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/***************************************************************************
* Copyright (c) 2016, Johan Mabille, Sylvain Corlay and Wolf Vollprecht *
* *
* Distributed under the terms of the BSD 3-Clause License. *
* *
* The full license is in the file LICENSE, distributed with this software. *
****************************************************************************/
#include <benchmark/benchmark.h>
#include "xtensor/xarray.hpp"
#include "xtensor/xreducer.hpp"
namespace xt
{
namespace reducer
{
template <class E, class X>
void reducer_reducer(benchmark::State& state, const E& x, E& res, const X& axes)
{
for (auto _ : state)
{
res = sum(x, axes);
benchmark::DoNotOptimize(res.data());
}
}
template <class E, class X>
void reducer_immediate_reducer(benchmark::State& state, const E& x, E& res, const X& axes)
{
for (auto _ : state)
{
res = sum(x, axes, evaluation_strategy::immediate);
benchmark::DoNotOptimize(res.data());
}
}
xarray<double> u = ones<double>({10, 100000});
xarray<double> v = ones<double>({100000, 10});
xarray<double> res2 = ones<double>({1});
std::vector<std::size_t> axis0 = {0};
std::vector<std::size_t> axis1 = {1};
std::vector<std::size_t> axis_both = {0, 1};
static auto res0 = xarray<double>::from_shape({100000});
static auto res1 = xarray<double>::from_shape({10});
BENCHMARK_CAPTURE(reducer_reducer, 10x100000 / axis 0, u, res0, axis0);
BENCHMARK_CAPTURE(reducer_reducer, 10x100000 / axis 1, u, res1, axis1);
BENCHMARK_CAPTURE(reducer_reducer, 100000x10 / axis 1, v, res1, axis0);
BENCHMARK_CAPTURE(reducer_reducer, 100000x10 / axis 0, v, res0, axis1);
BENCHMARK_CAPTURE(reducer_reducer, 100000x10 / axis both, v, res2, axis_both);
BENCHMARK_CAPTURE(reducer_immediate_reducer, 10x100000 / axis 0, u, res0, axis0);
BENCHMARK_CAPTURE(reducer_immediate_reducer, 10x100000 / axis 1, u, res1, axis1);
BENCHMARK_CAPTURE(reducer_immediate_reducer, 100000x10 / axis 1, v, res1, axis0);
BENCHMARK_CAPTURE(reducer_immediate_reducer, 100000x10 / axis 0, v, res0, axis1);
BENCHMARK_CAPTURE(reducer_immediate_reducer, 100000x10 / axis both, v, res2, axis_both);
template <class E, class X>
inline auto reducer_manual_strided_reducer(benchmark::State& state, const E& x, E& res, const X& axes)
{
using value_type = typename E::value_type;
std::size_t stride = x.strides()[axes[0]];
std::size_t offset_end = x.strides()[axes[0]] * x.shape()[axes[0]];
std::size_t offset_iter = 0;
if (axes[0] == 1)
{
offset_iter = x.strides()[0];
}
else if (axes[0] == 0)
{
offset_iter = x.strides()[1];
}
for (auto _ : state)
{
for (std::size_t j = 0; j < res.shape()[0]; ++j)
{
auto begin = x.data() + (offset_iter * j);
auto end = begin + offset_end;
value_type temp = *begin;
begin += stride;
for (; begin < end; begin += stride)
{
temp += *begin;
}
res(j) = temp;
}
benchmark::DoNotOptimize(res.data());
}
}
BENCHMARK_CAPTURE(reducer_manual_strided_reducer, 10x100000 / axis 0, u, res0, axis0);
BENCHMARK_CAPTURE(reducer_manual_strided_reducer, 10x100000 / axis 1, u, res1, axis1);
BENCHMARK_CAPTURE(reducer_manual_strided_reducer, 100000x10 / axis 1, v, res1, axis0);
BENCHMARK_CAPTURE(reducer_manual_strided_reducer, 100000x10 / axis 0, v, res0, axis1);
}
}
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