text: import os
  os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
  
  import argparse
  import importlib
  import sys
  
  
  def argparsing():
    parser = argparse.ArgumentParser(description='BiO-Net')
    parser.add_argument('--epochs', default=300, type=int, help='trining epochs')
    parser.add_argument('--batch_size', default=2, type=int, help='batch size')
    parser.add_argument('--steps', default=250, type=int, help='steps per epoch')
    parser.add_argument('--lr', default=0.01, type=float, help='learning rate')
    parser.add_argument('--lr_decay', default=3e-5, type=float, help='learning rate decay')
    parser.add_argument('--num_class', default=1, type=int, help='model output channel number')
    parser.add_argument('--multiplier', default=1.0, type=float, help='parameter multiplier')
    parser.add_argument('--iter', default=1, type=int, help='recurrent iteration')
    parser.add_argument('--integrate', action='store_true', help='integrate all inferenced features')
    parser.add_argument('--save_weight', action='store_true', help='save weight only')
    parser.add_argument('--train_data', default='./data/train', type=str, help='data path')
    parser.add_argument('--valid_data', default='./data/valid', type=str, help='data path')
    parser.add_argument('--exp', default='1', type=str, help='experiment number')
    parser.add_argument('--evaluate_only', action='store_true', help='evaluate only?')
    parser.add_argument('--save_result', action='store_true', default=False, help='save results to exp folder?')
    parser.add_argument('--model_path', default=None, type=str, help='path to model check')
    parser.add_argument('--valid_dataset', default='monuseg', choices=['monuseg', 'tnbc'], type=str, help='which dataset to validate?')
    parser.add_argument('--backend', default='keras', choices=['keras', 'pytorch'], type=str, help='which backend to use?')
    args = parser.parse_args()
  
    print()
    print()
    print(args) # print command line args
  
    return args
    
  def main(args, CORE):
      # path verification
      if args.model_path is not None:
        if os.path.isfile(args.output_path):
          print('Model path has been verified.')
        else:
          print('Invalid model path! Please specify a valid model file. Program terminating...')
          exit()
  
      # pipeline starts
      if not args.evaluate_only:
        CORE.train(args)
      CORE.evaluate(args)
      
  if __name__ == '__main__':
    # parse command line args
    args = argparsing()
  
    # import dependencies
    CORE = importlib.import_module(args.backend+'_version')
  
    main(args, CORE)
  