From adf650d2578b769e9fe0854efc1a9132c381654b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ricardo=20Montan=CC=83ana?= <rmontanana@gmail.com>
Date: Mon, 31 Jul 2023 18:49:18 +0200
Subject: [PATCH] Max threading

---
 src/BayesNet/Ensemble.cc | 14 ++++++++++++--
 src/BayesNet/Network.cc  |  5 ++---
 src/BayesNet/Network.h   |  4 ++--
 3 files changed, 16 insertions(+), 7 deletions(-)

diff --git a/src/BayesNet/Ensemble.cc b/src/BayesNet/Ensemble.cc
index 3e4d1a6..c18b51e 100644
--- a/src/BayesNet/Ensemble.cc
+++ b/src/BayesNet/Ensemble.cc
@@ -68,9 +68,19 @@ namespace bayesnet {
             throw logic_error("Ensemble has not been fitted");
         }
         Tensor y_pred = torch::zeros({ X.size(1), n_models }, kInt32);
+        //Create a threadpool
+        auto threads{ vector<thread>() };
+        auto lock = mutex();
         for (auto i = 0; i < n_models; ++i) {
-            auto ypredict = models[i]->predict(X);
-            y_pred.index_put_({ "...", i }, ypredict);
+            threads.push_back(thread([&, i]() {
+                auto ypredict = models[i]->predict(X);
+                lock.lock();
+                y_pred.index_put_({ "...", i }, ypredict);
+                lock.unlock();
+                }));
+        }
+        for (auto& thread : threads) {
+            thread.join();
         }
         return torch::tensor(voting(y_pred));
     }
diff --git a/src/BayesNet/Network.cc b/src/BayesNet/Network.cc
index f46e1e9..5f9aa93 100644
--- a/src/BayesNet/Network.cc
+++ b/src/BayesNet/Network.cc
@@ -3,8 +3,8 @@
 #include "Network.h"
 #include "bayesnetUtils.h"
 namespace bayesnet {
-    Network::Network() : laplaceSmoothing(1), features(vector<string>()), className(""), classNumStates(0), maxThreads(0.8), fitted(false) {}
-    Network::Network(float maxT) : laplaceSmoothing(1), features(vector<string>()), className(""), classNumStates(0), maxThreads(maxT), fitted(false) {}
+    Network::Network() : features(vector<string>()), className(""), classNumStates(0), fitted(false) {}
+    Network::Network(float maxT) : features(vector<string>()), className(""), classNumStates(0), maxThreads(maxT), fitted(false) {}
     Network::Network(float maxT, int smoothing) : laplaceSmoothing(smoothing), features(vector<string>()), className(""), classNumStates(0), maxThreads(maxT), fitted(false) {}
     Network::Network(Network& other) : laplaceSmoothing(other.laplaceSmoothing), features(other.features), className(other.className), classNumStates(other.getClassNumStates()), maxThreads(other.getmaxThreads()), fitted(other.fitted)
     {
@@ -132,7 +132,6 @@ namespace bayesnet {
     }
     void Network::completeFit()
     {
-
         int maxThreadsRunning = static_cast<int>(std::thread::hardware_concurrency() * maxThreads);
         if (maxThreadsRunning < 1) {
             maxThreadsRunning = 1;
diff --git a/src/BayesNet/Network.h b/src/BayesNet/Network.h
index f763dde..203daa7 100644
--- a/src/BayesNet/Network.h
+++ b/src/BayesNet/Network.h
@@ -10,11 +10,11 @@ namespace bayesnet {
         map<string, unique_ptr<Node>> nodes;
         map<string, vector<int>> dataset;
         bool fitted;
-        float maxThreads;
+        float maxThreads = 0.95;
         int classNumStates;
         vector<string> features;
         string className;
-        int laplaceSmoothing;
+        int laplaceSmoothing = 1;
         torch::Tensor samples;
         bool isCyclic(const std::string&, std::unordered_set<std::string>&, std::unordered_set<std::string>&);
         vector<double> predict_sample(const vector<int>&);