h2o-py/dynamic_tests/testdir_algos/kmeans/pyunit_PUBDEV_2980_kmeans_badfields_NOPASS.py
imports: import sys
  import random
  import os
  from builtins import range
  import time
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.kmeans import H2OKMeansEstimator
  from h2o.grid.grid_search import H2OGridSearch
label_desc: Use image node_id 2 for calling the Test_PUBDEV_2980_kmeans obj's underlying member method code with example usage: obj.setup_data() without return types