code: def _parse_args():
      parser = ArgumentParser(
          description="Set parameters for multi task demo"
      )
  
      parser.add_argument(
          "--model_type",
          type=str,
          default="mmoe",
          help="The multi task model, mmoe or ple.",
      )
      parser.add_argument(
          "--train_data_path",
          type=str,
          default="path/to/training/dataset",
          help="The path for training dataset.",
      )
      parser.add_argument(
          "--test_data_path",
          type=str,
          default="path/to/testing/dataset",
          help="The path for testing dataset.",
      )
      parser.add_argument(
          "--model_save_path",
          type=str,
          default="path/to/save/the/trained/model",
          help="The path for saving the trained model.",
      )
      parser.add_argument(
          "--cluster_mode",
          type=str,
          default="local",
          help="The cluster mode, such as local, yarn, standalone or spark-submit.",
      )
      parser.add_argument(
          "--master",
          type=str,
          default=None,
          help="The master url, only used when cluster mode is standalone.",
      )
      parser.add_argument(
          "--executor_cores",
          type=int,
          default=8,
          help="The executor core number.",
      )
      parser.add_argument(
          "--executor_memory",
          type=str,
          default="12g",
          help="The executor memory.",
      )
      parser.add_argument(
          "--num_executors",
          type=int,
          default=4,
          help="The number of executors.",
      )
      parser.add_argument(
          "--driver_cores",
          type=int,
          default=2,
          help="The driver core number.",
      )
      parser.add_argument(
          "--driver_memory",
          type=str,
          default="8g",
          help="The driver memory.",
      )
      args = parser.parse_args()
      return args
  
file_path: BigDL/python/friesian/example/multi_task/run_multi_task.py
imports: import math
  from time import time
  from argparse import ArgumentParser
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.learn.tf2.estimator import Estimator
  from bigdl.friesian.feature import FeatureTable
  from deepctr.feature_column import SparseFeat, DenseFeat
  from deepctr.models import MMOE, PLE
  from keras.callbacks import EarlyStopping
label_desc: Use image node_id 7 for calling a global function with example usage: _parse_args() and returns: args