Printing decoding speed

decoder/include/Decoder.hpp

@@ -25,7 +25,7 @@ class Decoder
   public :
 
   Decoder(ReadingMachine & machine);
-  void decode(BaseConfig & config, std::size_t beamSize, bool debug);
+  void decode(BaseConfig & config, std::size_t beamSize, bool debug, bool printAdvancement);
   void evaluate(const Config & config, std::filesystem::path modelPath, const std::string goldTSV);
   std::vector<std::pair<float,std::string>> getF1Scores(const std::set<std::string> & colNames) const;
   std::vector<std::pair<float,std::string>> getAlignedAccs(const std::set<std::string> & colNames) const;

decoder/src/Decoder.cpp

@@ -5,11 +5,15 @@ Decoder::Decoder(ReadingMachine & machine) : machine(machine)
 {
 }
 
-void Decoder::decode(BaseConfig & config, std::size_t beamSize, bool debug)
+void Decoder::decode(BaseConfig & config, std::size_t beamSize, bool debug, bool printAdvancement)
 {
   machine.getClassifier()->getNN()->train(false);
   config.addPredicted(machine.getPredicted());
 
+  constexpr int printInterval = 50;
+  int nbExamplesProcessed = 0;
+  auto pastTime = std::chrono::high_resolution_clock::now();
+
   try
   {
   config.setState(machine.getStrategy().getInitialState());
@@ -53,6 +57,16 @@ void Decoder::decode(BaseConfig & config, std::size_t beamSize, bool debug)
     transition->apply(config);
     config.addToHistory(transition->getName());
 
+    if (printAdvancement)
+      if (++nbExamplesProcessed >= printInterval)
+      {
+        auto actualTime = std::chrono::high_resolution_clock::now();
+        double seconds = std::chrono::duration<double, std::milli>(actualTime-pastTime).count() / 1000.0;
+        pastTime = actualTime;
+        fmt::print(stderr, "\rdecoding... speed={:<5}ex/s\r", (int)(nbExamplesProcessed/seconds));
+        nbExamplesProcessed = 0;
+      }
+
     auto movement = machine.getStrategy().getMovement(config, transition->getName());
     if (debug)
       fmt::print(stderr, "(Transition,Newstate,Movement) = ({},{},{})\n", transition->getName(), movement.first, movement.second);

decoder/src/macaon_decode.cpp

@@ -23,6 +23,7 @@ po::options_description getOptionsDescription()
   po::options_description opt("Optional");
   opt.add_options()
     ("debug,d", "Print debuging infos on stderr")
+    ("silent", "Don't print speed and progress")
     ("help,h", "Produce this help message");
 
   desc.add(req).add(opt);
@@ -72,6 +73,7 @@ int main(int argc, char * argv[])
   auto inputTXT = variables.count("inputTXT") ? variables["inputTXT"].as<std::string>() : "";
   auto mcdFile = variables["mcd"].as<std::string>();
   bool debug = variables.count("debug") == 0 ? false : true;
+  bool printAdvancement = !debug && variables.count("silent") == 0 ? true : false;
 
   if (dictPaths.empty())
     util::error(fmt::format("no '{}' files were found, and none were given. Has the model been trained yet ?", fmt::format(ReadingMachine::defaultDictFilename, "")));
@@ -87,7 +89,7 @@ int main(int argc, char * argv[])
 
     BaseConfig config(mcdFile, inputTSV, inputTXT);
 
-    decoder.decode(config, 1, debug);
+    decoder.decode(config, 1, debug, printAdvancement);
 
     config.print(stdout);
   } catch(std::exception & e) {util::error(e);}

trainer/src/macaon_train.cpp

@@ -23,6 +23,7 @@ po::options_description getOptionsDescription()
   po::options_description opt("Optional");
   opt.add_options()
     ("debug,d", "Print debuging infos on stderr")
+    ("silent", "Don't print speed and progress")
     ("trainTXT", po::value<std::string>()->default_value(""),
       "Raw text file of the training corpus")
     ("devTSV", po::value<std::string>()->default_value(""),
@@ -73,6 +74,7 @@ int main(int argc, char * argv[])
   auto devRawFile = variables["devTXT"].as<std::string>();
   auto nbEpoch = variables["nbEpochs"].as<int>();
   bool debug = variables.count("debug") == 0 ? false : true;
+  bool printAdvancement = !debug && variables.count("silent") == 0 ? true : false;
 
   fmt::print(stderr, "Training using device : {}\n", NeuralNetworkImpl::device.str());
 
@@ -94,14 +96,12 @@ int main(int argc, char * argv[])
 
   for (int i = 0; i < nbEpoch; i++)
   {
-    float loss = trainer.epoch(!debug);
+    float loss = trainer.epoch(printAdvancement);
     machine.getStrategy().reset();
     auto devConfig = devGoldConfig;
     if (debug)
       fmt::print(stderr, "Decoding dev :\n");
-    else
-      fmt::print(stderr, "\r{:80}\rDecoding dev...", " ");
-    decoder.decode(devConfig, 1, debug);
+    decoder.decode(devConfig, 1, debug, printAdvancement);
     machine.getStrategy().reset();
     decoder.evaluate(devConfig, modelPath, devTsvFile);
     std::vector<std::pair<float,std::string>> devScores = decoder.getF1Scores(machine.getPredicted());