code: def load_data(data_dir="./data"):
      transform = transforms.Compose(
          [
              transforms.ToTensor(),
              transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)),
          ]
      )
  
      trainset = torchvision.datasets.CIFAR10(
          root=data_dir, train=True, download=True, transform=transform
      )
  
      testset = torchvision.datasets.CIFAR10(
          root=data_dir, train=False, download=True, transform=transform
      )
  
      return trainset, testset
  
imports: from functools import partial
  import os
  from tempfile import TemporaryDirectory
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from torch.utils.data import random_split
  import torchvision
  import torchvision.transforms
  from ray import train, tune
  from ray.train import Checkpoint
  from ray.tune.schedulers import ASHAScheduler
label_desc: Use image node_id 1 for calling a global function with example usage: load_data(data_dir) and returns: trainset,  testset