title: Running Custom Prediction with Google Cloud AI Platform and GPU
body: <p>I am trying to deploy a MaskRCNN model to the GCP AI platform. The default online prediction doesn't work for me because my input size is bigger than the allowed limit. So, I decided to go ahead with the custom prediction route. </p>
  
  <p>With respect to custom prediction, I am trying to use a larger machine-type than what is provided by default because my model is big and needs more memory than what the default one ( mls1-c1-m2 ) provides. </p>
  
  <p>I want to deploy the model with n1-standard-4  machine type, and following is the command I am running: </p>
  
  <pre><code>gcloud beta ai-platform versions create $VERSION_NAME   --model $MODEL_NAME   --runtime-version 1.14   --python-version 3.5   --origin $MODEL_DIR   --package-uris gs://pred_02/staging/my_custom_code-0.1.tar.gz --framework tensorflow  --prediction-class predictor.MyPredictor --machine-type n1-standard-4 
  </code></pre>
  
  <p>but this throws an error: </p>
  
  <pre><code>ERROR: (gcloud.beta.ai-platform.versions.create) FAILED_PRECONDITION: Machine type n1-standard-4 only support FRAMEWORK_TENSORFLOW
  </code></pre>
  
  <p>I tried different variations of --framework arg as well but all of them throw some similar error. So, why is it throwing this error?  </p>
  
  <p>If this works, then my idea is to use this machine type with a k80 accelerator. And this would be my second question? can I run it with an accelerator for custom prediction?</p>