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#include <memory>
#include <random>
#include <chrono>
#include <algorithm>
#include <iostream>
#include <gflags/gflags.h>
#include <boost/chrono/chrono.hpp>
#include <boost/chrono/duration.hpp>
#include <boost/chrono/process_cpu_clocks.hpp>
DEFINE_int64(num_features, 1000, "");
DEFINE_int64(num_iterations, 5, "");
std::vector<double> generateLogisticData() {
auto result = std::vector<double>(FLAGS_num_features);
std::mt19937 gen(boost::chrono::system_clock::now().time_since_epoch().count());
std::normal_distribution<double> dist(0.0, 1.0);
for (auto& r: result) {
r = dist(gen);
}
std::sort(result.begin(), result.end());
std::uniform_real_distribution<double> uniform;
for (auto& r: result) {
r = (uniform(gen) < r) ? 1.0 : 0.0;
}
return result;
}
void isotonicRegression(std::vector<double>& y, const std::vector<double>& weights) {
auto n = y.size();
if (n <= 1) {
return;
}
n -= 1;
while (true) {
size_t i = 0;
bool pooled = false;
while (i < n) {
size_t k = i;
while (k < n && y[k] >= y[k+1]) {
k += 1;
}
if (y[i] != y[k]) {
double numerator = 0.0;
double denominator = 0.0;
for (size_t j = i; j <= k; j++) {
numerator += y[j] * weights[j];
denominator += weights[j];
}
for (size_t j = i; j <= k; j++) {
y[j] = numerator / denominator;
}
pooled = true;
}
i = k +1;
}
if (!pooled) {
break;
}
}
}
void runIsotonicRegression() {
const auto features = generateLogisticData();
const auto weights = std::vector<double>(FLAGS_num_features, 1.0);
auto iteration = [&]() {
const auto start = boost::chrono::process_real_cpu_clock::now();
auto scratch = features;
isotonicRegression(scratch, weights);
const auto end = boost::chrono::process_real_cpu_clock::now();
const auto delta = boost::chrono::duration_cast<boost::chrono::nanoseconds>(
end - start);
return std::chrono::nanoseconds(delta.count());
};
std::vector<std::chrono::nanoseconds> results(FLAGS_num_iterations);
for (auto& elem : results) {
elem = iteration();
}
double totalSec = 0.0;
for (const auto& elem: results) {
totalSec += elem.count() / 1e9;
}
std::cout << "Average time: " << totalSec / (results.size()) << std::endl;
}
bool test() {
std::vector<double> ys = {1, 41, 51, 1, 2, 5, 24};
std::vector<double> ws = {1, 2, 3, 4, 5, 6, 7};
std::vector<double> expected = {1.0, 13.95, 13.95, 13.95, 13.95, 13.95, 24};
isotonicRegression(ys, ws);
for (size_t i = 0; i < ys.size(); i++) {
if (abs(ys[i] - expected[i]) > 0.01) {
std::cerr << "bad test" << std::endl;
std::exit(1);
}
}
return true;
}
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
test();
runIsotonicRegression();
return 0;
}
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