code: def get_config():
      """
      Get config from arument parser.
      """
      parser = argparse.ArgumentParser(
          description="This program is using genetic algorithm to search architecture for SQuAD."
      )
      parser.add_argument(
          "--input_file",
          type=str,
          default="./train-v1.1.json",
          help="input file",
      )
      parser.add_argument(
          "--dev_file",
          type=str,
          default="./dev-v1.1.json",
          help="dev file",
      )
      parser.add_argument(
          "--embedding_file",
          type=str,
          default="./glove.840B.300d.txt",
          help="dev file",
      )
      parser.add_argument(
          "--root_path",
          default="./data/",
          type=str,
          help="Root path of models",
      )
      parser.add_argument(
          "--batch_size", type=int, default=64, help="batch size"
      )
      parser.add_argument(
          "--save_path",
          type=str,
          default="./save",
          help="save path dir",
      )
      parser.add_argument(
          "--learning_rate",
          type=float,
          default=0.0001,
          help="set half of original learning rate reload data and train.",
      )
      parser.add_argument("--max_epoch", type=int, default=30)
      parser.add_argument(
          "--dropout_rate", type=float, default=0.1, help="dropout_rate"
      )
      parser.add_argument(
          "--labelsmoothing",
          type=float,
          default=0.1,
          help="labelsmoothing",
      )
      parser.add_argument(
          "--num_heads", type=int, default=1, help="num_heads"
      )
      parser.add_argument(
          "--rnn_units", type=int, default=256, help="rnn_units"
      )
  
      args = parser.parse_args()
      return args
  
imports: import argparse
  import heapq
  import json
  import os
  import pickle
  import logging
  import numpy
  from tensorflow.train import init_from_checkpoint
  import graph
  from util import Timer
  import nni
  import data
  import evaluate
  from train_model import *
label_desc: Use image node_id 1 for calling a global function with example usage: get_config() and returns: args