code: def test_mutation(self):
      class Mod(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.mutated_param = torch.nn.Parameter(
                  torch.zeros([10, 10])
              )
  
          def forward(self):
              self.mutated_param.add_(10)
              return self.mutated_param
  
      with torch.no_grad():
          mod = Mod().to(self.device)
          out_eager = mod()
          out_eager2 = mod()
  
          mod = Mod().to(self.device)
  
          @torch.compile
          def foo(mod):
              return mod()
  
          out_comp = foo(mod)
          out_comp2 = foo(mod)
  
          self.assertEqual(out_eager, out_comp)
          self.assertEqual(out_eager2, out_comp2)
  
imports: import contextlib
  import functools
  import importlib
  import itertools
  import os
  import sys
  import unittest
  import weakref
  import torch
  from torch import nn
  from torch._inductor import config
  from torch._inductor.utils import override_lowering, run_and_get_code
  from torch.testing import FileCheck
  from torch.testing._internal.common_cuda import SM80OrLater
  from torch.testing._internal.common_utils import IS_CI, IS_WINDOWS, TEST_WITH_ASAN, TEST_WITH_ROCM, TestCase
  from inductor.test_torchinductor import check_model, check_model_cuda, copy_tests
  from torch.testing._internal.inductor_utils import HAS_CPU, HAS_CUDA
label_desc: Use image node_id 1 for calling the OptimizeForInferenceTemplate obj's underlying member method code with example usage: obj.test_mutation() and returns: self, mod