change to std::lock_guard

src/c_api.cpp

@@ -30,7 +30,7 @@ public:
 
   Booster(const Dataset* train_data, 
     const char* parameters) {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     auto param = ConfigBase::Str2Map(parameters);
     config_.Set(param);
     // create boosting
@@ -43,13 +43,11 @@ public:
     // initialize the boosting
     boosting_->Init(&config_.boosting_config, train_data, objective_fun_.get(),
       Common::ConstPtrInVectorWrapper<Metric>(train_metric_));
-    lock.unlock();
   }
 
   void MergeFrom(const Booster* other) {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     boosting_->MergeFrom(other->boosting_.get());
-    lock.unlock();
   }
 
   ~Booster() {
@@ -57,17 +55,16 @@ public:
   }
 
   void ResetTrainingData(const Dataset* train_data) {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     train_data_ = train_data;
     ConstructObjectAndTrainingMetrics(train_data_);
     // initialize the boosting
     boosting_->ResetTrainingData(&config_.boosting_config, train_data_, 
       objective_fun_.get(), Common::ConstPtrInVectorWrapper<Metric>(train_metric_));
-    lock.unlock();
   }
 
   void ResetConfig(const char* parameters) {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     auto param = ConfigBase::Str2Map(parameters);
     if (param.count("num_class")) {
       Log::Fatal("cannot change num class during training");
@@ -77,11 +74,10 @@ public:
     }
     config_.Set(param);
     ResetTrainingData(train_data_);
-    lock.unlock();
   }
 
   void AddValidData(const Dataset* valid_data) {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     valid_metrics_.emplace_back();
     for (auto metric_type : config_.metric_types) {
       auto metric = std::unique_ptr<Metric>(Metric::CreateMetric(metric_type, config_.metric_config));
@@ -92,30 +88,24 @@ public:
     valid_metrics_.back().shrink_to_fit();
     boosting_->AddValidDataset(valid_data,
       Common::ConstPtrInVectorWrapper<Metric>(valid_metrics_.back()));
-    lock.unlock();
   }
   bool TrainOneIter() {
-    std::unique_lock<std::mutex> lock(mutex_);
-    bool ret = boosting_->TrainOneIter(nullptr, nullptr, false);
-    lock.unlock();
-    return ret;
+    std::lock_guard<std::mutex> lock(mutex_);
+    return boosting_->TrainOneIter(nullptr, nullptr, false);
   }
 
   bool TrainOneIter(const float* gradients, const float* hessians) {
-    std::unique_lock<std::mutex> lock(mutex_);
-    bool ret = boosting_->TrainOneIter(gradients, hessians, false);
-    lock.unlock();
-    return ret;
+    std::lock_guard<std::mutex> lock(mutex_);
+    return boosting_->TrainOneIter(gradients, hessians, false);
   }
 
   void RollbackOneIter() {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     boosting_->RollbackOneIter();
-    lock.unlock();
   }
 
   void PrepareForPrediction(int num_iteration, int predict_type) {
-    std::unique_lock<std::mutex> lock(mutex_);
+    std::lock_guard<std::mutex> lock(mutex_);
     boosting_->SetNumIterationForPred(num_iteration);
     bool is_predict_leaf = false;
     bool is_raw_score = false;
@@ -127,7 +117,6 @@ public:
       is_raw_score = false;
     }
     predictor_.reset(new Predictor(boosting_.get(), is_raw_score, is_predict_leaf));
-    lock.unlock();
   }
 
   void GetPredictAt(int data_idx, score_t* out_result, data_size_t* out_len) {
@@ -143,9 +132,7 @@ public:
   }
 
   void SaveModelToFile(int num_iteration, const char* filename) {
-    std::unique_lock<std::mutex> lock(mutex_);
     boosting_->SaveModelToFile(num_iteration, filename);
-    lock.unlock();
   }
 
   int GetEvalCounts() const {