code: def test_basic(self):
      def fn():
          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 2 for calling the TestCompiledAutograd obj's underlying member method code with example usage: obj.test_basic() without return types