class_docstr: ImageNetR dataset, a distribution shift of ImageNet.
  
  ImageNet-R(endition) contains art, cartoons, deviantart, graffiti, embroidery,
  graphics, origami, paintings, patterns, plastic objects, plush objects, sculptures,
  sketches, tattoos, toys, and video game renditions of ImageNet classes.
  
  @article{hendrycks2021many,
  title={The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution
  Generalization},
  author={Dan Hendrycks and Steven Basart and Norman Mu and Saurav Kadavath and Frank
  Wang and Evan Dorundo and Rahul Desai and Tyler Zhu and Samyak Parajuli and Mike Guo
  and Dawn Song and Jacob Steinhardt and Justin Gilmer},
  journal={ICCV},
  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_R_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_R_SYNSETS, IMAGENET_SYNSETS
label_desc: Use image node_id 2 for calling the ImageNetRDataset obj's underlying member method code with example usage: obj.class_id_to_imagenet_class_id(class_id) and returns: IMAGENET_R_CLASS_SUBLIST