code: def test_torchscript_example_input_output_trace(modelclass):
      """Test that traced LightningModule forward works with example_input_array."""
      torch.manual_seed(1)
      model = modelclass()
  
      if isinstance(model, BoringModel):
          model.example_input_array = torch.randn(5, 32)
  
      script = model.to_torchscript(method="trace")
      assert isinstance(script, torch.jit.ScriptModule)
  
      model.eval()
      with torch.no_grad():
          model_output = model(model.example_input_array)
  
      script_output = script(model.example_input_array)
      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 2 for calling a global function with example usage: test_torchscript_example_input_output_trace(modelclass) without return types