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[dask] [docs] Fix inaccuracies in API docs for Dask module (fixes #3871) #3930
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@jameslamb I love how you introduced shared templates for docstrings! However, I think there are some mistakes, that I noted below:
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
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For the consistency:
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
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LGTM! Thank you!
the most recent build on RTD did pass: https://readthedocs.org/projects/lightgbm/builds/12979086/ And docs look ok to me! https://lightgbm.readthedocs.io/en/docs-jlamb/Python-API.html For example, here's And the sklearn docs look unchanged. |
This pull request has been automatically locked since there has not been any recent activity since it was closed. To start a new related discussion, open a new issue at https://github.com/microsoft/LightGBM/issues including a reference to this. |
This PR proposes a fix to #3871.
init_score
and variouseval_*
arguments)To minimize duplication, this PR moves the
sklearn
docstrings into template strings that are then formatted with.format()
. This indirection is a little confusing, but we can at least rely on getting CI failures in thecheck-docs
task, since.format()
has to fill all template values.Notes for Reviewers
docs/jlamb
branch so we can check on readthedocs builds: https://lightgbm.readthedocs.io/en/docs-jlamb/Python-API.html.LGBMModel.__init__
that have references that are incorrect for Dask, but when I tried to templatize it I got errors from Sphinx likeLGBMClassifier.__init__:66:Inline strong start-string without end-string.
. I'll try some more things, but it's ok if we can't figure out how to fix that for this PR since we're trying to get a release out (v3.2.0 release #3872 ) and the inaccuracies are minor.learning_rate
docs that says "you can use callbacks..."objective
doc that references scikit-learn classes ("Default: ‘regression’ for LGBMRegressor...")