message: Add snippets to save TF Lite model as a file
diff: @@ -42,7 +42,7 @@ root.v1 = tf.Variable(3.)
  root.v2 = tf.Variable(2.)
  root.f = tf.function(lambda x: root.v1 * root.v2 * x)
  -# Save the model.
  +# Save the model in SavedModel format.
  export_dir = "/tmp/test_saved_model"
  input_data = tf.constant(1., shape=[1, 1])
  to_save = root.f.get_concrete_function(input_data)
  @@ -51,6 +51,10 @@ tf.saved_model.save(root, export_dir, to_save)
  # Convert the model.
  converter = tf.lite.TFLiteConverter.from_saved_model(export_dir)
  tflite_model = converter.convert()
  +
  +# Save the TF Lite model.
  +with tf.gfile.GFile('model.tflite', 'wb') as f:
  + f.write(tflite_model)
  ```
  This API does not have the option of specifying the input shape of any input
  @@ -87,6 +91,10 @@ model.fit(x, y, epochs=50)
  # Convert the model.
  converter = tf.lite.TFLiteConverter.from_keras_model(model)
  tflite_model = converter.convert()
  +
  +# Save the TF Lite model.
  +with tf.gfile.GFile('model.tflite', 'wb') as f:
  + f.write(tflite_model)
  ```
  ### Converting a concrete function <a name="concrete_function"></a>
  @@ -115,6 +123,10 @@ concrete_func = root.f.get_concrete_function(input_data)
  # functions is under development.
  converter = tf.lite.TFLiteConverter.from_concrete_functions([concrete_func])
  tflite_model = converter.convert()
  +
  +# Save the TF Lite model.
  +with tf.gfile.GFile('model.tflite', 'wb') as f:
  + f.write(tflite_model)
  ```
  ### End-to-end MobileNet conversion <a name="mobilenet"></a>
  