code: def build_model(config):
      model = Sequential(
          [
              Dense(64, activation=tf.nn.relu, input_shape=[9]),
              Dense(64, activation=tf.nn.relu),
              Dense(1),
          ]
      )
  
      optimizer = tf.keras.optimizers.RMSprop(0.001)
  
      model.compile(
          loss="mean_squared_error",
          optimizer=optimizer,
          metrics=["mean_absolute_error", "mean_squared_error"],
      )
      return model
  
file_path: BigDL/python/orca/tutorial/xshards/auto_mpg.py
imports: import math
  import bigdl.orca.data.pandas
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.data.transformer import *
  from bigdl.orca.learn.tf2.estimator import Estimator
  import tensorflow.compat.v1
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.layers import Dense
label_desc: Use image node_id 4 for calling a global function with example usage: build_model(config) and returns: model