code: def validate_rai_insights_for_non_large_data(
      self,
      model,
      train_data,
      test_data,
      target_column,
      categorical_features,
      task_type,
  ):
      rai_insights = RAIInsights(
          model,
          train_data,
          test_data,
          LABELS,
          categorical_features=categorical_features,
          task_type=task_type,
      )
  
      self.do_non_large_data_validations(rai_insights)
  
      with TemporaryDirectory() as tmpdir:
          path = Path(tmpdir) / "rai_test_path"
          # save the rai_insights
          rai_insights.save(path)
  
          self.validate_number_of_large_test_samples_on_save(
              rai_insights, path
          )
  
          # load the rai_insights
          rai_insights = RAIInsights.load(path)
  
          self.do_non_large_data_validations(rai_insights)
  
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 3 for calling the TestRAIInsightsNonLargeData obj's underlying member method code with example usage: obj.validate_rai_insights_for_non_large_data(model, train_data, test_data, target_column, categorical_features, task_type) without return types