code: def test_iris_clipped(self):
      (_, _), (x_test, y_test) = self.iris
  
      classifier = get_tabular_classifier_kr()
      classifier = QueryEfficientGradientEstimationClassifier(
          classifier, 20, 1 / 64.0, round_samples=1 / 255.0
      )
  
      # Test untargeted attack
      attack = FastGradientMethod(classifier, eps=0.1)
      x_test_adv = attack.generate(x_test)
      self.assertFalse((x_test == x_test_adv).all())
      self.assertTrue((x_test_adv <= 1).all())
      self.assertTrue((x_test_adv >= 0).all())
  
      preds_adv = np.argmax(classifier.predict(x_test_adv), axis=1)
      self.assertFalse((np.argmax(y_test, axis=1) == preds_adv).all())
  
imports: import logging
  import unittest
  import keras.backend
  import numpy
  from art.attacks.evasion.fast_gradient import FastGradientMethod
  from art.estimators.classification.keras import KerasClassifier
  from art.defences.preprocessor import FeatureSqueezing
  from art.utils import load_dataset, get_labels_np_array
  from art.estimators.classification.query_efficient_bb import QueryEfficientGradientEstimationClassifier
  from tests.utils import master_seed, get_image_classifier_kr, get_tabular_classifier_kr
label_desc: Use image node_id 3 for calling the TestQueryEfficientVectors obj's underlying member method code with example usage: obj.test_iris_clipped() without return types