code: def build_cnn_model() -> tf.keras.Model:
      model = tf.keras.Sequential(
          [
              tf.keras.Input(shape=(28, 28)),
              tf.keras.layers.Reshape(target_shape=(28, 28, 1)),
              tf.keras.layers.Conv2D(32, 3, activation="relu"),
              tf.keras.layers.Flatten(),
              tf.keras.layers.Dense(128, activation="relu"),
              tf.keras.layers.Dense(10),
          ]
      )
      return model
  
file_path: ray/python/ray/train/examples/tf/tensorflow_mnist_example.py
imports: import argparse
  import json
  import os
  import numpy
  import tensorflow
  from filelock import FileLock
  from ray.air.integrations.keras import ReportCheckpointCallback
  from ray.train import Result, RunConfig, ScalingConfig
  from ray.train.tensorflow import TensorflowTrainer
label_desc: Use image node_id 2 for calling a global function with example usage: build_cnn_model() and returns: model