code: def test_accumulate_without_zero(self):
      def fn():
          model = torch.nn.Sequential(
              torch.nn.Linear(4, 4),
              torch.nn.ReLU(),
              torch.nn.Linear(4, 4),
              torch.nn.ReLU(),
          )
          opt_model = torch.compile(model, dynamic=True)
  
          for _ in range(10):
              x = torch.randn([10, 4])
              result = opt_model(x).sum()
              result.backward()
              yield model[0].weight.grad.clone()
              yield model[0].bias.grad.clone()
              yield model[2].weight.grad.clone()
              yield model[2].bias.grad.clone()
  
      self.check_output_and_recompiles(fn, count=2)
  
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 11 for calling the TestCompiledAutograd obj's underlying member method code with example usage: obj.test_accumulate_without_zero() without return types