class_docstr: ImageNetA dataset, a distribution shift of ImageNet.
  
  ImageNet-A contains real-world, unmodified natural images that cause model accuracy
  to substantially degrade.
  
  @article{hendrycks2021nae,
  title={Natural Adversarial Examples},
  author={Dan Hendrycks and Kevin Zhao and Steven Basart and Jacob Steinhardt and Dawn
  Song},
  journal={CVPR},
  year={2021}
  }
docstr: Return the mapped class index using precomputed mapping.
docstr_tok: ["Return","the","mapped","class","index","using","precomputed","mapping","."]
code: def class_id_to_imagenet_class_id(class_id: int) -> int:
      """Return the mapped class index using precomputed mapping."""
      return IMAGENET_A_CLASS_SUBLIST[class_id]
  
imports: import argparse
  from data.datasets import DATASET_REGISTRY
  from data.datasets.classification.base_imagenet_shift_dataset import BaseImageNetShiftDataset
  from data.datasets.classification.imagenet_synsets import IMAGENET_A_SYNSETS, IMAGENET_SYNSETS
label_desc: Use image node_id 2 for calling the ImageNetADataset obj's underlying member method code with example usage: obj.class_id_to_imagenet_class_id(class_id) and returns: IMAGENET_A_CLASS_SUBLIST