code: def predictions(self, image, strict=True, return_details=False):
          
          in_bounds = self.in_bounds(image)
          assert not strict or in_bounds
  
          self._total_prediction_calls += 1
          predictions = self.__model.predictions(image)
          is_adversarial, is_best, distance = self.__is_adversarial(
              image, predictions, in_bounds)
  
          assert predictions.ndim == 1
          if return_details:
              return predictions, is_adversarial, is_best, distance
          else:
              return predictions, is_adversarial
docs: Interface to model.predictions for attacks.
  
          Parameters
          ----------
          image : `numpy.ndarray`
              Single input with shape as expected by the model
              (without the batch dimension).
          strict : bool
              Controls if the bounds for the pixel values should be checked.