docstr: Test multiple return from a single node (ex. layer_norm has 2 outputs)
docstr_tok: ["Test","multiple","return","from","a","single","node","(","ex",".","layer_norm","has","2","outputs",")"]
code: def test_multi_return(self) -> None:
      """
      Test multiple return from a single node (ex. layer_norm has 2 outputs)
      """
  
      class MyModule(torch.nn.Module):
          def __init__(self):
              super().__init__()
  
          def forward(self, x, w, b):
              return torch.nn.functional.layer_norm(
                  x,
                  x.size()[1:],
                  weight=w,
                  bias=b,
                  eps=1e-5,
              )
  
      inputs = (
          torch.ones([512, 512], requires_grad=True),
          torch.ones([512]),
          torch.ones([512]),
      )
      self.check_graph(MyModule(), inputs)
  
imports: import io
  import pathlib
  import tempfile
  import unittest
  import zipfile
  import torch
  import torch._dynamo
  from torch.export import export, save, load, Dim
  from torch._export.db.case import ExportCase, normalize_inputs, SupportLevel
  from torch._export.db.examples import all_examples
  from torch._export.serde.serialize import ExportedProgramDeserializer, ExportedProgramSerializer, canonicalize, deserialize, serialize, SerializeError
  from torch._subclasses.fake_tensor import FakeTensor
  from torch.fx.experimental.symbolic_shapes import is_concrete_int
  import torch.utils._pytree
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TestCase, TemporaryFileName, IS_FBCODE, IS_MACOS, IS_SANDCASTLE, IS_WINDOWS, find_library_location
label_desc: Use image node_id 2 for calling the TestDeserialize obj's underlying member method code with example usage: obj.test_multi_return() and returns: torch