class_docstr: ImageNetSketch dataset, a distribution shift of ImageNet.
  
  Data set is created from Google Image queries "sketch of __", where __ is the
  standard class name. Search is only within the "black and white" color scheme.
  
  @inproceedings{wang2019learning,
      title={Learning Robust Global Representations by Penalizing Local Predictive
      Power},
      author={Wang, Haohan and Ge, Songwei and Lipton, Zachary and Xing, Eric P},
      booktitle={Advances in Neural Information Processing Systems},
      pages={10506--10518},
      year={2019}
  }
class_docstr_tok: ["ImageNetSketch","dataset",",","a","distribution","shift","of","ImageNet",".","Data","set","is","created","from","Google","Image","queries","``","sketch","of","__","''",",","where","__","is","the","standard","class","name",".","Search","is","only","within","the","``","black","and","white","''","color","scheme",".","@","inproceedings","{","wang2019learning",",","title=","{","Learning","Robust","Global","Representations","by","Penalizing","Local","Predictive","Power","}",",","author=","{","Wang",",","Haohan","and","Ge",",","Songwei","and","Lipton",",","Zachary","and","Xing",",","Eric","P","}",",","booktitle=","{","Advances","in","Neural","Information","Processing","Systems","}",",","pages=","{","10506","--","10518","}",",","year=","{","2019","}","}"]
docstr: Initialize ImageNetSketchDataset.
docstr_tok: ["Initialize","ImageNetSketchDataset","."]
code: def __init__(
      self,
      opts: argparse.Namespace,
      *args,
      **kwargs,
  ) -> None:
      """Initialize ImageNetSketchDataset."""
      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
label_desc: Use image node_id 1 to create a new ImageNetSketchDataset object from inherited base classes: BaseImageNetShiftDataset with example: obj = ImageNetSketchDataset(opts)