code: def setUp(self):
      super().setUp()
  
      vocab = "<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K ' X J Q Z".split(
          " "
      )
      vocab_tokens = dict(zip(vocab, range(len(vocab))))
  
      self.special_tokens_map = {
          "pad_token": "<pad>",
          "unk_token": "<unk>",
          "bos_token": "<s>",
          "eos_token": "</s>",
      }
  
      self.tmpdirname = tempfile.mkdtemp()
      self.vocab_file = os.path.join(
          self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"]
      )
      with open(self.vocab_file, "w", encoding="utf-8") as fp:
          fp.write(json.dumps(vocab_tokens) + "\n")
  
imports: import inspect
  import json
  import os
  import random
  import shutil
  import tempfile
  import unittest
  import numpy
  from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, Wav2Vec2Config, Wav2Vec2CTCTokenizer, Wav2Vec2Tokenizer
  from transformers.models.wav2vec2.tokenization_wav2vec2 import VOCAB_FILES_NAMES, Wav2Vec2CTCTokenizerOutput
  from transformers.testing_utils import require_torch, slow
  from ...test_tokenization_common import TokenizerTesterMixin
label_desc: Use image node_id 1 for calling the Wav2Vec2TokenizerTest obj's underlying member method code with example usage: obj.setUp() without return types