class_docstr: Create a Python wrapper around `language_model` to feed to the decoder.
class_docstr_tok: ["Create","a","Python","wrapper","around","`","language_model","`","to","feed","to","the","decoder","."]
code: def finish(self, state: CTCDecoderLMState):
      return self.score(state, self.sil)
  
imports: import torch
  import torchaudio
  import time
  from typing import List
  import IPython
  import matplotlib.pyplot
  from torchaudio.models.decoder import ctc_decoder
  from torchaudio.utils import download_asset
  from torchaudio.models.decoder import CTCDecoderLM, CTCDecoderLMState
  from torchaudio.models.decoder import download_pretrained_files
label_desc: Use image node_id 4 for calling the CustomLM obj's underlying member method code with example usage: obj.finish(state) and returns: self