code: def setUp_data(self) -> None:
      self.ds = FakeData(
          size=self.DATA_SIZE,
          image_size=(1, 35, 35),
          num_classes=10,
          transform=transforms.Compose(
              [
                  transforms.ToTensor(),
                  transforms.Normalize((0.1307,), (0.3081,)),
              ]
          ),
      )
      self.dl = DataLoader(self.ds, batch_size=self.BATCH_SIZE)
  
imports: import unittest
  from typing import Iterable, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from opacus import PrivacyEngine
  from opacus.grad_sample.utils import get_gsm_class
  from opacus.utils.batch_memory_manager import BatchMemoryManager
  from torch.utils.data import DataLoader
  from torchvision import transforms
  from torchvision.datasets import FakeData
label_desc: Use image node_id 2 for calling the GradientAccumulationTest obj's underlying member method code with example usage: obj.setUp_data() without return types