class_docstr: ImageNet Dataset for zero-shot evaluation of Image-text models.
  
  Args:
      opts: Command-line arguments
class_docstr_tok: ["ImageNet","Dataset","for","zero-shot","evaluation","of","Image-text","models",".","Args",":","opts",":","Command-line","arguments"]
docstr: Return the name of the classes present in the dataset.
docstr_tok: ["Return","the","name","of","the","classes","present","in","the","dataset","."]
code: def class_names(cls) -> List[str]:
      """Return the name of the classes present in the dataset."""
      return IMAGENET_CLASS_NAMES
  
file_path: ml-cvnets/data/datasets/multi_modal_img_text/zero_shot/imagenet.py
imports: import argparse
  from typing import List
  from torchvision.datasets import ImageFolder
  from data.datasets.multi_modal_img_text.zero_shot import ZERO_SHOT_DATASET_REGISTRY, BaseZeroShotDataset
  from data.datasets.multi_modal_img_text.zero_shot.imagenet_class_names import IMAGENET_CLASS_NAMES
  from data.datasets.multi_modal_img_text.zero_shot.templates import generate_text_prompts_clip
label_desc: Use image node_id 2 for calling the ImageNetDatasetZeroShot obj's underlying member method code with example usage: obj.class_names(cls) and returns: IMAGENET_CLASS_NAMES