code: def setup_dataloaders(self):
      self.train_loader = torch.utils.data.DataLoader(
          self.dataset1, **self.train_kwargs
      )
      self.test_loader = torch.utils.data.DataLoader(
          self.dataset2, **self.test_kwargs
      )
      self.next(self.train_model)
  
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 3 for calling the WandbPyTorchFlow obj's underlying member method code with example usage: obj.setup_dataloaders() without return types