code: def shuffle(loader, cur_epoch):
      """ "Shuffles the data."""
      err_str = "Sampler type '{}' not supported".format(
          type(loader.sampler)
      )
      assert isinstance(
          loader.sampler, (RandomSampler, DistributedSampler)
      ), err_str
      # RandomSampler handles shuffling automatically
      if isinstance(loader.sampler, DistributedSampler):
          # DistributedSampler shuffles data based on epoch
          loader.sampler.set_epoch(cur_epoch)
  
file_path: pycls/pycls/datasets/loader.py
imports: import os
  import torch
  from pycls.core.config import cfg
  from pycls.datasets.cifar10 import Cifar10
  from pycls.datasets.imagenet import ImageNet, ImageNetFFCV
  from torch.utils.data.distributed import DistributedSampler
  from torch.utils.data.sampler import RandomSampler
label_desc: Use image node_id 5 for calling a global function with example usage: shuffle(loader, cur_epoch) without return types