code: def test_multi_output_layout_fallback(self):
      mod = nn.RReLU(lower=3.2350976, upper=8.4220314, inplace=True)
      inp = torch.rand([4, 4]).cuda()
      m = torch.compile(mod)
  
      with freeze_rng_state():
          o1 = m(inp.clone())
  
      o2 = mod(inp.clone())
  
      self.assertEqual(o1, o2)
  
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 44 for calling the CudaReproTests obj's underlying member method code with example usage: obj.test_multi_output_layout_fallback() without return types