code: def test_inplace_add_alpha_autotune(self):
      def fn(x, y):
          aten.add_.Tensor(x, y, alpha=0.55)
          return (x,)
  
      x1 = torch.zeros(2, 3, 4, 10, device="cuda")
      x2 = torch.zeros(2, 3, 4, 10, device="cuda")
      x3 = torch.zeros(2, 3, 4, 10, device="cuda")
      y = torch.randn(2, 3, 4, 10, device="cuda").to(
          memory_format=torch.channels_last
      )
      fn_fx = make_fx(fn)(x1, y)
      fn_compiled = compile_fx_inner(fn_fx, [x1, y])
      fn(x2, y)
      fn_compiled([x3, y])
      assert same(x2, x3)
  
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 22 for calling the CudaReproTests obj's underlying member method code with example usage: obj.test_inplace_add_alpha_autotune() and returns: x