code: def test_double_nested_submodule(self):
      class SubSubMod(torch.nn.Module):
          def __init__(self):
              super().__init__()
  
          def forward(self, x):
              return x * x
  
      class SubMod(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.subsubmod = SubSubMod()
  
          def forward(self, x):
              return x - x
  
      class MyModule(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.submod = SubMod()
  
          def forward(self, x):
              return x + self.submod.subsubmod(x)
  
      orig_eager = MyModule()
      export_module = torch.export.export(
          orig_eager, (torch.rand(2, 3),), {}
      )
      unflattened = unflatten(export_module)
  
      inputs = (torch.rand(2, 3),)
      self.compare_outputs(orig_eager, unflattened, inputs)
  
imports: import dataclasses
  import unittest
  from contextlib import contextmanager
  from dataclasses import dataclass
  from typing import List, Any
  import torch
  import torch._dynamo
  from functorch.experimental.control_flow import cond, map
  from torch import Tensor
  from torch.export import Constraint, Dim, dynamic_dim, export, unflatten, FlatArgsAdapter
  from torch.export._trace import DEFAULT_EXPORT_DYNAMO_CONFIG
  from torch._export import capture_pre_autograd_graph
  from torch._export.utils import get_buffer, get_param, is_buffer, is_param, register_dataclass_as_pytree_node
  from torch.export import Constraint, Dim, export
  from torch.fx.experimental.proxy_tensor import make_fx
  from torch.testing import FileCheck
  from torch.testing._internal.common_utils import run_tests, TestCase
  from torch.utils._pytree import LeafSpec, tree_flatten, tree_unflatten, TreeSpec, treespec_dumps, treespec_loads
label_desc: Use image node_id 11 for calling the TestUnflatten obj's underlying member method code with example usage: obj.test_double_nested_submodule() and returns: unknown, unknown, unknown