* Add the web-ui for the mnist example
Copy the mnist web app from
https://github.com/googlecodelabs/kubeflow-introduction
* Update the web app
* Change "server-name" argument to "model-name" because this is what
is.
* Update the prediction client code; The prediction code was copied
from https://github.com/googlecodelabs/kubeflow-introduction and
that model used slightly different values for the input names
and outputs.
* Add a test for the mnist_client code; currently it needs to be run
manually.
* Fix the label selector for the mnist service so that it matches the
TFServing deployment.
* Delete the old copy of mnist_client.py; we will go with the copy in ewb-ui from https://github.com/googlecodelabs/kubeflow-introduction
* Delete model-deploy.yaml, model-train.yaml, and tf-user.yaml.
The K8s resources for training and deploying the model are now in ks_app.
* Fix tensorboard; tensorboard only partially works behind Ambassador. It seems like some requests don't work behind a reverse proxy.
* Fix lint.
* This is the first step in adding E2E tests for the mnist example.
* Add a Makefile and .jsonnet file to build the Docker images using GCB
* Define an Argo workflow to trigger the image builds on pre & post submit.
Related to: #460
Jeremy Lewi