code: def __init__(self, loader):
      self.loader = iter(loader)
      self.stream = torch.cuda.Stream()
      self.mean = (
          torch.tensor([0.485 * 255, 0.456 * 255, 0.406 * 255])
          .cuda()
          .view(1, 3, 1, 1)
      )
      self.std = (
          torch.tensor([0.229 * 255, 0.224 * 255, 0.225 * 255])
          .cuda()
          .view(1, 3, 1, 1)
      )
      self.preload()
  
imports: import math
  import random
  import numpy
  import torch
  import torch.distributed
  from PIL import Image, ImageEnhance, ImageOps
  from torch.utils.data import Sampler
label_desc: Use image node_id 1 to create a new data_prefetcher object  with example: obj = data_prefetcher(loader)