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[Enhancement] Add float datatype support to rocAucScore #3074

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[Enhancement] Add float datatype support to rocAucScore #3074

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49d0c89
Update roc_auc_score.cpp
icfaust Feb 16, 2025
d6832ec
Update roc_auc_score.cpp
icfaust Feb 16, 2025
6b8d263
Update roc_auc_score.cpp
icfaust Feb 16, 2025
545aa74
Update roc_auc_score.cpp
icfaust Feb 16, 2025
a953a76
Update roc_auc_score.h
icfaust Feb 16, 2025
5522e57
Update roc_auc_score.cpp
icfaust Feb 16, 2025
b95d450
Update roc_auc_score.cpp
icfaust Feb 16, 2025
c89cd33
clang-formatting and comment
icfaust Feb 17, 2025
c2ee01e
Merge branch 'uxlfoundation:main' into roc_auc_float
icfaust Mar 3, 2025
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4 changes: 3 additions & 1 deletion cpp/daal/include/data_management/data/internal/roc_auc_score.h
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,9 @@ namespace data_management
{
namespace internal
{
DAAL_EXPORT double rocAucScore(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction);
// Default template to double for backwards compatability in daal4py (<2025.5)
template <typename DataType = double>
DAAL_EXPORT DataType rocAucScore(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction);
} // namespace internal
} // namespace data_management
} // namespace daal
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35 changes: 20 additions & 15 deletions cpp/daal/src/data_management/roc_auc_score.cpp
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Expand Up @@ -35,21 +35,21 @@ using namespace daal::internal;
using namespace daal::services;
using namespace daal::services::internal;

template <daal::CpuType cpu>
services::Status rocAucScoreImpl(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction, double & score)
template <typename DataType, daal::CpuType cpu>
services::Status rocAucScoreImpl(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction, DataType & score)
{
services::Status s;
SafeStatus safeStat;
const size_t nElements = truePrediction->getNumberOfRows();
TArrayScalable<IdxValType<double>, cpu> predict(nElements);
TArrayScalable<IdxValType<DataType>, cpu> predict(nElements);
DAAL_CHECK_MALLOC(predict.get());

const size_t blockSizeDefault = 256;
const size_t nBlocks = nElements / blockSizeDefault + !!(nElements % blockSizeDefault);

ReadColumns<double, cpu> testPredictionBlock(testPrediction.get(), 0, 0, nElements);
ReadColumns<DataType, cpu> testPredictionBlock(testPrediction.get(), 0, 0, nElements);
DAAL_CHECK_BLOCK_STATUS(testPredictionBlock);
const double * const testPredictionPtr = testPredictionBlock.get();
const DataType * const testPredictionPtr = testPredictionBlock.get();

daal::threader_for(nBlocks, nBlocks, [&](const size_t iBlock) {
const size_t blockBegin = iBlock * blockSizeDefault;
Expand All @@ -63,12 +63,12 @@ services::Status rocAucScoreImpl(const NumericTablePtr & truePrediction, const N
}
});

daal::parallel_sort<double>(predict.get(), predict.get() + nElements);
daal::parallel_sort<DataType>(predict.get(), predict.get() + nElements);

size_t rank = 1;
size_t elementsInBlock = 1;
size_t i = 0;
TArray<double, cpu> predictedRank(nElements);
TArray<DataType, cpu> predictedRank(nElements);
DAAL_CHECK_MALLOC(predictedRank.get());
while (i < nElements)
{
Expand All @@ -84,14 +84,14 @@ services::Status rocAucScoreImpl(const NumericTablePtr & truePrediction, const N
for (size_t j = 0; j < elementsInBlock; ++j)
{
const size_t idx = predict[i + j].index;
predictedRank[idx] = static_cast<double>(rank) + ((static_cast<double>(elementsInBlock) - double(1.0)) * double(0.5));
predictedRank[idx] = static_cast<DataType>(rank) + ((static_cast<DataType>(elementsInBlock) - DataType(1.0)) * DataType(0.5));
}
rank += elementsInBlock;
i += elementsInBlock;
}

double nPos = double(0);
double filteredRankSum = double(0);
DataType nPos = DataType(0);
DataType filteredRankSum = DataType(0);
for (size_t iBlock = 0; iBlock < nBlocks; ++iBlock)
{
const size_t blockBegin = iBlock * blockSizeDefault;
Expand All @@ -108,21 +108,26 @@ services::Status rocAucScoreImpl(const NumericTablePtr & truePrediction, const N
}
}
}
const double nNeg = static_cast<double>(nElements) - nPos;
score = (filteredRankSum - (nPos * (nPos + double(1.0)) * double(0.5))) / (nPos * nNeg);
const DataType nNeg = static_cast<DataType>(nElements) - nPos;
score = (filteredRankSum - (nPos * (nPos + DataType(1.0)) * DataType(0.5))) / (nPos * nNeg);
return s;
}

DAAL_EXPORT double rocAucScore(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction)
template <typename DataType>
DAAL_EXPORT DataType rocAucScore(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction)
{
double score = double(0);
#define DAAL_ROC_AUC_SCORE(cpuId, ...) rocAucScoreImpl<cpuId>(__VA_ARGS__);
DataType score = DataType(0);
#define DAAL_ROC_AUC_SCORE(cpuId, ...) rocAucScoreImpl<DataType, cpuId>(__VA_ARGS__);

DAAL_DISPATCH_FUNCTION_BY_CPU_SAFE(DAAL_ROC_AUC_SCORE, truePrediction, testPrediction, score);

#undef DAAL_ROC_AUC_SCORE
return score;
}

template DAAL_EXPORT float rocAucScore<float>(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction);
template DAAL_EXPORT double rocAucScore<double>(const NumericTablePtr & truePrediction, const NumericTablePtr & testPrediction);

} // namespace internal
} // namespace data_management
} // namespace daal
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