class_docstr: Class which converts the supplied pytorch model into an equivalent model
  which uses abstract operations
class_docstr_tok: ["Class","which","converts","the","supplied","pytorch","model","into","an","equivalent","model","which","uses","abstract","operations"]
docstr: Helper function to set the forward mode of the model
  
  :param mode: either concrete or abstract signifying how to run the forward pass
docstr_tok: ["Helper","function","to","set","the","forward","mode","of","the","model",":","param","mode",":","either","concrete","or","abstract","signifying","how","to","run","the","forward","pass"]
code: def set_forward_mode(self, mode: str) -> None:
      """
      Helper function to set the forward mode of the model
  
      :param mode: either concrete or abstract signifying how to run the forward pass
      """
      assert mode in {"concrete", "abstract"}
      self.forward_mode = mode
  
imports: from typing import List, Optional, Tuple, Union, Callable, Any, TYPE_CHECKING
  import logging
  import math
  import warnings
  import sys
  import numpy
  import torch
  from art.estimators.certification.deep_z.deep_z import ZonoConv, ZonoDenseLayer, ZonoReLU, ZonoBounds
  from art.estimators.classification.pytorch import PyTorchClassifier
label_desc: Use image node_id 5 for calling the ConvertedModel obj's underlying member method code with example usage: obj.set_forward_mode(mode) without return types