code: def run_with_time_budget(time_budget: float):
      """
      :param time_budget: the given time budget, in second
      :return:
      """
  
      # define dataLoader, and sample a mini-batch
      (
          train_loader,
          val_loader,
          test_loader,
          class_num,
      ) = generate_data_loader()
      args.num_labels = class_num
      data_loader = [train_loader, val_loader, test_loader]
  
      rms = RunModelSelection(
          args.search_space, args, is_simulate=False
      )
      best_arch, _, _, _, _, _, _, _ = rms.select_model_online(
          time_budget, data_loader
      )
  
      return best_arch
  
file_path: singa/examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/main.py
imports: import calendar
  import os
  import time
  from src.common.constant import Config
  from src.dataset_utils.structure_data_loader import libsvm_dataloader
  from exps.shared_args import parse_arguments
label_desc: Use image node_id 2 for calling a global function with example usage: run_with_time_budget(time_budget) and returns: best_arch