How to save a TensorFlow Hub model in SavedModels format? - tensorflow2.0

Question

I'd like to load a model from TensorFlow Hub and save it to disk. I tried:
import tensorflow as tf
import tensorflow_hub as hub
def save_module(url, save_path):
with tf.Graph().as_default():
module = hub.load(url)
tf.saved_model.save(module, save_path)
save_module("https://tfhub.dev/google/universal-sentence-encoder/4", "./saved-module")
But this fails with:
Traceback (most recent call last):
File "C:\project\python-env\lib\site-packages\tensorflow\python\client\session.py", line 1365, in _do_call
return fn(*args)
File "C:\project\python-env\lib\site-packages\tensorflow\python\client\session.py", line 1349, in _run_fn
return self._call_tf_sessionrun(options, feed_dict, fetch_list,
File "C:\project\python-env\lib\site-packages\tensorflow\python\client\session.py", line 1441, in _call_tf_sessionrun
return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
tensorflow.python.framework.errors_impl.FailedPreconditionError: 2 root error(s) found.
(0) Failed precondition: Error while reading resource variable EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27 from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27)
[[{{node EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27/Read/ReadVariableOp}}]]
[[EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_22/Read/ReadVariableOp/_287]]
(1) Failed precondition: Error while reading resource variable EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27 from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27)
[[{{node EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27/Read/ReadVariableOp}}]]
0 successful operations.
0 derived errors ignored.
The answer must use the TensorFlow 2 API. Ideally, I want to accomplish this without Keras but I'll also accept answers that use it. Any ideas?

Answer 1

I couldn't get this working without Keras, but in any case this works:
import tensorflow as tf
import tensorflow_hub as hub
def save_module(url, save_path):
module = hub.KerasLayer(url)
model = tf.keras.Sequential(module)
tf.saved_model.save(model, save_path)
save_module("https://tfhub.dev/google/universal-sentence-encoder/4", "./saved-module")