title: Tensorflow hub.load Model to TFLite
body: <p>I am trying to convert a model loaded with hub.load to TFLite.
  The model in question is universal-sentence-encoder (4) found at <a href="https://tfhub.dev/google/universal-sentence-encoder/4" rel="nofollow noreferrer">https://tfhub.dev/google/universal-sentence-encoder/4</a>
  I tried in Python with Tensorflow version 2.1.0 and 2.2.0</p>
  
  <pre><code>import tensorflow as tf
  import tensorflow_hub as hub
  
  model = hub.load("https://tfhub.dev/google/universal-sentence-encoder/4")
  converter = tf.lite.TFLiteConverter.from_keras_model(model )
  converter.experimental_new_converter = True // tried with and without
  tflite_model = converter.convert()
  </code></pre>
  
  <p>I get the following error:</p>
  
  <pre><code>    converter = tf.lite.TFLiteConverter.from_keras_model(model)
    File "...\lib\site-packages\tensorflow_core\lite\python\lite.py", line 394, in from_keras_model
      if not isinstance(model.call, _def_function.Function):
  AttributeError: '_UserObject' object has no attribute 'call'
  </code></pre>
  
  <p>From my understanding hub.load return a keras SavedModel, so shouldn't be convertible right away?</p>