code: def get_model():
      """Constracts a model."""
      with mirrored_strategy.scope():
          model_ = tf.keras.Sequential(
              [
                  tf.keras.layers.Conv2D(
                      32, 3, activation="relu", input_shape=(28, 28, 1)
                  ),
                  tf.keras.layers.MaxPooling2D(),
                  tf.keras.layers.Flatten(),
                  tf.keras.layers.Dense(64, activation="relu"),
                  tf.keras.layers.Dense(10),
              ]
          )
  
      model_.compile(
          loss=tf.keras.losses.SparseCategoricalCrossentropy(
              from_logits=True
          ),
          optimizer="adam",
          metrics=["accuracy"],
      )
      return model_
  
file_path: cloud/src/python/tensorflow_cloud/core/tests/testdata/save_and_load.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling a global function with example usage: get_model() and returns: model_