mirror of
https://github.com/NVIDIA/nvbench.git
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86 lines
2.3 KiB
Plaintext
86 lines
2.3 KiB
Plaintext
/*
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* Copyright 2023 NVIDIA Corporation
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*
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* Licensed under the Apache License, Version 2.0 with the LLVM exception
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* (the "License"); you may not use this file except in compliance with
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* the License.
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*
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* You may obtain a copy of the License at
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*
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* http://llvm.org/foundation/relicensing/LICENSE.txt
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <nvbench/detail/stdrel_criterion.cuh>
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#include <nvbench/stopping_criterion.cuh>
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#include <nvbench/types.cuh>
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#include "test_asserts.cuh"
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#include <algorithm>
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#include <numeric>
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#include <random>
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#include <vector>
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void test_const()
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{
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nvbench::criterion_params params;
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nvbench::detail::stdrel_criterion criterion;
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criterion.initialize(params);
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for (int i = 0; i < 5; i++)
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{ // nvbench wants at least 5 to compute the standard deviation
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criterion.add_measurement(42.0);
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}
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ASSERT(criterion.is_finished());
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}
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std::vector<double> generate(double mean, double rel_std_dev, int size)
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{
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static std::mt19937::result_type seed = 0;
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std::mt19937 gen(seed++);
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std::vector<nvbench::float64_t> v(static_cast<std::size_t>(size));
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std::normal_distribution<nvbench::float64_t> dist(mean, mean * rel_std_dev);
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std::generate(v.begin(), v.end(), [&]{ return dist(gen); });
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return v;
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}
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void test_stdrel()
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{
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const nvbench::int64_t size = 10;
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const nvbench::float64_t mean = 42.0;
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const nvbench::float64_t max_noise = 0.1;
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nvbench::criterion_params params;
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params.set_float64("max-noise", max_noise);
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nvbench::detail::stdrel_criterion criterion;
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criterion.initialize(params);
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for (nvbench::float64_t measurement: generate(mean, max_noise / 2, size))
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{
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criterion.add_measurement(measurement);
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}
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ASSERT(criterion.is_finished());
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params.set_float64("max-noise", max_noise);
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criterion.initialize(params);
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for (nvbench::float64_t measurement: generate(mean, max_noise * 2, size))
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{
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criterion.add_measurement(measurement);
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}
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ASSERT(!criterion.is_finished());
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}
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int main()
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{
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test_const();
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test_stdrel();
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}
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