code: def register_refinement_rule(call_target):
      def register(fn):
          if call_target in _REFINEMENT_RULES:
              raise RuntimeError(
                  f"Refinement rule already registered for {call_target}!"
              )
          _REFINEMENT_RULES[call_target] = fn
          return fn
  
      return register
  
imports: from functools import reduce
  import torch
  import operator
  from torch.fx.tensor_type import Dyn, is_consistent, TensorType, is_more_precise
  from typing import Callable, Dict
  from torch.fx.node import Target, Node
  from torch.nn.modules.batchnorm import BatchNorm2d
  from torch.nn.modules.conv import Conv2d
  from torch.fx.experimental.refinement_types import Equality
  import itertools
  from torch.fx.experimental.unification import Var
  import sympy
label_desc: Use image node_id 4 for calling a global function with example usage: register_refinement_rule(call_target) and returns: register, fn