code: def __init__(
      self, config, dataset_type, imdb_file_index, *args, **kwargs
  ):
      super().__init__("airstore", config, dataset_type)
  
      self.pathmanager = create_path_manager()
      self.config = config
      self.batch_size = get_batch_size()
      self.airstore_uri = config.annotations.get(dataset_type)[
          imdb_file_index
      ]
      self.split = dataset_type
      self.epoch = 0
      self.start_iter = 0
      self.global_rank = torch.distributed.get_rank()
      self.global_world_size = torch.distributed.get_world_size()
      self._iterator = None
  
file_path: mmf/mmf/datasets/builders/airstore/dataset.py
imports: import logging
  from io import BytesIO
  from typing import Any, Iterable
  import torch
  from iopath.common.file_io import PathManager
  from mmf.common.sample import Sample
  from mmf.datasets.base_dataset import BaseDataset
  from mmf.utils.general import get_batch_size
  from PIL import Image, ImageFile
label_desc: Use image node_id 1 to create a new AirstoreDataset object from inherited base classes: BaseDataset with example: obj = AirstoreDataset(config, dataset_type, imdb_file_index)