title: Deploying Keras Models via Google Cloud ML
body: <p>I am looking to use Google Cloud ML to host my Keras models so that I can call the API and make some predictions. I am running into some issues from the Keras side of things. </p>
  
  <p>So far I have been able to build a model using TensorFlow and deploy it on CloudML. In order for this to work I had to make some changes to my basic TF code. The changes are documented here: <a href="https://cloud.google.com/ml/docs/how-tos/preparing-models#code_changes" rel="noreferrer">https://cloud.google.com/ml/docs/how-tos/preparing-models#code_changes</a></p>
  
  <p>I have also been able to train a similar model using Keras. I can even save the model in the same export and export.meta format as I would get with TF.</p>
  
  <pre><code>from keras import backend as K
  
  saver = tf.train.Saver()
  session = K.get_session()
  saver.save(session, 'export')
  </code></pre>
  
  <p>The part I am missing is how do I add the placeholders for input and output into the graph I build on Keras?</p>