* Update the Docker image for T2T to use a newer version of T2T library
* Add parameters to set the GCP secret; we need GCP credentials to
read from GCS even if reading a public bucket. We default
to the parameters that are created automatically in the case of a GKE
deployment.
* Create a v1alpha2 template for the job that uses PVC.
* Improvements to the tensor2tensor traininer for the GitHub summarization example.
* Simplify the launcher; we can just pass through most command line arguments and not
use environment variables and command line arguments.
* This makes it easier to control the job just by setting the parameters in the template
rather than having to rebuild the images.
* Add a Makefile to build the image.
* Replace the tensor2tensor jsonnet with a newer version of the jsonnet used with T2T.
* Address reviewer comments.
* Install pip packages as user Jovyan
* Rely on implicit string conversion with concatenation in template file.
* Distributed training using tensor2tensor
* Use a transformer model to train the github issue summarization
problem
* Dockerfile for building training image
* ksonnet component for deploying tfjob
Fixes https://github.com/kubeflow/examples/issues/43
* Fix lint issues
Jeremy Lewi
Ankush Agarwal