code: def teardown(self, stage):
      if stage == "fit":
          nni.report_final_result(
              self.trainer.callback_metrics["val_accuracy"].item()
          )
  
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 NasBench101Cell
  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 CIFAR10
  from base_ops import Conv3x3BnRelu, Conv1x1BnRelu, Projection
label_desc: Use image node_id 7 for calling the NasBench101TrainingModule obj's underlying member method code with example usage: obj.teardown(stage) without return types