code: def all_eq(n: Node):
      """
      For operations where the input shape is equal to the output shape
      """
      res = []
      assert isinstance(n.args[0], Node)
      arg_type = n.args[0].type
      if isinstance(arg_type, TensorType) and isinstance(
          n.type, TensorType
      ):
          args1 = arg_type.__args__
          args2 = n.type.__args__
          res = [
              Equality(args1[i], args2[i]) for i in range(len(args1))
          ]
      return res
  
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 25 for calling a global function with example usage: all_eq(n) and returns: res