* Replace double quotes for field values (ks convention) * Recreate the ksonnet application from scratch * Fix pip commands to find requirements and redo installation, fix ks param set * Use sed replace instead of ks param set. * Add cells to first show JobSpec and then apply * Upgrade T2T, fix conflicting problem types * Update docker images * Reduce to 200k samples for vocab * Use Jupyter notebook service account * Add illustrative gsutil commands to show output files, specify index files glob explicitly * List files after index creation step * Use the model in current repository and not upstream t2t * Update Docker images * Expose TF Serving Rest API at 9001 * Spawn terminal from the notebooks ui, no need to go to lab |
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docker | ||
kubeflow | ||
src | ||
.dockerignore | ||
.gitignore | ||
README.md | ||
code-search.ipynb |
README.md
Code Search on Kubeflow
This demo implements End-to-End Code Search on Kubeflow.
Prerequisites
NOTE: If using the JupyterHub Spawner on a Kubeflow cluster, use the Docker image
gcr.io/kubeflow-images-public/kubeflow-codelab-notebook
which has baked all the pre-prequisites.
-
Kubeflow Latest
This notebook assumes a Kubeflow cluster is already deployed. See Getting Started with Kubeflow. -
Python 2.7
(bundled withpip
) For this demo, we will use Python 2.7. This restriction is due to Apache Beam, which does not support Python 3 yet (See BEAM-1251). -
Google Cloud SDK
This example will use tools from the Google Cloud SDK. The SDK must be authenticated and authorized. See Authentication Overview. -
Ksonnet 0.12
We use Ksonnet to write Kubernetes jobs in a declarative manner to be run on top of Kubeflow.
Getting Started
To get started, follow the instructions below.
NOTE: We will assume that the Kubeflow cluster is available at kubeflow.example.com
. Make sure
you replace this with the true FQDN of your Kubeflow cluster in any subsequent instructions.
-
Spawn a new JupyterLab instance inside the Kubeflow cluster by pointing your browser to https://kubeflow.example.com/hub and clicking "Start My Server".
-
In the Image text field, enter
gcr.io/kubeflow-images-public/kubeflow-codelab-notebook:v20180808-v0.2-22-gcfdcb12
. This image contains all the pre-requisites needed for the demo. -
Once spawned, you should be redirected to the Jupyter Notebooks UI.
-
Spawn a new Terminal and run
$ git clone --branch=master --depth=1 https://github.com/kubeflow/examples
This will create an examples folder. It is safe to close the terminal now.
-
Navigate back to the Jupyter Notebooks UI and navigate to
examples/code_search
. Open the Jupyter notebookcode-search.ipynb
and follow it along.
Acknowledgements
This project derives from hamelsmu/code_search.