title: ValueError: Importing a SavedModel with tf.saved_model.load requires a 'tags=' argument
body: <p>I'm following tutorial <a href="https://www.tensorflow.org/tutorials/images/hub_with_keras" rel="noreferrer">Hub with Keras</a> with tensorflow 1.14. I didn't pip install tf-nightly-gpu as it <a href="https://pypi.org/project/tf-nightly-gpu/#files" rel="noreferrer">does not seem to be available</a> for MacOS. All went ok though until the keras.Sequential() :</p>
  
  <pre><code>import tensorflow_hub as hub
  from tensorflow.keras import layers
  classifier_url ="https://tfhub.dev/google/imagenet/resnet_v2_50/feature_vector/3"
  IMAGE_SHAPE = (224, 224)
  classifier = tf.keras.Sequential([
       hub.KerasLayer(classifier_url, input_shape=IMAGE_SHAPE+(3,))
  ])
  </code></pre>
  
  <p>Last line gives following error:</p>
  
  <pre><code>ValueError: Importing a SavedModel with tf.saved_model.load requires a 'tags=' argument if there is more than one MetaGraph. Got 'tags=None', but there are 2 MetaGraphs in the SavedModel with tag sets [[], ['train']]. Pass a 'tags=' argument to load this SavedModel.
  </code></pre>
  
  <p>Is it related to the tensorflow version or is it related to something else?</p>
  
  <p>MacOS High Sierra 10.13.1
  python 3.6.8
  tensorflow 1.14.0</p>