code: def main(_):
      """Train a model against the MNIST dataset and print performance metrics."""
      mnist = tf.keras.datasets.mnist
  
      (x_train, y_train), (x_test, y_test) = mnist.load_data()
      x_train, x_test = x_train / 255.0, x_test / 255.0
  
      model = get_keras_model()
  
      loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(
          from_logits=True
      )
      optimizer = tf.keras.optimizers.Adam(
          learning_rate=FLAGS.learning_rate
      )
  
      model.compile(
          optimizer=optimizer, loss=loss_fn, metrics=["accuracy"]
      )
  
      print(
          f"Training model with learning rate={FLAGS.learning_rate} for {FLAGS.epochs} epochs."
      )
      model.fit(x_train, y_train, epochs=FLAGS.epochs)
  
      print("Model performance: ")
      model.evaluate(x_test, y_test, verbose=2)
  
imports: import warnings
  import tensorflow
  from absl import app, flags
label_desc: Use image node_id 2 for calling a global function with example usage: main(_) without return types