Simple demo of TensorFlow 2.0's SavedModel, not very complicated

tf_2.0_savedmodel.py

import tensorflow as tf

def create_model():
    X = tf.keras.Input(shape=(10,), name='input')
    h = tf.keras.layers.Dense(10, kernel_initializer=tf.constant_initializer(1), bias_initializer=tf.constant_initializer(1))(X)
    y = tf.keras.layers.Dense(10, kernel_initializer=tf.constant_initializer(1), bias_initializer=tf.constant_initializer(1), name='output')(h)
    model = tf.keras.models.Model(inputs=[X], outputs=[y])
    return model

def run_model(model: tf.keras.Model):
    output = model.predict(np.array([[1,2,3,4,5,6,7,8,9,10]]))
    print(output)

if __name__ == "__main__":
    model = create_model()
    run_model(model)
    tf.saved_model.save(model, './data/save_model_v2')