fix deterministic, part2 (#3578)

* fix deterministic, part2 * Apply suggestions from code review
microsoft · Nov 23, 2020 · 5285974 · 5285974
1 parent d6f20e3
commit 5285974
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Showing 3 changed files with 33 additions and 18 deletions.
diff --git a/src/objective/binary_objective.hpp b/src/objective/binary_objective.hpp
@@ -20,7 +20,9 @@ namespace LightGBM {
 */
 class BinaryLogloss: public ObjectiveFunction {
  public:
-  explicit BinaryLogloss(const Config& config, std::function<bool(label_t)> is_pos = nullptr) {
+  explicit BinaryLogloss(const Config& config,
+                         std::function<bool(label_t)> is_pos = nullptr)
+      : deterministic_(config.deterministic) {
     sigmoid_ = static_cast<double>(config.sigmoid);
     if (sigmoid_ <= 0.0) {
       Log::Fatal("Sigmoid parameter %f should be greater than zero", sigmoid_);
@@ -36,7 +38,8 @@ class BinaryLogloss: public ObjectiveFunction {
     }
   }
 
-  explicit BinaryLogloss(const std::vector<std::string>& strs) {
+  explicit BinaryLogloss(const std::vector<std::string>& strs)
+      : deterministic_(false) {
     sigmoid_ = -1;
     for (auto str : strs) {
       auto tokens = Common::Split(str.c_str(), ':');
@@ -137,14 +140,14 @@ class BinaryLogloss: public ObjectiveFunction {
     double suml = 0.0f;
     double sumw = 0.0f;
     if (weights_ != nullptr) {
-      #pragma omp parallel for schedule(static) reduction(+:suml, sumw)
+      #pragma omp parallel for schedule(static) reduction(+:suml, sumw) if (!deterministic_)
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += is_pos_(label_[i]) * weights_[i];
         sumw += weights_[i];
       }
     } else {
       sumw = static_cast<double>(num_data_);
-      #pragma omp parallel for schedule(static) reduction(+:suml)
+      #pragma omp parallel for schedule(static) reduction(+:suml) if (!deterministic_)
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += is_pos_(label_[i]);
       }
@@ -202,6 +205,7 @@ class BinaryLogloss: public ObjectiveFunction {
   double scale_pos_weight_;
   std::function<bool(label_t)> is_pos_;
   bool need_train_;
+  const bool deterministic_;
 };
 
 }  // namespace LightGBM

diff --git a/src/objective/regression_objective.hpp b/src/objective/regression_objective.hpp
@@ -92,11 +92,13 @@ namespace LightGBM {
 */
 class RegressionL2loss: public ObjectiveFunction {
  public:
-  explicit RegressionL2loss(const Config& config) {
+  explicit RegressionL2loss(const Config& config)
+      : deterministic_(config.deterministic) {
     sqrt_ = config.reg_sqrt;
   }
 
-  explicit RegressionL2loss(const std::vector<std::string>& strs) {
+  explicit RegressionL2loss(const std::vector<std::string>& strs)
+      : deterministic_(false) {
     sqrt_ = false;
     for (auto str : strs) {
       if (str == std::string("sqrt")) {
@@ -172,14 +174,14 @@ class RegressionL2loss: public ObjectiveFunction {
     double suml = 0.0f;
     double sumw = 0.0f;
     if (weights_ != nullptr) {
-      #pragma omp parallel for schedule(static) reduction(+:suml, sumw)
+      #pragma omp parallel for schedule(static) reduction(+:suml, sumw) if (!deterministic_)
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += label_[i] * weights_[i];
         sumw += weights_[i];
       }
     } else {
       sumw = static_cast<double>(num_data_);
-      #pragma omp parallel for schedule(static) reduction(+:suml)
+      #pragma omp parallel for schedule(static) reduction(+:suml) if (!deterministic_)
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += label_[i];
       }
@@ -196,6 +198,7 @@ class RegressionL2loss: public ObjectiveFunction {
   /*! \brief Pointer of weights */
   const label_t* weights_;
   std::vector<label_t> trans_label_;
+  const bool deterministic_;
 };
 
 /*!

diff --git a/src/objective/xentropy_objective.hpp b/src/objective/xentropy_objective.hpp
@@ -43,10 +43,11 @@ namespace LightGBM {
 */
 class CrossEntropy: public ObjectiveFunction {
  public:
-  explicit CrossEntropy(const Config&) {
-  }
+  explicit CrossEntropy(const Config& config)
+      : deterministic_(config.deterministic) {}
 
-  explicit CrossEntropy(const std::vector<std::string>&) {
+  explicit CrossEntropy(const std::vector<std::string>&)
+      : deterministic_(false) {
   }
 
   ~CrossEntropy() {}
@@ -113,14 +114,16 @@ class CrossEntropy: public ObjectiveFunction {
     double suml = 0.0f;
     double sumw = 0.0f;
     if (weights_ != nullptr) {
-      #pragma omp parallel for schedule(static) reduction(+:suml, sumw)
+      #pragma omp parallel for schedule(static) reduction(+:suml, sumw) if (!deterministic_)
+
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += label_[i] * weights_[i];
         sumw += weights_[i];
       }
     } else {
       sumw = static_cast<double>(num_data_);
-      #pragma omp parallel for schedule(static) reduction(+:suml)
+      #pragma omp parallel for schedule(static) reduction(+:suml) if (!deterministic_)
+
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += label_[i];
       }
@@ -140,19 +143,21 @@ class CrossEntropy: public ObjectiveFunction {
   const label_t* label_;
   /*! \brief Weights for data */
   const label_t* weights_;
+  const bool deterministic_;
 };
 
 /*!
 * \brief Objective function for alternative parameterization of cross-entropy (see top of file for explanation)
 */
 class CrossEntropyLambda: public ObjectiveFunction {
  public:
-  explicit CrossEntropyLambda(const Config&) {
+  explicit CrossEntropyLambda(const Config& config)
+      : deterministic_(config.deterministic) {
     min_weight_ = max_weight_ = 0.0f;
   }
 
-  explicit CrossEntropyLambda(const std::vector<std::string>&) {
-  }
+  explicit CrossEntropyLambda(const std::vector<std::string>&)
+      : deterministic_(false) {}
 
   ~CrossEntropyLambda() {}
 
@@ -239,14 +244,16 @@ class CrossEntropyLambda: public ObjectiveFunction {
     double suml = 0.0f;
     double sumw = 0.0f;
     if (weights_ != nullptr) {
-      #pragma omp parallel for schedule(static) reduction(+:suml, sumw)
+      #pragma omp parallel for schedule(static) reduction(+:suml, sumw) if (!deterministic_)
+
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += label_[i] * weights_[i];
         sumw += weights_[i];
       }
     } else {
       sumw = static_cast<double>(num_data_);
-      #pragma omp parallel for schedule(static) reduction(+:suml)
+      #pragma omp parallel for schedule(static) reduction(+:suml) if (!deterministic_)
+
       for (data_size_t i = 0; i < num_data_; ++i) {
         suml += label_[i];
       }
@@ -268,6 +275,7 @@ class CrossEntropyLambda: public ObjectiveFunction {
   label_t min_weight_;
   /*! \brief Maximum weight found during init */
   label_t max_weight_;
+  const bool deterministic_;
 };
 
 }  // end namespace LightGBM