code: def setUp(self):
      vocab_tokens = [
          "[UNK]",
          "[CLS]",
          "[SEP]",
          "[PAD]",
          "[MASK]",
          "want",
          "##want",
          "##ed",
          "wa",
          "un",
          "runn",
          "##ing",
          ",",
          "low",
          "lowest",
      ]
  
      image_processor_map = {
          "do_resize": True,
          "size": 224,
          "apply_ocr": True,
      }
  
      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 vocab_writer:
          vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
      self.image_processing_file = os.path.join(
          self.tmpdirname, FEATURE_EXTRACTOR_NAME
      )
      with open(
          self.image_processing_file, "w", encoding="utf-8"
      ) as fp:
          fp.write(json.dumps(image_processor_map) + "\n")
  
imports: import json
  import os
  import shutil
  import tempfile
  import unittest
  from typing import List
  import numpy
  from transformers import PreTrainedTokenizer, PreTrainedTokenizerBase, PreTrainedTokenizerFast
  from transformers.models.layoutlmv2 import LayoutLMv2Tokenizer, LayoutLMv2TokenizerFast
  from transformers.models.layoutlmv2.tokenization_layoutlmv2 import VOCAB_FILES_NAMES
  from transformers.testing_utils import require_pytesseract, require_tokenizers, require_torch, slow
  from transformers.utils import FEATURE_EXTRACTOR_NAME, cached_property, is_pytesseract_available
label_desc: Use image node_id 1 for calling the LayoutLMv2ProcessorTest obj's underlying member method code with example usage: obj.setUp() without return types