code: def test_named_seq(backend, io_type, named_layers):
      if named_layers:
          model = SeqModelNamedLayers()
      else:
          model = SeqModelUnnamedLayers()
      config = config_from_pytorch_model(model)
      output_dir = str(
          test_root_path
          / f"hls4mlprj_pytorch_seq_named_{backend}_{io_type}_{named_layers}"
      )
  
      convert_from_pytorch_model(
          model,
          (None, 1, 5, 5),
          hls_config=config,
          output_dir=output_dir,
          backend=backend,
          io_type=io_type,
      )
  
file_path: hls4ml/test/pytest/test_sequential_parsing_pytorch.py
imports: from collections import OrderedDict
  from pathlib import Path
  import pytest
  import torch.nn
  from hls4ml.converters import convert_from_pytorch_model
  from hls4ml.utils.config import config_from_pytorch_model
label_desc: Use image node_id 2 for calling a global function with example usage: test_named_seq(backend, io_type, named_layers) without return types