class_docstr: An untargeted attack on classification models which attempts to minimize
  the score of the correct label until it is no longer the predicted label.
  
  Args:
      target_max_score (float): If set, goal is to reduce model output to
          below this score. Otherwise, goal is to change the overall predicted
          class.
class_docstr_tok: ["An","untargeted","attack","on","classification","models","which","attempts","to","minimize","the","score","of","the","correct","label","until","it","is","no","longer","the","predicted","label",".","Args",":","target_max_score","(","float",")",":","If","set",",","goal","is","to","reduce","model","output","to","below","this","score",".","Otherwise",",","goal","is","to","change","the","overall","predicted","class","."]
code: def _is_goal_complete(self, model_output, _):
      if self.target_max_score:
          return (
              model_output[self.ground_truth_output]
              < self.target_max_score
          )
      elif (model_output.numel() == 1) and isinstance(
          self.ground_truth_output, float
      ):
          return (
              abs(self.ground_truth_output - model_output.item()) >= 0.5
          )
      else:
          return model_output.argmax() != self.ground_truth_output
  
imports: from .classification_goal_function import ClassificationGoalFunction
label_desc: Use image node_id 2 for calling the UntargetedClassification obj's underlying member method code with example usage: obj._is_goal_complete(model_output, _) and returns: unknown, unknown, unknown