code: def do_non_large_data_validations(self, rai_insights):
      assert rai_insights._large_test is None
      assert rai_insights._large_predict_output is None
      assert rai_insights._large_predict_proba_output is None
      dataset = rai_insights._get_dataset()
      assert not dataset.is_large_data_scenario
      assert not dataset.use_entire_test_data
  
      filtered_small_data = rai_insights.get_filtered_test_data(
          [], [], use_entire_test_data=False
      )
      assert len(filtered_small_data) == len(rai_insights.test)
  
      filtered_large_data = rai_insights.get_filtered_test_data(
          [], [], use_entire_test_data=True
      )
      assert len(filtered_large_data) == len(rai_insights.test)
  
imports: import json
  from pathlib import Path
  from tempfile import TemporaryDirectory
  import pandas
  import pytest
  from tests.common_utils import create_iris_data
  from rai_test_utils.datasets.tabular import create_housing_data
  from rai_test_utils.models.sklearn import create_sklearn_random_forest_classifier, create_sklearn_random_forest_regressor
  from responsibleai import RAIInsights
  from responsibleai._interfaces import Dataset, TabularDatasetMetadata
label_desc: Use image node_id 1 for calling the TestRAIInsightsNonLargeData obj's underlying member method code with example usage: obj.do_non_large_data_validations(rai_insights) without return types