code: def __getitem__(self, index):
      sentence = torch.LongTensor(
          self.tokenizer.encode(
              self.data[index]["text"], add_special_tokens=True
          )
      )
      start_token, sentence, end_token = (
          sentence[0],
          sentence[1:-1],
          sentence[-1],
      )
      sentence = sentence[: self.max_seq_length]
  
      label = torch.zeros(self.n_classes)
      label[
          [self.labels.index(tgt) for tgt in self.data[index]["label"]]
      ] = 1
  
      image = Image.open(
          os.path.join(self.data_dir, self.data[index]["img"])
      ).convert("RGB")
      image = self.transforms(image)
  
      return {
          "image_start_token": start_token,
          "image_end_token": end_token,
          "sentence": sentence,
          "image": image,
          "label": label,
      }
  
imports: import json
  import os
  from collections import Counter
  import torch
  import torchvision
  import torchvision.transforms
  from PIL import Image
  from torch import nn
  from torch.utils.data import Dataset
label_desc: Use image node_id 3 for calling the JsonlDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: dict