code: def setup_data(self):
      transform = transforms.Compose(
          [
              transforms.ToTensor(),
              transforms.Normalize((0.1307,), (0.3081,)),
          ]
      )
      self.dataset1 = datasets.FakeData(
          size=2000,
          image_size=(1, 28, 28),
          num_classes=10,
          transform=transform,
      )
      self.dataset2 = datasets.FakeData(
          size=2000,
          image_size=(1, 28, 28),
          num_classes=10,
          transform=transform,
      )
      self.next(self.setup_dataloaders)
  
imports: import os
  from pathlib import Path
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import wandb
  from metaflow import FlowSpec, Parameter, step
  from torch.optim.lr_scheduler import StepLR
  from torchvision import datasets, transforms
  from wandb.integration.metaflow import wandb_log
label_desc: Use image node_id 2 for calling the WandbPyTorchFlow obj's underlying member method code with example usage: obj.setup_data() without return types