code: def get_diabetes_dataset(load_diabetes_dataset, framework):
      (x_train_diabetes, y_train_diabetes), (
          x_test_diabetes,
          y_test_diabetes,
      ) = load_diabetes_dataset
  
      x_train_diabetes_original = x_train_diabetes.copy()
      y_train_diabetes_original = y_train_diabetes.copy()
      x_test_diabetes_original = x_test_diabetes.copy()
      y_test_diabetes_original = y_test_diabetes.copy()
  
      yield (x_train_diabetes, y_train_diabetes), (
          x_test_diabetes,
          y_test_diabetes,
      )
  
      np.testing.assert_array_almost_equal(
          x_train_diabetes_original, x_train_diabetes, decimal=3
      )
      np.testing.assert_array_almost_equal(
          y_train_diabetes_original, y_train_diabetes, decimal=3
      )
      np.testing.assert_array_almost_equal(
          x_test_diabetes_original, x_test_diabetes, decimal=3
      )
      np.testing.assert_array_almost_equal(
          y_test_diabetes_original, y_test_diabetes, decimal=3
      )
  
imports: import importlib
  import json
  import logging
  import os
  import shutil
  import tempfile
  from typing import Dict, List, TYPE_CHECKING, Union
  import warnings
  import numpy
  import pytest
  import requests
  from art.data_generators import KerasDataGenerator, MXDataGenerator, PyTorchDataGenerator, TensorFlowDataGenerator, TensorFlowV2DataGenerator
  from art.defences.preprocessor import FeatureSqueezing, JpegCompression, SpatialSmoothing
  from art.estimators.classification import KerasClassifier
  from tests.utils import ARTTestFixtureNotImplemented, get_attack_classifier_pt, get_image_classifier_kr, get_image_classifier_kr_functional, get_image_classifier_kr_tf, get_image_classifier_kr_tf_functional, get_image_classifier_kr_tf_with_wildcard, get_image_classifier_mxnet_custom_ini, get_image_classifier_pt, get_image_classifier_pt_functional, get_image_classifier_tf, get_image_classifier_hf, get_image_gan_tf_v2, get_image_generator_tf_v2, get_tabular_classifier_kr, get_tabular_classifier_pt, get_tabular_classifier_scikit_list, get_tabular_classifier_tf, load_dataset, master_seed
label_desc: Use image node_id 28 for calling a global function with example usage: get_diabetes_dataset(load_diabetes_dataset, framework) without return types