code: def __init__(self, data_path, args) -> None:
      self.data_path = data_path
      self.tokenizer = BertTokenizer.from_pretrained(
          args.bert_name, do_lower_case=True
      )
      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)
      self.cwd = args.cwd
  
file_path: DeepKE/src/deepke/name_entity_re/multimodal/modules/dataset.py
imports: import torch
  import os
  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 MMPNERProcessor object from inherited base classes: object with example: obj = MMPNERProcessor(data_path, args)