code: def __init__(self, data):
      super().__init__(data)
  
imports: import os
  import numpy
  import PIL
  import torch
  from PIL import Image
  from torch.utils.data import Dataset, DataLoader, Sampler
  from torchvision import transforms
  from collections import defaultdict
  from random import shuffle, choices
  import random
  import tqdm
  from modules import devices, shared
  import re
  from ldm.modules.distributions.distributions import DiagonalGaussianDistribution
label_desc: Use image node_id 1 to create a new BatchLoaderRandom object from inherited base classes: BatchLoader with example: obj = BatchLoaderRandom(data)