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float64 support in FIL core #4646
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rerun tests |
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Just a couple of comments.
@divyegala Thanks for your comments! I've addressed them, could you take another look? |
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LGTM!
rerun tests |
Codecov Report
@@ Coverage Diff @@
## branch-22.06 #4646 +/- ##
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Coverage ? 84.06%
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Files ? 252
Lines ? 20336
Branches ? 0
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Hits ? 17095
Misses ? 3241
Partials ? 0
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@gpucibot merge |
- removed default `T = float` from multi-sum - tests with float64 for multi-sum and `child_index()` - refactored multi-sum tests to reduce shared memory usage - this is needed for the tests with float64 to compile This is pull request 1 of 3 to integrate rapidsai#4646. This pull request is partly based on the work by @levsnv. Authors: - Andy Adinets (https://github.com/canonizer) Approvers: - Divye Gala (https://github.com/divyegala) - William Hicks (https://github.com/wphicks) URL: rapidsai#4648
Templatized functions related to FIL inference in preparation of `float64` support. Instantiations of templates with `float64`, or tests for `float64`, _are not included_; they will be provided in a future pull request. This is pull request 2 of 3 to integrate rapidsai#4646. This pull request is partly based on the work by @levsnv. Authors: - Andy Adinets (https://github.com/canonizer) - Levs Dolgovs (https://github.com/levsnv) - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - Divye Gala (https://github.com/divyegala) - William Hicks (https://github.com/wphicks) URL: rapidsai#4655
`float64` support in FIL core and tests. Added `float64`-based instantiations of FIL types and functions, together with `float64`-based FIL tests. Treelite and Python layers _are not covered_ here, but will be in separate pull requests. This is pull request 3 of 3 to enable `float64` support in FIL core. This is partly based on the work by @levsnv. Authors: - Andy Adinets (https://github.com/canonizer) - Levs Dolgovs (https://github.com/levsnv) Approvers: - Divye Gala (https://github.com/divyegala) URL: rapidsai#4646
- removed default `T = float` from multi-sum - tests with float64 for multi-sum and `child_index()` - refactored multi-sum tests to reduce shared memory usage - this is needed for the tests with float64 to compile This is pull request 1 of 3 to integrate rapidsai#4646. This pull request is partly based on the work by @levsnv. Authors: - Andy Adinets (https://github.com/canonizer) Approvers: - Divye Gala (https://github.com/divyegala) - William Hicks (https://github.com/wphicks) URL: rapidsai#4648
Templatized functions related to FIL inference in preparation of `float64` support. Instantiations of templates with `float64`, or tests for `float64`, _are not included_; they will be provided in a future pull request. This is pull request 2 of 3 to integrate rapidsai#4646. This pull request is partly based on the work by @levsnv. Authors: - Andy Adinets (https://github.com/canonizer) - Levs Dolgovs (https://github.com/levsnv) - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - Divye Gala (https://github.com/divyegala) - William Hicks (https://github.com/wphicks) URL: rapidsai#4655
`float64` support in FIL core and tests. Added `float64`-based instantiations of FIL types and functions, together with `float64`-based FIL tests. Treelite and Python layers _are not covered_ here, but will be in separate pull requests. This is pull request 3 of 3 to enable `float64` support in FIL core. This is partly based on the work by @levsnv. Authors: - Andy Adinets (https://github.com/canonizer) - Levs Dolgovs (https://github.com/levsnv) Approvers: - Divye Gala (https://github.com/divyegala) URL: rapidsai#4646
float64
support in FIL core and tests.Added
float64
-based instantiations of FIL types and functions, together withfloat64
-based FIL tests.Treelite and Python layers are not covered here, but will be in separate pull requests.
This is pull request 3 of 3 to enable
float64
support in FIL core. This is partly based on the work by @levsnv.