code: def get_image_path(
      self, image_id: Union[str, int], coco_split: str
  ) -> str:
      base_paths = self._get_path_based_on_index(
          self.config, "images", self._index
      )
      base_paths = base_paths.split(",")
      if "train" in base_paths[0]:
          train_path = base_paths[0]
          val_path = base_paths[1]
      else:
          train_path = base_paths[1]
          val_path = base_paths[0]
  
      # coco_split indicates whether the image is from the train or val split of COCO
      if "train" in coco_split:
          image_path = f"COCO_train2014_{str(image_id).zfill(12)}.jpg"
          image_path = os.path.join(train_path, image_path)
      else:
          image_path = f"COCO_val2014_{str(image_id).zfill(12)}.jpg"
          image_path = os.path.join(val_path, image_path)
      return image_path
  
file_path: mmf/mmf/datasets/builders/vqacp_v2/dataset.py
imports: import os
  from typing import Type, Union
  import torch
  from mmf.common.sample import Sample
  from mmf.common.typings import MMFDatasetConfigType
  from mmf.datasets.builders.okvqa.dataset import OKVQADataset
  from mmf.datasets.builders.vqacp_v2.database import VQACPv2AnnotationDatabase
label_desc: Use image node_id 3 for calling the VQACPv2Dataset obj's underlying member method code with example usage: obj.get_image_path(image_id, coco_split) and returns: image_path