code: def training_step(self, batch, batch_idx):
      x, y = batch
      y_hat = self(x)
      loss = self.criterion(y_hat, y)
      self.log("train_loss", loss, prog_bar=True)
      self.log("train_accuracy", self.accuracy(y_hat, y), prog_bar=True)
      return loss
  
imports: import click
  import nni
  import nni.retiarii.evaluator.pytorch.lightning
  import torch.nn
  import torchmetrics
  from nni.retiarii import model_wrapper, serialize
  from nni.retiarii.experiment.pytorch import RetiariiExperiment, RetiariiExeConfig
  from nni.retiarii.nn.pytorch import NasBench201Cell
  from nni.retiarii.strategy import Random
  from pytorch_lightning.callbacks import LearningRateMonitor
  from timm.optim import RMSpropTF
  from torch.optim.lr_scheduler import CosineAnnealingLR
  from torchvision import transforms
  from torchvision.datasets import CIFAR100
  from base_ops import ResNetBasicblock, PRIMITIVES, OPS_WITH_STRIDE
label_desc: Use image node_id 3 for calling the NasBench201TrainingModule obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: loss