code: def create_keras_model():
      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, activation="softmax"),
          ]
      )
  
      model.compile(
          loss="sparse_categorical_crossentropy",
          optimizer=tf.keras.optimizers.Adam(),
          metrics=["sparse_categorical_accuracy"],
      )
  
      return model
  
label_desc: Use image node_id 1 for calling a global function with example usage: create_keras_model() and returns: model