code: def parse_config_arguments(config_path: str):
      parser = configparser.ConfigParser()
      parser.read(config_path)
  
      args = argparse.Namespace()
  
      # job config under DEFAULT
      args.log_name = parser.get("DEFAULT", "log_name")
      args.budget = parser.getint("DEFAULT", "budget")
      args.device = parser.get("DEFAULT", "device")
      args.log_folder = parser.get("DEFAULT", "log_folder")
      args.result_dir = parser.get("DEFAULT", "result_dir")
      args.num_points = parser.getint("DEFAULT", "num_points")
      args.max_load = parser.getint("DEFAULT", "max_load")
  
      # sampler args
      args.search_space = parser.get("SAMPLER", "search_space")
      args.population_size = parser.getint("SAMPLER", "population_size")
      args.sample_size = parser.getint("SAMPLER", "sample_size")
      args.simple_score_sum = parser.getboolean(
          "SAMPLER", "simple_score_sum"
      )
  
      # nb101 args
      args.api_loc = parser.get("NB101", "api_loc")
      args.init_channels = parser.getint("NB101", "init_channels")
      args.bn = parser.getint("NB101", "bn")
      args.num_stacks = parser.getint("NB101", "num_stacks")
      args.num_modules_per_stack = parser.getint(
          "NB101", "num_modules_per_stack"
      )
  
      # nb201 args
      args.init_w_type = parser.get("NB201", "init_w_type")
      args.init_b_type = parser.get("NB201", "init_b_type")
      args.arch_size = parser.getint("NB201", "arch_size")
  
      # mlp args
      args.num_layers = parser.getint("MLP", "num_layers")
      args.hidden_choice_len = parser.getint("MLP", "hidden_choice_len")
  
      # mlp_trainer args
      args.epoch = parser.getint("MLP_TRAINER", "epoch")
      args.batch_size = parser.getint("MLP_TRAINER", "batch_size")
      args.lr = parser.getfloat("MLP_TRAINER", "lr")
      args.patience = parser.getint("MLP_TRAINER", "patience")
      args.iter_per_epoch = parser.getint(
          "MLP_TRAINER", "iter_per_epoch"
      )
      args.nfeat = parser.getint("MLP_TRAINER", "nfeat")
      args.nfield = parser.getint("MLP_TRAINER", "nfield")
      args.nemb = parser.getint("MLP_TRAINER", "nemb")
      args.report_freq = parser.getint("MLP_TRAINER", "report_freq")
      args.workers = parser.getint("MLP_TRAINER", "workers")
  
      # dataset args
      args.base_dir = parser.get("DATASET", "base_dir")
      args.dataset = parser.get("DATASET", "dataset")
      args.num_labels = parser.getint("DATASET", "num_labels")
  
      # seq_train args
      args.worker_id = parser.getint("SEQ_TRAIN", "worker_id")
      args.total_workers = parser.getint("SEQ_TRAIN", "total_workers")
      args.total_models_per_worker = parser.getint(
          "SEQ_TRAIN", "total_models_per_worker"
      )
      args.pre_partitioned_file = parser.get(
          "SEQ_TRAIN", "pre_partitioned_file"
      )
  
      # dis_train args
      args.worker_each_gpu = parser.getint(
          "DIS_TRAIN", "worker_each_gpu"
      )
      args.gpu_num = parser.getint("DIS_TRAIN", "gpu_num")
  
      # tune_interval args
      args.kn_rate = parser.getint("TUNE_INTERVAL", "kn_rate")
  
      # anytime args
      args.only_phase1 = parser.getboolean("ANYTIME", "only_phase1")
      args.is_simulate = parser.getboolean("ANYTIME", "is_simulate")
  
      # system performance exps
      args.models_explore = parser.getint(
          "SYS_PERFORMANCE", "models_explore"
      )
      args.tfmem = parser.get("SYS_PERFORMANCE", "tfmem")
      args.embedding_cache_filtering = parser.getboolean(
          "SYS_PERFORMANCE", "embedding_cache_filtering"
      )
      args.concurrency = parser.getint("SYS_PERFORMANCE", "concurrency")
  
      args.refinement_url = parser.get("SERVER", "refinement_url")
      args.cache_svc_url = parser.get("SERVER", "cache_svc_url")
  
      # db config
      args.db_name = parser.get("DB_CONFIG", "db_name")
      args.db_user = parser.get("DB_CONFIG", "db_user")
      args.db_host = parser.get("DB_CONFIG", "db_host")
      args.db_port = parser.get("DB_CONFIG", "db_port")
  
      return args
  
imports: import calendar
  import os
  import time
  import argparse
  import configparser
label_desc: Use image node_id 1 for calling a global function with example usage: parse_config_arguments(config_path) and returns: args