code: def test(self, audio_file):
      self.model.eval()
      cfg = self.config.decoding
      collate_fn_test = self.collate_fn_test
      audio, _ = collate_fn_test.process_utterance(
          audio_file=audio_file, transcript="Hello"
      )
      audio_len = audio.shape[0]
      audio = paddle.to_tensor(audio, dtype="float32")
      audio_len = paddle.to_tensor(audio_len)
      audio = paddle.unsqueeze(audio, axis=0)
      vocab_list = collate_fn_test.vocab_list
  
      text_feature = self.collate_fn_test.text_feature
      result_transcripts = self.model.decode(
          audio,
          audio_len,
          text_feature=text_feature,
          decoding_method=cfg.decoding_method,
          lang_model_path=cfg.lang_model_path,
          beam_alpha=cfg.alpha,
          beam_beta=cfg.beta,
          beam_size=cfg.beam_size,
          cutoff_prob=cfg.cutoff_prob,
          cutoff_top_n=cfg.cutoff_top_n,
          num_processes=cfg.num_proc_bsearch,
          ctc_weight=cfg.ctc_weight,
          decoding_chunk_size=cfg.decoding_chunk_size,
          num_decoding_left_chunks=cfg.num_decoding_left_chunks,
          simulate_streaming=cfg.simulate_streaming,
      )
  
      return result_transcripts
  
file_path: PaddleHub/modules/audio/asr/u2_conformer_librispeech/u2_conformer_tester.py
imports: import os
  import sys
  import paddle
  from deepspeech.frontend.featurizer.text_featurizer import TextFeaturizer
  from deepspeech.io.collator import SpeechCollator
  from deepspeech.models.u2 import U2Model
  from deepspeech.utils import mp_tools
  from deepspeech.utils.utility import UpdateConfig
label_desc: Use image node_id 2 for calling the U2ConformerTester obj's underlying member method code with example usage: obj.test(audio_file) and returns: result_transcripts