code: def test_black_box_loss_regression_pred(
      art_warning, model_type, get_diabetes_dataset
  ):
      try:
          from sklearn import linear_model
  
          (x_train_diabetes, y_train_diabetes), (
              x_test_diabetes,
              _,
          ) = get_diabetes_dataset
          regr_model = linear_model.LinearRegression()
          regr_model.fit(x_train_diabetes, y_train_diabetes)
          regressor = ScikitlearnRegressor(regr_model)
          pred_x = regr_model.predict(x_train_diabetes)
          test_pred_x = regr_model.predict(x_test_diabetes)
          pred = (pred_x, test_pred_x)
          attack = MembershipInferenceBlackBox(
              regressor, input_type="loss", attack_model_type=model_type
          )
          backend_check_membership_accuracy_pred(
              attack,
              get_diabetes_dataset,
              pred,
              attack_train_ratio,
              0.25,
          )
      except ARTTestException as e:
          art_warning(e)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import pytest
  import numpy
  import keras
  from art.attacks.inference.membership_inference.black_box import MembershipInferenceBlackBox
  from art.estimators.classification.keras import KerasClassifier
  from art.estimators.estimator import BaseEstimator
  from art.estimators.classification.classifier import ClassifierMixin
  from art.estimators.regression import ScikitlearnRegressor, RegressorMixin
  from tests.attacks.utils import backend_test_classifier_type_check_fail
  from tests.utils import ARTTestException
label_desc: Use image node_id 17 for calling a global function with example usage: test_black_box_loss_regression_pred(art_warning, model_type, get_diabetes_dataset) without return types