code: def get_attr_inference_rule(n: Node, traced):
      """
      The current getattr rule only handles the shape attribute
      Can be extended to other attributes
      The most representitive type we have is "Dyn" but the system
      can be extended with more types, such as a type to represent shapes
      """
      attr_node = n.args[0]
      attr_name = n.args[1]
  
      if attr_name == "shape":
          n.type = Dyn
      else:
          raise TypeError("Not yet implemented")
  
      # TODO. We leave it like this till we add a type to represent tensor sizes
      return n.type
  
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 7 for calling a global function with example usage: get_attr_inference_rule(n, traced) and returns: n