code: def test_issue_103924(self):
      class MyModule(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.temperature = 1
              self.layer = torch.nn.Softmax(dim=1)
  
          def forward(self, x):
              n_samples, _ = x.shape
              y = 1.0 * torch.ones(
                  n_samples, dtype=x.dtype, device=x.device
              )
              inp = x / y[..., None]
              return self.layer(inp)
  
      x = torch.rand([4, 4], device="cuda")
      m = MyModule()
      opt_m = torch.compile(backend="inductor")(m)
      self.assertEqual(opt_m(x), m(x))
  
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 27 for calling the CudaReproTests obj's underlying member method code with example usage: obj.test_issue_103924() and returns: self