code: def _get_dist_imagenet(args):
      traindir = os.path.join(args.data_dir, "train")
      valdir = os.path.join(args.data_dir, "val")
      normalize = transforms.Normalize(
          mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
      )
  
      train_dataset = dset.ImageFolder(
          traindir,
          transforms.Compose(
              [
                  transforms.RandomResizedCrop(224),
                  transforms.RandomHorizontalFlip(),
                  transforms.ColorJitter(
                      brightness=0.4,
                      contrast=0.4,
                      saturation=0.4,
                      hue=0.2,
                  ),
                  transforms.ToTensor(),
                  normalize,
              ]
          ),
      )
  
      sampler = torch.utils.data.distributed.DistributedSampler(
          train_dataset, num_replicas=args.gpu_num, rank=args.local_rank
      )
  
      train_loader = torch.utils.data.DataLoader(
          train_dataset,
          batch_size=args.batch_size // args.gpu_num,
          num_workers=max(args.gpu_num * 2, 4),
          pin_memory=True,
          drop_last=True,
          sampler=sampler,
      )
  
      val_loader = torch.utils.data.DataLoader(
          dset.ImageFolder(
              valdir,
              transforms.Compose(
                  [
                      transforms.Resize(256),
                      transforms.CenterCrop(224),
                      transforms.ToTensor(),
                      normalize,
                  ]
              ),
          ),
          batch_size=args.batch_size,
          shuffle=False,
          num_workers=4,
          pin_memory=True,
      )
  
      return train_loader, val_loader, sampler
  
imports: import math
  import os
  import random
  import sys
  import time
  import warnings
  import numpy
  import numpy
  import shutil
  import logging
  import torch
  import torchvision.transforms
  import torchvision.datasets
  import torch.nn
label_desc: Use image node_id 7 for calling a global function with example usage: _get_dist_imagenet(args) and returns: train_loader,  val_loader,  sampler