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This was only used in naive bayes, and is easy to write as a single `ElementWise` kernel.
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LGTM, just two questions.
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This applies the cleanups part of rapidsai#7317 to `cuml.naive_bayes`. It's a followup to rapidsai#7424. Highlights: - Several followup fixes from rapidsai#7424. Mostly ripping out debugging code that was leftover and no longer needed. - Removal of validation, conversion, and initialization of fitted attributes from `__init__`. - Fixed `CumlArrayDescriptor` definitions to only define fitted attributes for models that support them, rather than defining the same fitted attributes across all naive bayes estimators - Removal of `cuml.prims.array`, this module is no longer used - Simplification of code paths, removal of extraneous definitions - Docstring cleanups Given this is a very low priority module, I didn't dwell too much on the individual implementations, instead only handling the end goals in rapidsai#7317. _There are still improvements that could be made to this module_. In particular: - There are visible inefficiencies in the cupy code and category handling. Work is repeated, extraneous copies are made. Given the priorities here, I don't think this is worth working on unless someone suddenly needs these models to be much faster. - These classifiers still don't handle non-numeric inputs (like the rest of cuml does). Punting on this for now, but we likely do want to support this in the future (if for nothing else, I'd like to rip out `cuml.prims.labels` completely). I'll open a followup issue. Authors: - Jim Crist-Harif (https://github.com/jcrist) Approvers: - Victor Lafargue (https://github.com/viclafargue) URL: rapidsai#7623
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This applies the cleanups part of #7317 to
cuml.naive_bayes. It's a followup to #7424.Highlights:
__init__.CumlArrayDescriptordefinitions to only define fitted attributes for models that support them, rather than defining the same fitted attributes across all naive bayes estimatorscuml.prims.array, this module is no longer usedGiven this is a very low priority module, I didn't dwell too much on the individual implementations, instead only handling the end goals in #7317. There are still improvements that could be made to this module. In particular:
cuml.prims.labelscompletely). I'll open a followup issue.