code: def test_cache_hit(self):
      def fn():
          for _ in range(3):
              model = torch.nn.Sequential(
                  torch.nn.Linear(4, 4),
                  torch.nn.ReLU(),
                  torch.nn.Linear(4, 4),
                  torch.nn.ReLU(),
              )
              x = torch.randn([2, 4])
              result = model(x).sum()
              result.backward()
              yield model[0].weight.grad
              yield model[0].bias.grad
              yield model[2].weight.grad
              yield model[2].bias.grad
  
      self.check_output_and_recompiles(fn)
  
imports: import functools
  import re
  import sys
  import unittest
  from importlib.machinery import SourceFileLoader
  from pathlib import Path
  from unittest import mock
  import torch
  import torch.nn
  from torch import _inductor
  from torch._dynamo import compiled_autograd
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.utils import counters
  from torch.testing._internal.inductor_utils import HAS_CPU, HAS_CUDA
label_desc: Use image node_id 3 for calling the TestCompiledAutograd obj's underlying member method code with example usage: obj.test_cache_hit() without return types