code: def get_train_test_datasets(path):
      path = Path(path)
      if not path.exists():
          path.mkdir(parents=True)
          download = True
      else:
          download = True if len(os.listdir(path)) < 1 else False
  
      train_ds = datasets.CIFAR10(
          root=path,
          train=True,
          download=download,
          transform=train_transform,
      )
      test_ds = datasets.CIFAR10(
          root=path,
          train=False,
          download=False,
          transform=test_transform,
      )
  
      return train_ds, test_ds
  
imports: import os
  from pathlib import Path
  import brevitas.nn
  import torch
  import torch.nn
  from pact import PACTReLU
  from torchvision import datasets, models
  from torchvision.transforms import Compose, Normalize, Pad, RandomCrop, RandomHorizontalFlip, ToTensor
label_desc: Use image node_id 1 for calling a global function with example usage: get_train_test_datasets(path) and returns: train_ds,  test_ds