class_docstr: ImageNet dataset.
class_docstr_tok: ["ImageNet","dataset","."]
code: def _load_imdb(self):
      split_path = os.path.join(
          self.cfg.DATA.PATH_TO_PRELOAD_IMDB, f"{self.mode}.json"
      )
      with pathmgr.open(split_path, "r") as f:
          data = f.read()
      self._imdb = json.loads(data)
  
imports: import json
  import numpy
  import os
  import random
  import re
  import torch
  import torch.utils.data
  from PIL import Image
  from torchvision import transforms
  import slowfast.datasets.transform
  import slowfast.utils.logging
  from slowfast.models.utils import calc_mvit_feature_geometry
  from slowfast.utils.env import pathmgr
  from .build import DATASET_REGISTRY
  from .transform import MaskingGenerator, transforms_imagenet_train
label_desc: Use image node_id 2 for calling the Imagenet obj's underlying member method code with example usage: obj._load_imdb() without return types