[profiling] Profile fast predict methods

CMakeLists.txt

@@ -15,6 +15,7 @@ OPTION(USE_R35 "Set to ON if your R version is not earlier than 3.5" OFF)
 OPTION(USE_TIMETAG "Set to ON to output time costs" OFF)
 OPTION(USE_DEBUG "Set to ON for Debug mode" OFF)
 OPTION(BUILD_FOR_R "Set to ON if building lib_lightgbm for use with the R package" OFF)
+OPTION(BUILD_PROFILING_TESTS "Set to ON to compile profiling executables for development and benchmarks." OFF)
 
 if(APPLE)
     OPTION(APPLE_OUTPUT_DYLIB "Output dylib shared library" OFF)
@@ -234,6 +235,12 @@ file(GLOB SOURCES
     src/treelearner/*.cpp
 )
 
+if(BUILD_PROFILING_TESTS)
+    # For profiling builds (use -DDEBUG=ON)
+    add_executable(lightgbm_profile_single_row_predict profiling/profile_single_row_predict.cpp ${SOURCES} src/c_api.cpp)
+    add_executable(lightgbm_profile_single_row_predict_fast profiling/profile_single_row_predict_fast.cpp ${SOURCES} src/c_api.cpp)
+endif(BUILD_PROFILING_TESTS)
+
 add_executable(lightgbm src/main.cpp ${SOURCES})
 add_library(_lightgbm SHARED src/c_api.cpp src/lightgbm_R.cpp ${SOURCES})
 

profiling/profile_single_row_predict.cpp

@@ -0,0 +1,27 @@
+#include <iostream>
+#include "LightGBM/c_api.h"
+
+using namespace std;
+
+int main() {
+  cout << "start\n";
+
+  BoosterHandle boosterHandle;
+  int num_iterations;
+  LGBM_BoosterCreateFromModelfile("./LightGBM_model.txt", &num_iterations, &boosterHandle);
+  cout << "Model iterations " << num_iterations<< "\n";
+
+  double vals[] = {  158.0, 311.4, 2.08207657E7, 10841.0, 0.0, 1.0, 2.0};  // 0.23829552970680268
+
+  int64_t dummy;
+
+  double score[1];
+  for (size_t i = 0; i < 1e5; ++i) {
+    LGBM_BoosterPredictForMatSingleRow(boosterHandle, vals, C_API_DTYPE_FLOAT64, 7, 1, C_API_PREDICT_NORMAL, num_iterations, "num_threads=1", &dummy, score);
+  }
+  cout << "len=" << dummy << endl;
+
+  cout << "Score = " << score[0] << "\n";
+
+  cout << "end\n";
+}

profiling/profile_single_row_predict_fast.cpp

@@ -0,0 +1,33 @@
+#include <iostream>
+#include "LightGBM/c_api.h"
+
+using namespace std;
+
+int main() {
+  cout << "start\n";
+
+  BoosterHandle boosterHandle;
+  int num_iterations;
+  LGBM_BoosterCreateFromModelfile("./LightGBM_model.txt", &num_iterations, &boosterHandle);
+  cout << "Model iterations " << num_iterations<< "\n";
+
+  double values[] = {158.0, 311.4, 2.08207657E7, 10841.0, 0.0, 1.0, 2.0};  // 0.23829552970680268
+
+
+  FastConfigHandle fastConfigHandle;
+  LGBM_BoosterPredictForMatSingleRowFastInit(boosterHandle, values, C_API_DTYPE_FLOAT64, 7, "num_threads=1", &fastConfigHandle);
+
+  int64_t dummy;
+  double score[1];
+  for (size_t i = 0; i < 1e5; ++i) {
+    LGBM_BoosterPredictForMatSingleRowFast(fastConfigHandle, C_API_PREDICT_NORMAL, num_iterations, &dummy, score);
+  }
+
+  LGBM_FastConfigFree(fastConfigHandle);
+
+  cout << "len=" << dummy << endl;
+
+  cout << "Score = " << score[0] << "\n";
+
+  cout << "end\n";
+}