code: def validation_step(engine, batch):
      model.eval()
      with torch.no_grad():
          x, y = batch[0].to(device), batch[1].to(device)
          y_pred = model(x)
  
      return y_pred, y
  
imports: import argparse
  import torch
  import torch.nn
  import torch.optim
  import torchvision
  from model import Net
  from torch.utils.data import DataLoader
  from torchvision.transforms.functional import center_crop, resize, to_tensor
  from ignite.contrib.handlers import ProgressBar
  from ignite.engine import Engine, Events
  from ignite.handlers import BasicTimeProfiler
  from ignite.metrics import PSNR
label_desc: Use image node_id 2 for calling a global function with example usage: validation_step(engine, batch) and returns: y_pred,  y