text: import argparse
  
  
  def parse_args():
      """
      Parse Arguments for our Bert Conv2d example.
      Returns:
      -------
      * `args`: [argparse object]
          Parsed arguments.
      """
      parser = argparse.ArgumentParser(description='BertKim Combo!')
      parser.add_argument('-d','--datapath', metavar='DIR',
                          default='/home/ygx/kaggle/scene/data/splits/small_val/csv',
                          help='path to dataset')
      parser.add_argument('--savepath', type=str,
                          default='/home/kaggle/scene/saves',
                          help='path to save checkpoints')
      parser.add_argument('--serialization_dir', type=str,
                          default='/home/ygx/kaggle/scene/examples/yoonkim_conv/saves',
                          help='path to save serialized models')
      parser.add_argument('--options_file', type=str,
                          default='https://s3-us-west-2.amazonaws.com/allennlp/models/elmo/' \
                                  '2x1024_128_2048cnn_1xhighway/elmo_2x1024_128_2048cnn_1xhighway_options.json',
                          help='Elmo embeddings option file')
      parser.add_argument('--weight_file', type=str,
                          default='https://s3-us-west-2.amazonaws.com/allennlp/models/elmo/' \
                                  '2x1024_128_2048cnn_1xhighway/elmo_2x1024_128_2048cnn_1xhighway_weights.hdf5',
                          help='Elmo embedding weights')
      parser.add_argument('--batch_size', type=int, default=28, metavar='N',
                          help='input batch size for training (default: 16)')
      parser.add_argument('--num_epochs', type=int, default=100, metavar='N',
                          help='number of epochs to train (default: 10)')
      parser.add_argument('--lr', type=float, default=0.01, metavar='LR',
                          help='learning rate (default: 0.01)')
      parser.add_argument('--momentum', type=float, default=0.5, metavar='M',
                          help='SGD momentum (default: 0.5)')
      parser.add_argument('--no-cuda', action='store_true', default=False,
                          help='disables CUDA training')
      parser.add_argument('--seed', type=int, default=1, metavar='S',
                          help='random seed (default: 1)')
      parser.add_argument('--log-interval', type=int, default=10, metavar='N',
                          help='how many batches to wait before logging training status')
      args = parser.parse_args()
      return args
  