code: def get_rel2id(self, train_path):
      with open(
          os.path.join(self.args.cwd, self.re_path),
          "r",
          encoding="utf-8",
      ) as f:
          line = f.readlines()[0]
          re_dict = json.loads(line)
      re2id = {key: [] for key in re_dict.keys()}
      with open(train_path, "r", encoding="utf-8") as f:
          lines = f.readlines()
          for i, line in enumerate(lines):
              line = ast.literal_eval(line)  # str to dict
              assert line["relation"] in re2id
              re2id[line["relation"]].append(i)
      return re2id
  
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 4 for calling the MMREProcessor obj's underlying member method code with example usage: obj.get_rel2id(train_path) and returns: re2id