code: def test_processor_from_auto_processor(self):
      processor_wav2vec2 = Wav2Vec2ProcessorWithLM.from_pretrained(
          "hf-internal-testing/processor_with_lm"
      )
      processor_auto = AutoProcessor.from_pretrained(
          "hf-internal-testing/processor_with_lm"
      )
  
      raw_speech = floats_list((3, 1000))
  
      input_wav2vec2 = processor_wav2vec2(
          raw_speech, return_tensors="np"
      )
      input_auto = processor_auto(raw_speech, return_tensors="np")
  
      for key in input_wav2vec2.keys():
          self.assertAlmostEqual(
              input_wav2vec2[key].sum(),
              input_auto[key].sum(),
              delta=1e-2,
          )
  
      logits = self._get_dummy_logits()
  
      decoded_wav2vec2 = processor_wav2vec2.batch_decode(logits)
      decoded_auto = processor_auto.batch_decode(logits)
  
      self.assertListEqual(decoded_wav2vec2.text, decoded_auto.text)
  
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 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 18 for calling the Wav2Vec2ProcessorWithLMTest obj's underlying member method code with example usage: obj.test_processor_from_auto_processor() without return types