code: def test_TransducerDecoder_cache_score():
      decoder = TransducerDecoder(10, rnn_type="gru")
  
      batch_state = decoder.init_state(3)
  
      hyps = [
          Hypothesis(
              score=0.0,
              yseq=[0],
              dec_state=decoder.select_state(batch_state, 0),
          )
      ]
  
      cache = {"0": hyps[0].dec_state}
      dec_out, _, _ = decoder.score(hyps[0], cache)
  
      batch_cache = {"0": (dec_out.view(1, 1, -1), hyps[0].dec_state)}
      _, _, _ = decoder.batch_score(
          hyps, batch_state, batch_cache, False
      )
  
file_path: espnet/test/espnet2/asr/decoder/test_transducer_decoder.py
imports: import pytest
  import torch
  from espnet2.asr.decoder.transducer_decoder import TransducerDecoder
  from espnet2.asr.transducer.beam_search_transducer import Hypothesis
label_desc: Use image node_id 5 for calling a global function with example usage: test_TransducerDecoder_cache_score() without return types