Added a hands-on self-containted MLflow/Ray Serve deployment example#22192
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simon-mo merged 2 commits intoray-project:masterfrom Feb 8, 2022
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Signed-off-by: Jules S.Damji <jules@anyscale.com>
architkulkarni
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Feb 8, 2022
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Looks great, thanks for adding this! I'll make a followup issue to run this code sample in CI using Sphinx's literalinclude. I'll need to figure out where to install mlflow in the CI setup but it should be straightforward.
Signed-off-by: Jules S.Damji <jules@anyscale.com>
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Signed-off-by: Jules S.Damji jules@anyscale.com
Why are these changes needed?
To augment examples in Ray Serve's Integration with Model Registries section,
I added a hands-on self-contained example of how to use
mlflow.sklearn.autolog(), which logsall the metrics, parameters, and artifacts to the local model registry; and a deployment class that
loads the registered model as a
pyfuncmodel and does the prediction.This complete example augments the previous partial code snippet.
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scripts/format.shto lint the changes in this PR.