code: def print_decoded(
      cuda_decoder,
      bpe_model,
      log_prob,
      encoder_out_lens,
      param,
      param_value,
  ):
      start_time = time.monotonic()
      results = cuda_decoder(log_prob, encoder_out_lens.to(torch.int32))
      decode_time = time.monotonic() - start_time
      transcript = bpe_model.decode(results[0][0].tokens).lower()
      score = results[0][0].score
      print(
          f"{param} {param_value:<3}: {transcript} (score: {score:.2f}; {decode_time:.4f} secs)"
      )
  
file_path: audio/examples/tutorials/asr_inference_with_cuda_ctc_decoder_tutorial.py
imports: import torch
  import torchaudio
  import time
  from pathlib import Path
  import IPython
  import sentencepiece
  from torchaudio.models.decoder import cuda_ctc_decoder
  from torchaudio.utils import download_asset
label_desc: Use image node_id 2 for calling a global function with example usage: print_decoded(cuda_decoder, bpe_model, log_prob, encoder_out_lens, param, param_value) without return types