code: def parse_arguments():
      parser = argparse.ArgumentParser()
  
      # parser.add_argument("mode", choices=["train", "test", "tag", "extract"])
      # parser.add_argument("--training-file",
      #                     help="Defines training data set")
      # parser.add_argument("--test-file",
      #                     help="Defines test data set")
      # parser.add_argument("--input-file",
      #                     help="Defines input file to be tagged")
      parser.add_argument(
          "--epochs",
          default=5,
          help="Defines number of training epochs",
      )
      # parser.add_argument(
      #     "--architecture",
      #     default="cnn",
      #     help="Neural network architectures, supported: cnn, lstm, bi-lstm, gru, bi-gru, mlp")
      parser.add_argument(
          "--window-size",
          default=5,
          help="Defines number of window size (char-ngram)",
      )
      parser.add_argument(
          "--batch-size",
          default=32,
          help="Defines number of batch_size",
      )
      parser.add_argument(
          "--dropout", default=0.2, help="Defines number dropout"
      )
      parser.add_argument(
          "--min-freq",
          default=100,
          help="Defines the min. freq. a char must appear in data",
      )
      parser.add_argument(
          "--max-features",
          default=200,
          help="Defines number of features for Embeddings layer",
      )
      parser.add_argument(
          "--embedding-size",
          default=128,
          help="Defines Embeddings size",
      )
      parser.add_argument(
          "--kernel-size", default=8, help="Defines Kernel size of CNN"
      )
      parser.add_argument(
          "--filters",
          default=6,
          help="Defines number of filters of CNN",
      )
      parser.add_argument(
          "--pool-size", default=8, help="Defines pool size of CNN"
      )
      parser.add_argument(
          "--hidden-dims",
          default=250,
          help="Defines number of hidden dims",
      )
      parser.add_argument(
          "--strides",
          default=1,
          help="Defines numer of strides for CNN",
      )
      parser.add_argument(
          "--lstm_gru_size",
          default=256,
          help="Defines size of LSTM/GRU layer",
      )
      parser.add_argument(
          "--mlp-dense",
          default=6,
          help="Defines number of dense layers for mlp",
      )
      parser.add_argument(
          "--mlp-dense-units",
          default=16,
          help="Defines number of dense units for mlp",
      )
      parser.add_argument(
          "--model-filename",
          default="best_model.hdf5",
          help="Defines model filename",
      )
      parser.add_argument(
          "--vocab-filename",
          default="vocab.dump",
          help="Defines vocab filename",
      )
      parser.add_argument(
          "--eos-marker",
          default="</eos>",
          help="Defines end-of-sentence marker used for tagging",
      )
      return parser.parse_args()
  
label_desc: Use image node_id 1 for calling a global function with example usage: parse_arguments() and returns: parser