code: def _makeEvalResults(self):
      result_a = view_types.EvalResult(
          slicing_metrics=self._makeTestData(),
          plots=None,
          attributions=None,
          config=config_pb2.EvalConfig(),
          data_location=self.data_location_1,
          file_format="tfrecords",
          model_location=self.model_location_1,
      )
      result_b = view_types.EvalResult(
          slicing_metrics=[self.result_c2],
          plots=None,
          attributions=None,
          config=config_pb2.EvalConfig(),
          data_location=self.full_data_location_2,
          file_format="tfrecords",
          model_location=self.full_model_location_2,
      )
      return view_types.EvalResults(
          [result_a, result_b], constants.MODEL_CENTRIC_MODE
      )
  
imports: import os
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.slicer.slicer_lib import OVERALL_SLICE_NAME
  from tensorflow_model_analysis.slicer.slicer_lib import SingleSliceSpec
  from tensorflow_model_analysis.view import util
  from tensorflow_model_analysis.view import view_types
  from google.protobuf import text_format
label_desc: Use image node_id 3 for calling the UtilTest obj's underlying member method code with example usage: obj._makeEvalResults() and returns: view_types