code: def __init__(self, data_path, re_path, args):
      self.args = args
      self.data_path = data_path
      self.re_path = re_path
      self.tokenizer = BertTokenizer.from_pretrained(
          args.bert_name, do_lower_case=True
      )
      self.tokenizer.add_special_tokens(
          {"additional_special_tokens": ["<s>", "</s>", "<o>", "</o>"]}
      )
  
      self.clip_processor = CLIPProcessor.from_pretrained(args.vit_name)
      self.aux_processor = CLIPProcessor.from_pretrained(args.vit_name)
      (
          self.aux_processor.feature_extractor.size,
          self.aux_processor.feature_extractor.crop_size,
      ) = (args.aux_size, args.aux_size)
      self.rcnn_processor = CLIPProcessor.from_pretrained(args.vit_name)
      (
          self.rcnn_processor.feature_extractor.size,
          self.rcnn_processor.feature_extractor.crop_size,
      ) = (args.rcnn_size, args.rcnn_size)
  
file_path: DeepKE/src/deepke/relation_extraction/multimodal/modules/dataset.py
imports: import random
  import os
  import torch
  import json
  import ast
  from PIL import Image
  from torch.utils.data import Dataset
  from transformers import BertTokenizer, CLIPProcessor
  import logging
label_desc: Use image node_id 1 to create a new MMREProcessor object from inherited base classes: object with example: obj = MMREProcessor(data_path, re_path, args)