* Add estimator example for github issues
This is code input for doc about writing Keras for tfjob.
There are few todos:
1. bug in dataset injection, can't raise number of steps
2. intead of adding hostpath for data, we should have quick job + pvc
for this
* pyling
* wip
* confirmed working on minikube
* pylint
* remove t2t, add documentation
* add note about storageclass
* fix link
* remove code redundancy
* adress review
* small language fix
* Some of the code is copied over from https://github.com/kubeflow/katib/tree/master/examples/GKEDemo
* I think it makes sense to centralize all the code in a single place.
* Update the controller program (git-issue-summarize-demo.go) so that can
specify the Docker image containing the training code.
* Create a ksonnet deployment for running the controller on the cluster.
* The HP tuning job isn't functional here's an incomplete list of issues
* The training jobs launched fail because they don't have GCP credentials
so they can't download the data.
* We don't actually extract and report metrics back to Katib.
Related to: kubeflow/katib#116
* Make it easier to demo serving and run in Katacoda
* Allow the model path to be specified via environment variables so that
we could potentially load the model from PVC.
* Continue to bake the model into the image so that we don't need to train
in order to serve.
* Parameterize download_data.sh so we could potentially fetch different sources.
* Update the Makefile so that we can build and set the image for the serving
component.
* Fix lint.
* Update the serving docs.
* Create a end-to-end kubeflow example using seq2seq model (4/n)
* Move from a custom tornado server to a seldon-core model
Related to #11
* Update to use gcr.io registry for serving image
Michelle Casbon