code: def setUp(self):
      self.tmpdirname = tempfile.mkdtemp()
  
      vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest"]  # fmt: skip
      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]))
  
      image_processor_map = {
          "do_resize": True,
          "size": {"height": 18, "width": 18},
          "do_normalize": True,
          "image_mean": [0.5, 0.5, 0.5],
          "image_std": [0.5, 0.5, 0.5],
      }
      self.image_processor_file = os.path.join(
          self.tmpdirname, IMAGE_PROCESSOR_NAME
      )
      with open(self.image_processor_file, "w", encoding="utf-8") as fp:
          json.dump(image_processor_map, fp)
  
imports: import json
  import os
  import shutil
  import tempfile
  import unittest
  import numpy
  from transformers import BertTokenizerFast
  from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
  from transformers.testing_utils import require_tokenizers, require_vision
  from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available
label_desc: Use image node_id 1 for calling the VisionTextDualEncoderProcessorTest obj's underlying member method code with example usage: obj.setUp() without return types