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: Initialize ImageNetA.
docstr_tok: ["Initialize","ImageNetA","."]
code: def __init__(
      self,
      opts: argparse.Namespace,
      *args,
      **kwargs,
  ) -> None:
      """Initialize ImageNetA."""
      BaseImageNetShiftDataset.__init__(
          self, opts=opts, *args, **kwargs
      )
  
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 1 to create a new ImageNetADataset object from inherited base classes: BaseImageNetShiftDataset with example: obj = ImageNetADataset(opts)