code: def test_out_dtype_non_functional(self):
      def f(x, y):
          return out_dtype(
              torch.ops.aten.add_.Tensor, torch.int32, x, y
          )
  
      with self.assertRaisesRegex(
          ValueError,
          "out_dtype's first argument needs to be a functional operator",
      ):
          _ = torch._export.export(
              f,
              (
                  torch.randint(-128, 127, (5, 5), dtype=torch.int8),
                  torch.randint(-128, 127, (5, 5), dtype=torch.int8),
              ),
          )
  
imports: import unittest
  import torch
  import torch._dynamo
  import torch._inductor
  import torch._inductor.decomposition
  import torch._export
  from torch._higher_order_ops.out_dtype import out_dtype
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing._internal.common_utils import run_tests, TestCase, IS_WINDOWS, TEST_WITH_ROCM, IS_FBCODE, IS_REMOTE_GPU, TEST_CUDA
  from torch.testing._internal.common_quantization import skipIfNoDynamoSupport
  from torch.testing import FileCheck
  from torch.testing._internal.common_cuda import SM80OrLater, _get_torch_cuda_version
label_desc: Use image node_id 6 for calling the TestOutDtypeOp obj's underlying member method code with example usage: obj.test_out_dtype_non_functional() and returns: out_dtype