class_docstr: The DSprites dataset, mapping images to the latent vector used to generate the image
code: def __init__(self, root: str, target_transform=None):
      npz_file_name = "dsprites-dataset-master/dsprites_ndarray_co1sh3sc6or40x32y32_64x64.npz"
      self.npz_file_path = os.path.join(root, npz_file_name)
      self.npz_file = np.load(self.npz_file_path)
      self.images = self.npz_file["imgs"]
      self.latents = self.npz_file["latents_values"]
      self.target_transform = target_transform
  
imports: import argparse
  import os
  from typing import Set
  import numpy
  from PIL import Image
  from torch.utils.data import DataLoader, Dataset
  from tqdm import tqdm
  from vissl.utils.download import download_and_extract_archive
label_desc: Use image node_id 1 to create a new DSprites object from inherited base classes: Dataset with example: obj = DSprites(root, target_transform)