code: def get_model():
      model = tf.keras.Sequential()
      model.add(layers.Dense(64, activation="relu"))
      model.add(layers.Dense(64, activation="relu"))
      model.add(layers.Dense(10, activation="softmax"))
      model.compile(
          optimizer=tf.keras.optimizers.Adam(0.01),
          loss="categorical_crossentropy",
          metrics=["accuracy"],
      )
      return model
  
file_path: mars/mars/learn/contrib/tensorflow/tests/tf_dataset.py
imports: import os
  import json
  import sys
  import tensorflow
  from tensorflow.keras import layers
  from mars.learn.contrib.tensorflow import gen_tensorflow_dataset
  from tensorflow.python.data.ops.dataset_ops import DatasetV2
label_desc: Use image node_id 1 for calling a global function with example usage: get_model() and returns: model