code: def test_torchscript_input_output_trace():
      """Test that traced LightningModule forward works with example_inputs."""
      model = BoringModel()
      example_inputs = torch.randn(1, 32)
      script = model.to_torchscript(
          example_inputs=example_inputs, method="trace"
      )
      assert isinstance(script, torch.jit.ScriptModule)
  
      model.eval()
      with torch.no_grad():
          model_output = model(example_inputs)
  
      script_output = script(example_inputs)
      assert torch.allclose(script_output, model_output)
  
imports: import os
  import fsspec
  import pytest
  import torch
  from fsspec.implementations.local import LocalFileSystem
  from lightning.fabric.utilities.cloud_io import get_filesystem
  from lightning.pytorch.core.module import LightningModule
  from lightning.pytorch.demos.boring_classes import BoringModel
  from tests_pytorch.helpers.advanced_models import BasicGAN, ParityModuleRNN
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 3 for calling a global function with example usage: test_torchscript_input_output_trace() without return types