code: def test_save_load_pretrained_additional_features(self):
      processor = Wav2Vec2ProcessorWithLM(
          tokenizer=self.get_tokenizer(),
          feature_extractor=self.get_feature_extractor(),
          decoder=self.get_decoder(),
      )
      processor.save_pretrained(self.tmpdirname)
  
      # make sure that error is thrown when decoder alphabet doesn't match
      processor = Wav2Vec2ProcessorWithLM.from_pretrained(
          self.tmpdirname,
          alpha=5.0,
          beta=3.0,
          score_boundary=-7.0,
          unk_score_offset=3,
      )
  
      # decoder
      self.assertEqual(processor.language_model.alpha, 5.0)
      self.assertEqual(processor.language_model.beta, 3.0)
      self.assertEqual(processor.language_model.score_boundary, -7.0)
      self.assertEqual(processor.language_model.unk_score_offset, 3)
  
imports: import json
  import os
  import shutil
  import tempfile
  import unittest
  from multiprocessing import get_context
  from pathlib import Path
  import datasets
  import numpy
  from datasets import load_dataset
  from packaging import version
  from parameterized import parameterized
  from transformers import AutoProcessor
  from transformers.models.wav2vec2 import Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor
  from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_pyctcdecode, require_torch, require_torchaudio, slow
  from transformers.utils import FEATURE_EXTRACTOR_NAME, is_pyctcdecode_available, is_torch_available
  from ..wav2vec2.test_feature_extraction_wav2vec2 import floats_list
label_desc: Use image node_id 7 for calling the Wav2Vec2ProcessorWithLMTest obj's underlying member method code with example usage: obj.test_save_load_pretrained_additional_features() without return types