I am trying to use tensorflow serving to serve a model. when I try to apply serve component using ksonnet, I see that workload created on kubernetes(gke) is using tensorflow 1.7(gcr.io/kubeflow-images-public/tensorflow-serving-1.7:v20180604-0da89b8a).
Is there a way to specify what version of tensorflow serving in Kubeflow ?
The version of TensorFlow is determined by the TensorFlow Serving Docker image you use. If you are using the Kubeflow ksonnet prototype for TFServing the parameter modelServerImage can be used to set the image.