code: def test_dynamic_to_static_cudagraphs(self):
      for b in [False, True]:
          with config.patch({"triton.cudagraph_trees": b}):
  
              @torch._dynamo.optimize("inductor")
              def fn(x, y):
                  r = x + y
                  return r, r.size(0)
  
              inputs = (
                  torch.randn((5, 5), device="cuda"),
                  torch.randn((5, 5), device="cuda"),
              )
              self.assertTrue(
                  same(fn(*inputs), (inputs[0] + inputs[1], 5))
              )
  
              inputs = (
                  torch.randn((6, 6), device="cuda"),
                  torch.randn((6, 6), device="cuda"),
              )
              self.assertTrue(
                  same(fn(*inputs), (inputs[0] + inputs[1], 6))
              )
  
imports: import math
  import sys
  import unittest
  import torch
  import torch._dynamo.config
  import torch.backends.cuda
  import torch.nn.functional
  from torch import nn
  from torch._dynamo.debug_utils import same_two_models
  from torch._dynamo.testing import rand_strided
  from torch._dynamo.utils import same
  from torch._inductor import config
  from torch._inductor.compile_fx import compile_fx_inner
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing._internal.common_cuda import PLATFORM_SUPPORTS_FLASH_ATTENTION
  from torch.testing._internal.common_utils import DeterministicGuard, freeze_rng_state, IS_FBCODE, skipIfRocm, TEST_WITH_ASAN
label_desc: Use image node_id 8 for calling the CudaReproTests obj's underlying member method code with example usage: obj.test_dynamic_to_static_cudagraphs() and returns: r,  r