code: def prepare_processor_dict(self):
      image_processor_dict = {
          "do_resize": self.do_resize,
          "size": self.size,
          "do_normalize": self.do_normalize,
          "image_mean": self.image_mean,
          "image_std": self.image_std,
          "num_labels": self.num_labels,
          "reduce_labels": self.reduce_labels,
          "ignore_index": self.ignore_index,
          "class_info_file": self.class_info_file,
          "metadata": self.metadata,
          "num_text": self.num_text,
      }
  
      image_processor = OneFormerImageProcessor(**image_processor_dict)
      tokenizer = CLIPTokenizer.from_pretrained(self.model_repo)
  
      return {
          "image_processor": image_processor,
          "tokenizer": tokenizer,
          "max_seq_length": self.max_seq_length,
          "task_seq_length": self.task_seq_length,
      }
  
imports: import json
  import os
  import tempfile
  import unittest
  import numpy
  from datasets import load_dataset
  from huggingface_hub import hf_hub_download
  from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_vision
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_image_processing_common import prepare_image_inputs
label_desc: Use image node_id 2 for calling the OneFormerProcessorTester obj's underlying member method code with example usage: obj.prepare_processor_dict() and returns: dict