code: def __getitem__(self, index):
      ann = copy.deepcopy(self.annotation[index])
      for modality in self.modalities:
          ann[f"{modality}_path"] = getattr(
              self, f"get_{modality}_path"
          )(ann["image_id"])
  
          if type(ann[f"{modality}_path"]) == list:
              ann[f"{modality}_path"] = random.choice(
                  ann[f"{modality}_path"]
              )
          if "image" in modality:
              ann["image"] = self.vis_processor(
                  Image.open(ann[f"images_path"])
              )
          else:
              ann[modality] = getattr(self, f"{modality}_processor")(
                  ann[f"{modality}_path"]
              ).to(torch.float32)
  
      ann["sample_id"] = ann["image_id"]
      dialog = ""
      for t in ann["dialog"]:
          dialog += f"{t['question']} {t['answer']} "
      ann["dialog"] = dialog
      ann["text_output"] = self.text_processor(ann["answer"])
      ann["text_input"] = self.text_processor(ann["question"])
      ann["question_id"] = index
      # ann['captions'] = ann[ann['answer']] # commented out for test dataset
      return ann
  
imports: import torch
  import os
  import copy
  import random
  from PIL import Image
  from lavis.datasets.datasets.dialogue_datasets import DialogueDataset, DialogueEvalDataset
label_desc: Use image node_id 6 for calling the AVSDDialInstructEvalDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: ann