code: def process_text(
      self,
      ann,
      data_debug_path=None,
      data_debug_counter=0,
      first_message=True,
  ):
      all_captions = ann["sentences"]
      if not isinstance(all_captions, list):
          all_captions = [all_captions]
      caption = random.choice(all_captions)
      caption = caption["raw"]
      instruction = self.prompter(
          random.choice(QUESTIONS),
          with_image=True,
          first_message=first_message,
      )
      save_debug_text(
          [instruction, caption],
          data_debug_path,
          data_debug_counter,
          get_rank(),
      )
      return dict(instruction=instruction, answer=caption)
  
file_path: deepspeedexamples/applications/DeepSpeed-VisualChat/utils/data/coco_caption_dataset.py
imports: import os
  import random
  from PIL import Image
  from .vqa_dataset import VQADataset
  from utils.utils import get_rank
  from .utils import save_debug_image, save_debug_text
label_desc: Use image node_id 3 for calling the COCOCaptionDataset obj's underlying member method code with example usage: obj.process_text(ann, data_debug_path, data_debug_counter, first_message) and returns: dict