Fix number of threads spawned
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8e9090d283
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59c1cf5b3b
@ -190,8 +190,11 @@ namespace bayesnet {
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const double n_samples = static_cast<double>(samples.size(1));
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auto worker = [&](std::pair<const std::string, std::unique_ptr<Node>>& node, int i) {
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std::string threadName = "FitWorker-" + std::to_string(i);
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#if defined(__linux__)
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pthread_setname_np(pthread_self(), threadName.c_str());
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semaphore.acquire();
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#else
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pthread_setname_np(threadName.c_str());
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#endif
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double numStates = static_cast<double>(node.second->getNumStates());
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double smoothing_factor = 0.0;
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switch (smoothing) {
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@ -212,6 +215,7 @@ namespace bayesnet {
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};
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int i = 0;
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for (auto& node : nodes) {
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semaphore.acquire();
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threads.emplace_back(worker, std::ref(node), i++);
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}
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for (auto& thread : threads) {
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@ -236,8 +240,11 @@ namespace bayesnet {
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result = torch::zeros({ samples.size(1), classNumStates }, torch::kFloat64);
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auto worker = [&](const torch::Tensor& sample, int i) {
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std::string threadName = "PredictWorker-" + std::to_string(i);
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#if defined(__linux__)
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pthread_setname_np(pthread_self(), threadName.c_str());
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semaphore.acquire();
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#else
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pthread_setname_np(threadName.c_str());
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#endif
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auto psample = predict_sample(sample);
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auto temp = torch::tensor(psample, torch::kFloat64);
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{
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@ -247,6 +254,7 @@ namespace bayesnet {
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semaphore.release();
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};
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for (int i = 0; i < samples.size(1); ++i) {
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semaphore.acquire();
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const torch::Tensor sample = samples.index({ "...", i });
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threads.emplace_back(worker, sample, i);
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}
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