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Amy 767ecd240d Use the client libs to do a GCS copy instead of gsutil (#558) 
* use gcs client libs to copy checkpoint dir

* more minor cleanup, use tagged image, use newer pipeline param spec. syntax.
pylint cleanup.
added set_memory_limit() to notebook pipeline training steps.
modified the pipelines definitions to use the user-defined params as defaults.

* put a retry loop around the copy_blob
 		2019-05-17 14:00:11 -07:00
..
components Use the client libs to do a GCS copy instead of gsutil (#558) 2019-05-17 14:00:11 -07:00
example_pipelines Use the client libs to do a GCS copy instead of gsutil (#558) 2019-05-17 14:00:11 -07:00
README.md import of Pipelines Github issue summarization examples & tutorial (#507) 2019-04-18 17:57:54 -07:00
tutorial.md import of Pipelines Github issue summarization examples & tutorial (#507) 2019-04-18 17:57:54 -07:00

README.md

Kubeflow Pipelines - GitHub Issue Summarization

This Kubeflow Pipelines example shows how to build a web app that summarizes GitHub issues using Kubeflow Pipelines to train and serve a model. The pipeline trains a Tensor2Tensor model on GitHub issue data, learning to predict issue titles from issue bodies. It then exports the trained model and deploys the exported model using Tensorflow Serving. The final step in the pipeline launches a web app, which interacts with the TF-Serving instance in order to get model predictions.

You can follow this example as a codelab: g.co/codelabs/kubecon18.
Or, you can run it as a Cloud shell Tutorial. The source for the Cloud Shell tutorial is here.