code: def test_experiment_resume():
      model_space = SimpleNet()
      evaluator = FunctionalEvaluator(simple_evaluation)
      strategy = RegularizedEvolution(population_size=2, sample_size=2)
  
      config = NasExperimentConfig("sequential", "raw")
      config.max_trial_number = 3
      exp = NasExperiment(model_space, evaluator, strategy, config)
      exp.run_or_resume(debug=True)
      exp.stop()
  
      strategy2 = RegularizedEvolution(population_size=2, sample_size=2)
      config = NasExperimentConfig("sequential", "raw")
      config.max_trial_number = 5
      exp = NasExperiment(
          model_space, evaluator, strategy2, config, id=exp.id
      )
      exp.run_or_resume(debug=True)
      exp.stop()
  
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 4 for calling a global function with example usage: test_experiment_resume() without return types