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Refactor reduction logic for fixed-point types #12652

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merged 8 commits into from
Feb 7, 2023
Merged

Refactor reduction logic for fixed-point types #12652

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e561e82
Refactor reduction logic for fixed-point types
davidwendt Jan 30, 2023
399e99c
Merge branch 'branch-23.04' into rework-fixed-point-reduction
davidwendt Jan 30, 2023
77f65a5
Merge branch 'branch-23.04' into rework-fixed-point-reduction
davidwendt Jan 31, 2023
2a226c2
Merge branch 'branch-23.04' into rework-fixed-point-reduction
davidwendt Jan 31, 2023
e899175
Merge branch 'branch-23.04' into rework-fixed-point-reduction
davidwendt Feb 2, 2023
d863335
remove unused using statement
davidwendt Feb 2, 2023
3a643e5
fix copyright style violation
davidwendt Feb 2, 2023
c386e45
Merge branch 'branch-23.04' into rework-fixed-point-reduction
davidwendt Feb 3, 2023
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31 changes: 3 additions & 28 deletions cpp/src/reductions/simple.cuh
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
/*
* Copyright (c) 2019-2022, NVIDIA CORPORATION.
* Copyright (c) 2019-2023, NVIDIA CORPORATION.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -115,37 +115,12 @@ std::unique_ptr<scalar> fixed_point_reduction(
{
using Type = device_storage_type_t<DecimalXX>;

auto dcol = cudf::column_device_view::create(col, stream);
auto simple_op = Op{};

// Cast initial value
std::optional<Type> const initial_value = [&] {
if (init.has_value() && init.value().get().is_valid()) {
using ScalarType = cudf::scalar_type_t<Type>;
return std::optional<Type>(
static_cast<const ScalarType*>(&init.value().get())->value(stream));
} else {
return std::optional<Type>(std::nullopt);
}
}();

auto result = [&] {
if (col.has_nulls()) {
auto f = simple_op.template get_null_replacing_element_transformer<Type>();
auto it = thrust::make_transform_iterator(dcol->pair_begin<Type, true>(), f);
return cudf::reduction::detail::reduce(it, col.size(), simple_op, initial_value, stream, mr);
} else {
auto f = simple_op.template get_element_transformer<Type>();
auto it = thrust::make_transform_iterator(dcol->begin<Type>(), f);
return cudf::reduction::detail::reduce(it, col.size(), simple_op, initial_value, stream, mr);
}
}();
auto result = simple_reduction<Type, Type, Op>(col, init, stream, mr);

auto const scale = [&] {
if (std::is_same_v<Op, cudf::reduction::op::product>) {
auto const valid_count = static_cast<int32_t>(col.size() - col.null_count());
return numeric::scale_type{col.type().scale() *
(valid_count + (initial_value.has_value() ? 1 : 0))};
return numeric::scale_type{col.type().scale() * (valid_count + (init.has_value() ? 1 : 0))};
} else if (std::is_same_v<Op, cudf::reduction::op::sum_of_squares>) {
return numeric::scale_type{col.type().scale() * 2};
}
Expand Down
3 changes: 1 addition & 2 deletions cpp/tests/reductions/reduction_tests.cpp
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
/*
* Copyright (c) 2019-2022, NVIDIA CORPORATION.
* Copyright (c) 2019-2023, NVIDIA CORPORATION.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -294,7 +294,6 @@ TYPED_TEST(SumReductionTest, Sum)
.second);
}

using ReductionTypes = cudf::test::Types<int16_t, int32_t, float, double>;
TYPED_TEST_SUITE(ReductionTest, cudf::test::NumericTypes);

TYPED_TEST(ReductionTest, Product)
Expand Down