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Briefly describe the changes included in this Pull Request.
How is this patch tested?
I have written tests (not required for typo or doc fix) and confirmed the proposed feature/bug-fix/change works.
Does this PR change any dependencies?
No. You can skip this section.
Yes. Make sure the dependencies are resolved correctly, and list changes here.
Does this PR add a new feature? If so, have you added samples on website?
No. You can skip this section.
Yes. Make sure you have added samples following below steps.
Find the corresponding markdown file for your new feature in website/docs/documentation folder.
Make sure you choose the correct class estimators/transformers and namespace.
Follow the pattern in markdown file and add another section for your new API, including pyspark, scala (and .NET potentially) samples.
Make sure the DocTable points to correct API link.
Navigate to website folder, and run yarn run start to make sure the website renders correctly.
Don't forget to add <!--pytest-codeblocks:cont--> before each python code blocks to enable auto-tests for python samples.
Make sure the WebsiteSamplesTests job pass in the pipeline.
Hey @mhamilton723 👋!
Thank you so much for contributing to our repository 🙌.
Someone from SynapseML Team will be reviewing this pull request soon.
We use semantic commit messages to streamline the release process.
Before your pull request can be merged, you should make sure your first commit and PR title start with a semantic prefix.
This helps us to create release messages and credit you for your hard work!
Examples of commit messages with semantic prefixes:
fix: Fix LightGBM crashes with empty partitions
feat: Make HTTP on Spark back-offs configurable
docs: Update Spark Serving usage
build: Add codecov support
perf: improve LightGBM memory usage
refactor: make python code generation rely on classes
style: Remove nulls from CNTKModel
test: Add test coverage for CNTKModel
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Related Issues/PRs
#xxx
What changes are proposed in this pull request?
Briefly describe the changes included in this Pull Request.
How is this patch tested?
Does this PR change any dependencies?
Does this PR add a new feature? If so, have you added samples on website?
website/docs/documentationfolder.Make sure you choose the correct class
estimators/transformersand namespace.DocTablepoints to correct API link.yarn run startto make sure the website renders correctly.<!--pytest-codeblocks:cont-->before each python code blocks to enable auto-tests for python samples.WebsiteSamplesTestsjob pass in the pipeline.