fixed_point + cudf::binary_operation API Changes
#7435
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codereport
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Thanks for the quick turn around |
Well this PR is going to be modified based on the proposal laid out here: #7442. Post any comments if you have them. |
codereport
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fixed_point cudf::binary_operation specified output_type parameterfixed_point + cudf::binary_operation API Changes
Codecov Report
@@ Coverage Diff @@
## branch-0.19 #7435 +/- ##
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+ Coverage 81.88% 82.30% +0.42%
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Files 101 101
Lines 16900 17273 +373
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+ Hits 13838 14216 +378
+ Misses 3062 3057 -5
Continue to review full report at Codecov.
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Fixed! This was an awesome catch! Thank you! |
hyperbolic2346
requested changes
Mar 8, 2021
codereport
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Mar 9, 2021
kkraus14
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Mar 9, 2021
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rerun tests |
hyperbolic2346
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Mar 10, 2021
codereport
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breaking
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@shwina @trxcllnt @brandon-b-miller @jrhemstad Can we get this going as my other PRs are blocked by this. |
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@gpucibot merge |
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Mar 16, 2021
@codereport is making changes to the way `DIV` will behave for fixed-point types #7435. This PR contains Java changes to support those changes. Note: This is a draft until #7435 is merged Authors: - Raza Jafri (@razajafri) Approvers: - MithunR (@mythrocks) - Jason Lowe (@jlowe) - Gera Shegalov (@gerashegalov) URL: #7527
hyperbolic2346
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Mar 25, 2021
This resolves rapidsai#7442 Recently while working with @razajafri on `fixed_point` binary ops, it became clear that the `cudf::binary_operation` is breaking the "easy to use, **hard to misuse**" # 1 design guideline. I knew about this but I slotted it as technical debt to be cleaned up later. Long story short, after discussions with both @razajafri, @jrhemstad and comments on the rapidsai#7442, we will implement the following: * [x] For `fixed_point` + `cudf::binary_operation` + `DIV` always **use** the `cudf::data_type output_type` parameter * [x] ~~For `fixed_point` + `cudf::binary_operation` + `TRUE_DIV`, require that the columns/scalars provided as arguments (`lhs` and `rhs`) will result in the specified `data_type`/`scale`~~ * [x] Provide a convenience function (something like `binary_operation_fixed_point_scale()`) that will compute the "expected" scale given two input columns/scalars and a `binary_operator` * [x] Remove `TRUE_DIV` * [x] Add unit tests for different output data_types * [x] Update Python/Cython **This will be a breaking change for all `fixed_point` + `cudf::binary_operation`.** Authors: - Conor Hoekstra (@codereport) Approvers: - Keith Kraus (@kkraus14) - Mike Wilson (@hyperbolic2346) URL: rapidsai#7435
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This resolves #7442
Recently while working with @razajafri on
fixed_pointbinary ops, it became clear that thecudf::binary_operationis breaking the "easy to use, hard to misuse" # 1 design guideline. I knew about this but I slotted it as technical debt to be cleaned up later. Long story short, after discussions with both @razajafri, @jrhemstad and comments on the #7442, we will implement the following:fixed_point+cudf::binary_operation+DIValways use thecudf::data_type output_typeparameterForfixed_point+cudf::binary_operation+TRUE_DIV, require that the columns/scalars provided as arguments (lhsandrhs) will result in the specifieddata_type/scalebinary_operation_fixed_point_scale()) that will compute the "expected" scale given two input columns/scalars and abinary_operatorTRUE_DIVThis will be a breaking change for all
fixed_point+cudf::binary_operation.