code: def model_creator(config):
      model = build_model(
          model_type=config["model_type"],
          sparse_features=config["column_info"]["cat_cols"],
          dense_features=config["column_info"]["continuous_cols"],
          feature_max_idx=config["column_info"]["feature_max_idx"],
      )
      model.compile(
          optimizer="adam",
          loss=["mean_squared_error", "binary_crossentropy"],
          metrics=[["mae"], ["AUC", "Precision", "Recall"]],
      )
      return model
  
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 2 for calling a global function with example usage: model_creator(config) and returns: model