udacity TensorFlow Lite Chap.2-3 example code

example2_3_1.py

import tensorflow as tf
# Store data for x and y
x = [-1, 0, 1, 2, 3, 4]
y = [-3,-1, 1, 3, 5, 7]

# Create a simple Keras model
model = tf.keras.models.Sequential(
  [tf.keras.layers.Dense(units=1, input_shape=[1])])
model.compile(optimizer='sgd', loss='mean_squared_error')
model.fit(x, y, epochs=500)

import pathlib
# Export the SavedModel
export_dir = '/tmp/saved_model'
tf.saved_model.save(model, export_dir)

# Convert the model
converter = tf.lite.TFLiteConverter.from_saved_model(export_dir)
tflite_model = converter.convert()

# Save the model
tflite_model_file = pathlib.Path('/tmp/foo.tflite')
tflite_model_file.write_bytes(tflite_model)