code: def get_lightning_module(args):
      sp_model = spm.SentencePieceProcessor(
          model_file=str(args.sp_model_path)
      )
      if args.modality == "audiovisual":
          from lightning_av import AVConformerRNNTModule
  
          model = AVConformerRNNTModule(args, sp_model)
      else:
          from lightning import ConformerRNNTModule
  
          model = ConformerRNNTModule(args, sp_model)
      ckpt = torch.load(
          args.checkpoint_path,
          map_location=lambda storage, loc: storage,
      )["state_dict"]
      model.load_state_dict(ckpt)
      model.eval()
      return model
  
file_path: audio/examples/avsr/eval.py
imports: import logging
  from argparse import ArgumentParser
  import sentencepiece
  import torch
  import torchaudio
  from transforms import get_data_module
label_desc: Use image node_id 2 for calling a global function with example usage: get_lightning_module(args) and returns: model