code: def test_module_info_flatbuffer(self):
      class Foo(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.foo = torch.nn.Linear(2, 2)
              self.bar = torch.nn.Linear(2, 2)
  
          def forward(self, x):
              x = self.foo(x)
              x = self.bar(x)
              return x
  
      first_script_module = torch.jit.script(Foo())
      first_saved_module = io.BytesIO()
      torch.jit.save_jit_module_to_flatbuffer(
          first_script_module, first_saved_module
      )
      first_saved_module.seek(0)
      ff_info = torch.jit._serialization.get_flatbuffer_module_info(
          first_saved_module
      )
      self.assertEqual(ff_info["bytecode_version"], 9)
      self.assertEqual(ff_info["operator_version"], 1)
      self.assertEqual(ff_info["type_names"], set())
      self.assertEqual(
          ff_info["opname_to_num_args"], {"aten::linear": 3}
      )
  
      self.assertEqual(len(ff_info["function_names"]), 1)
      self.assertTrue(
          next(iter(ff_info["function_names"])).endswith("forward")
      )
  
imports: import io
  import os
  import pathlib
  import sys
  from typing import NamedTuple, Optional
  import torch
  from torch import Tensor
  from torch.testing._internal.common_utils import TemporaryFileName
  from torch.testing._internal.jit_utils import JitTestCase, clear_class_registry
label_desc: Use image node_id 8 for calling the TestSaveLoadFlatbuffer obj's underlying member method code with example usage: obj.test_module_info_flatbuffer() and returns: x