code: def load_test_data():
      # Loads a fake dataset for testing so it doesn't rely on external download.
      trainset = torchvision.datasets.FakeData(
          128,
          (3, 32, 32),
          num_classes=10,
          transform=transforms.ToTensor(),
      )
      testset = torchvision.datasets.FakeData(
          16,
          (3, 32, 32),
          num_classes=10,
          transform=transforms.ToTensor(),
      )
      return trainset, testset
  
imports: import numpy
  import os
  import tempfile
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from filelock import FileLock
  from torch.utils.data import random_split
  import torchvision
  import torchvision.transforms
  from typing import Dict
  import ray
  from ray import train, tune
  from ray.train import Checkpoint
  from ray.tune.schedulers import ASHAScheduler
label_desc: Use image node_id 2 for calling a global function with example usage: load_test_data() and returns: trainset,  testset