code: def preload(self):
      try:
          self.next_input, self.next_target = next(self.loader)
      except StopIteration:
          self.next_input = None
          self.next_target = None
          return
      # if record_stream() doesn't work, another option is to make sure device inputs are created
      # on the main stream.
      # self.next_input_gpu = torch.empty_like(self.next_input, device='cuda')
      # self.next_target_gpu = torch.empty_like(self.next_target, device='cuda')
      # Need to make sure the memory allocated for next_* is not still in use by the main stream
      # at the time we start copying to next_*:
      # self.stream.wait_stream(torch.cuda.current_stream())
      with torch.cuda.stream(self.stream):
          self.next_input = self.next_input.cuda(non_blocking=True)
          self.next_target = self.next_target.cuda(non_blocking=True)
          # more code for the alternative if record_stream() doesn't work:
          # copy_ will record the use of the pinned source tensor in this side stream.
          # self.next_input_gpu.copy_(self.next_input, non_blocking=True)
          # self.next_target_gpu.copy_(self.next_target, non_blocking=True)
          # self.next_input = self.next_input_gpu
          # self.next_target = self.next_target_gpu
  
          # With Amp, it isn't necessary to manually convert data to half.
          # if args.fp16:
          #     self.next_input = self.next_input.half()
          # else:
          self.next_input = self.next_input.float()
          self.next_input = self.next_input.sub_(self.mean).div_(
              self.std
          )
  
imports: import argparse
  import os
  import shutil
  import time
  import torch
  import torch.nn
  import torch.nn.parallel
  import torch.backends.cudnn
  import torch.distributed
  import torch.optim
  import torch.utils.data
  import torch.utils.data.distributed
  import torchvision.transforms
  import torchvision.datasets
  import torchvision.models
  import numpy
label_desc: Use image node_id 2 for calling the data_prefetcher obj's underlying member method code with example usage: obj.preload() without return types