code: def test_fake_tensor_mode_simple(self):
      class Model(torch.nn.Module):
          def __init__(self) -> None:
              super().__init__()
              self.linear = torch.nn.Linear(2, 2)
  
          def forward(self, x):
              out = self.linear(x)
              return out
  
      with torch.onnx.enable_fake_mode() as fake_context:
          x = torch.rand(5, 2, 2)
          model = Model()
          export_options = ExportOptions(fake_context=fake_context)
          onnx_program = torch.onnx.dynamo_export(
              model, x, export_options=export_options
          )
  
      assert (
          onnx_program is not None
      ), "ONNXProgram must be created on successful export"
      assert (
          onnx_program.model_proto is not None
      ), "A model protobuf must be created on a successful export"
      onnx.checker.check_model(
          onnx_program.model_proto, full_check=True
      )
      assert (
          len(onnx_program.model_proto.graph.initializer) == 0
      ), "Initializers cannot exist when fake mode is enabled"
  
      # Variant 1: Save ONNX proto using Model's state_dict()
      with tempfile.NamedTemporaryFile(suffix=".onnx") as tmp_onnx_file:
          model_state_dict = (
              Model().state_dict()
          )  # Create a state_dict for testing
          onnx_program.save(
              tmp_onnx_file.name, model_state_dict=model_state_dict
          )
          assert (
              len(onnx.load(tmp_onnx_file.name).graph.initializer) == 2
          ), "Initializers must be present after loading it from model_state_dict"
  
      # Variant 2: Save ONNX proto using Model checkpoint file
      with tempfile.NamedTemporaryFile(
          suffix=".onnx"
      ) as tmp_onnx_file, tempfile.NamedTemporaryFile(
          suffix=".pt"
      ) as tmp_checkpoint_file:
          torch.save(
              Model().state_dict(), tmp_checkpoint_file.name
          )  # Create checkpoint file for testing
          onnx_program.save(
              tmp_onnx_file.name,
              model_state_dict=tmp_checkpoint_file.name,
          )
          assert (
              len(onnx.load(tmp_onnx_file.name).graph.initializer) == 2
          ), "Initializers must be present after loading it from model_state_dict"
  
imports: from __future__ import annotations
  import io
  import tempfile
  from typing import Mapping, Tuple
  import onnx
  import pytorch_test_common
  import torch
  import transformers
  from torch import nn
  from torch._subclasses import fake_tensor
  from torch.nn import functional
  from torch.onnx import dynamo_export, ExportOptions
  from torch.onnx._internal.diagnostics import infra
  from torch.onnx._internal.fx import diagnostics, registration
  from torch.testing._internal import common_utils
label_desc: Use image node_id 18 for calling the TestFxToOnnx obj's underlying member method code with example usage: obj.test_fake_tensor_mode_simple() and returns: out