code: def test_canonicalize(self) -> None:
      class Module(torch.nn.Module):
          def forward(
              self, x: torch.Tensor, y: torch.Tensor
          ) -> torch.Tensor:
              a = y + x
              b = x + y
              return b + a
  
      ep = torch.export.export(
          Module(), (torch.randn(3, 2), torch.randn(3, 2))
      )
      s = ExportedProgramSerializer().serialize(ep)
      c = canonicalize(s.exported_program)
      g = c.graph_module.graph
      self.assertLess(
          g.nodes[0].inputs[0].arg.as_tensor.name,
          g.nodes[1].inputs[0].arg.as_tensor.name,
      )
  
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 6 for calling the TestSerialize obj's underlying member method code with example usage: obj.test_canonicalize() and returns: unknown