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Implement Custom Transformer to Model Deployment #15
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You'll need to include end to end test to the to do list |
Yes. The e2e tests will be included in Python SDK test |
After a model+transformer is deployed, is there a way to see the configuration in UI? |
Can you create an issue for this? |
LGTM |
* Implement Transformer to Version Endpoint * Add transformer config on deployment page UI * Update API port to 8080 as 3000 used by UI * Update swagger api spec -- add transformer * Add env vars to transformer object * Display existing transformer spec in UI * Update Transformer models gorm relation * Integrate transformer to sdk * Preload transformers without joining * Update merlin-sdk version for pyfunc-server * Address review - move transformer to models.Service * Propagate transformer related env vars * Increase timeout for local pyfunc server test * Revert timeout for local pyfunc server test * Add e2e test for transformer via python sdk test * Fix sdk syntax * Update API unit test * Propagate docker registries list * Cast env vars to string
This PR allows users to deploy their Transformer Docker image that contains pre/post-processing code.
Changes:
deploy()
function to accept new optional arg:transformer
Model version deployment page preview: