class_docstr: Use to map the classes of datasets featuring a sub-set of Imagenet classes
  such as Imagenet-A or Imagenet-R to the Imagenet classes index
class_docstr_tok: ["Use","to","map","the","classes","of","datasets","featuring","a","sub-set","of","Imagenet","classes","such","as","Imagenet-A","or","Imagenet-R","to","the","Imagenet","classes","index"]
code: def __init__(self):
      with g_pathmgr.open(self.IMAGENET_TARGETS_URL) as f:
          imagenet_classes = [line.strip() for line in f.readlines()]
          imagenet_classes.sort()
      self.label_to_id = {
          label: i for i, label in enumerate(imagenet_classes)
      }
  
file_path: vissl/extra_scripts/datasets/create_imagenet_a_data_files.py
imports: import argparse
  import os
  import numpy
  import torchvision.datasets
  from iopath.common.file_io import g_pathmgr
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive
  from vissl.utils.io import cleanup_dir
label_desc: Use image node_id 1 to create a new ImagenetTargetMapper object  with example: obj = ImagenetTargetMapper()