class_docstr: NeuralEngine takes a list of hooks and executes them in their topological order. The
  topological order of the hooks is determined by their required inputs and outputs.
class_docstr_tok: ["NeuralEngine","takes","a","list","of","hooks","and","executes","them","in","their","topological","order",".","The","topological","order","of","the","hooks","is","determined","by","their","required","inputs","and","outputs","."]
code: def set_execution_order_func(self, func):
      self.execution_order_func = func
  
file_path: pytorchvideo/pytorchvideo/neural_engine/engine.py
imports: import itertools
  from collections import OrderedDict
  from typing import List, Union
  import networkx
  from pytorchvideo.neural_engine import HookBase
label_desc: Use image node_id 3 for calling the NeuralEngine obj's underlying member method code with example usage: obj.set_execution_order_func(func) without return types