code: def test_oneshot_sanity():
      model_space = SimpleNet()
      train_dataset = RandomMnistDataset(1000)
      train_loader = DataLoader(train_dataset, 64, shuffle=True)
      valid_dataset = RandomMnistDataset(200)
      valid_loader = DataLoader(valid_dataset, 64, shuffle=True)
  
      evaluator = Classification(
          num_classes=10,
          train_dataloaders=train_loader,
          val_dataloaders=valid_loader,
          max_epochs=2,
      )
      strategy = DARTS()
  
      exp = NasExperiment(model_space, evaluator, strategy)
      exp.run()
      assert isinstance(
          exp.export_top_models(formatter="dict")[0], dict
      )
  
file_path: nni/test/ut/nas/experiment/test_experiment.py
imports: import torch
  from torch import nn
  from torch.optim import SGD
  from torch.utils.data import DataLoader, Dataset
  import nni
  from nni.nas.evaluator import FunctionalEvaluator
  from nni.nas.evaluator.pytorch import Classification
  from nni.nas.experiment import *
  from nni.nas.experiment.config import *
  from nni.nas.strategy import RegularizedEvolution, PolicyBasedRL, DARTS, Random
  from ut.nas.nn.models import SimpleNet
label_desc: Use image node_id 3 for calling a global function with example usage: test_oneshot_sanity() without return types