code: def build_model() -> tf.keras.Model:
      model = tf.keras.Sequential(
          [
              tf.keras.layers.InputLayer(input_shape=(100,)),
              tf.keras.layers.Dense(10),
              tf.keras.layers.Dense(1),
          ]
      )
      return model
  
file_path: ray/python/ray/train/examples/tf/tensorflow_regression_example.py
imports: import argparse
  import tensorflow
  import ray
  from ray import train
  from ray.air.integrations.keras import ReportCheckpointCallback
  from ray.data.preprocessors import Concatenator
  from ray.train import Result, ScalingConfig
  from ray.train.tensorflow import TensorflowTrainer
label_desc: Use image node_id 1 for calling a global function with example usage: build_model() and returns: model