class_docstr: Dataset used to parallelize the transformation of the dataset via a DataLoader
class_docstr_tok: ["Dataset","used","to","parallelize","the","transformation","of","the","dataset","via","a","DataLoader"]
code: def __init__(self, data_path: str, split: str):
      self.data_path = data_path
      self.split = split
      self.split_path = os.path.join(data_path, split)
      self.video_paths = []
      self.video_labels = []
      self._init_dataset()
  
file_path: vissl/extra_scripts/datasets/create_k700_data_files.py
imports: import argparse
  import os
  from typing import Optional, Tuple
  import numpy
  from PIL import Image
  from torch.utils.data import DataLoader
  from torchvision.datasets.utils import download_url
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive
  from vissl.utils.io import save_file
label_desc: Use image node_id 1 to create a new KineticsMiddleFrameDataset object  with example: obj = KineticsMiddleFrameDataset(data_path, split)