code: def get_cifar10_train_loader(batch_size, shuffle=True):
      loader = torch.utils.data.DataLoader(
          datasets.CIFAR10(
              DATA_PATH,
              train=True,
              download=True,
              transform=transforms.ToTensor(),
          ),
          batch_size=batch_size,
          shuffle=shuffle,
      )
      loader.name = "cifar10_train"
      return loader
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import os
  import sys
  import pathlib
  from torch.utils.data.dataset import Subset
  import numpy
  import torch
  import torchvision.transforms
  import torchvision.datasets
  from advertorch.test_utils import LeNet5
label_desc: Use image node_id 4 for calling a global function with example usage: get_cifar10_train_loader(batch_size, shuffle) and returns: loader