Merge pull request #180 from shijiashuai/fix-memory-leak

fix memory leak
Xtra-Computing · Nov 18, 2019 · 831a8c4 · 831a8c4
2 parents e71013a + 9f58e21
commit 831a8c4
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Showing 11 changed files with 34 additions and 4 deletions.
diff --git a/include/thundersvm/model/nusvc.h b/include/thundersvm/model/nusvc.h
@@ -11,6 +11,9 @@
  * @brief Nu-Support Vector Machine for classification
  */
 class NuSVC : public SVC {
+public:
+    ~NuSVC() override = default;
+
 protected:
     void train_binary(const DataSet &dataset, int i, int j, SyncArray<float_type> &alpha, float_type &rho) override;
 

diff --git a/include/thundersvm/model/nusvr.h b/include/thundersvm/model/nusvr.h
@@ -14,6 +14,8 @@ class NuSVR : public SVR {
 public:
     void train(const DataSet &dataset, SvmParam param) override;
 
+    ~NuSVR() override = default;
+
 protected:
     void model_setup(const DataSet &dataset, SvmParam &param) override;
 

diff --git a/include/thundersvm/model/oneclass_svc.h b/include/thundersvm/model/oneclass_svc.h
@@ -16,6 +16,8 @@ class OneClassSVC : public SvmModel {
 
     vector<float_type> predict(const DataSet::node2d &instances, int batch_size) override;
 
+    ~OneClassSVC() override = default;
+
 protected:
     void model_setup(const DataSet &dataset, SvmParam &param) override;
 

diff --git a/include/thundersvm/model/svc.h b/include/thundersvm/model/svc.h
@@ -21,6 +21,7 @@ class SVC : public SvmModel {
 
     vector<float_type> predict(const DataSet::node2d &instances, int batch_size) override;
 
+    ~SVC() override = default;
 protected:
     /**
      * train a binary SVC model \f$SVM_{i,j}\f$ for class i and class j.

diff --git a/include/thundersvm/model/svmmodel.h b/include/thundersvm/model/svmmodel.h
@@ -98,7 +98,7 @@ class SvmModel {
 
 	//set max_memory_size during training and prediction (input unit Byte)
 	void set_max_memory_size_Byte(size_t size);
-	
+
     //return n_binary_models
     int get_n_binary_models() const;
 
@@ -120,6 +120,9 @@ class SvmModel {
 
     //return param.probability
     const bool is_prob() const;
+
+    virtual ~SvmModel() = default;
+
 protected:
 
     /**

diff --git a/include/thundersvm/model/svr.h b/include/thundersvm/model/svr.h
@@ -18,6 +18,8 @@ class SVR : public SvmModel {
 public:
     void train(const DataSet &dataset, SvmParam param) override;
 
+    ~SVR() override = default;
+
 protected:
     void model_setup(const DataSet &dataset, SvmParam &param) override;
 

diff --git a/include/thundersvm/solver/csmosolver.h b/include/thundersvm/solver/csmosolver.h
@@ -16,6 +16,8 @@ class CSMOSolver {
     void solve(const KernelMatrix &k_mat, const SyncArray<int> &y, SyncArray<float_type> &alpha, float_type &rho,
                SyncArray<float_type> &f_val, float_type eps, float_type Cp, float_type Cn, int ws_size, int max_iter) const;
 
+    virtual ~CSMOSolver() = default;
+
 protected:
     void init_f(const SyncArray<float_type> &alpha, const SyncArray<int> &y, const KernelMatrix &k_mat,
                 SyncArray<float_type> &f_val) const;

diff --git a/include/thundersvm/solver/nusmosolver.h b/include/thundersvm/solver/nusmosolver.h
@@ -13,6 +13,7 @@
 class NuSMOSolver : public CSMOSolver {
 public:
     explicit NuSMOSolver(bool for_svr) : for_svr(for_svr) {};
+    ~NuSMOSolver() override = default;
 protected:
     float_type
     calculate_rho(const SyncArray<float_type> &f_val, const SyncArray<int> &y, SyncArray<float_type> &alpha,

diff --git a/include/thundersvm/util/metric.h b/include/thundersvm/util/metric.h
@@ -15,12 +15,16 @@ class Metric {
     virtual string name() = 0;
 
     virtual float_type score(const vector<float_type> &predict_y, const vector<float_type> &ground_truth_y) = 0;
+
+    virtual ~Metric() = default;
 };
 
 /**
  * @brief Accuracy
  */
 class Accuracy : public Metric {
+public:
+    ~Accuracy() override = default;
     string name() override;
 
     /**
@@ -36,6 +40,8 @@ class Accuracy : public Metric {
  * @brief Mean Squared Error
  */
 class MSE : public Metric {
+public:
+    ~MSE() override = default;
     string name() override;
 
     /**

diff --git a/src/thundersvm/svm_R_interface.cpp b/src/thundersvm/svm_R_interface.cpp
@@ -275,7 +275,9 @@ extern "C" {
             if (metric) {
                 std::cout << metric->name() << " = " << metric->score(predict_y, train_dataset.y()) << std::endl;
             }
+            delete metric;
         }
+        delete model;
         return succeed;
 //        model->train(train_dataset, param_cmd);
 //        model->save_to_file(model_file_path);
@@ -333,5 +335,7 @@ extern "C" {
         if (metric) {
             LOG(INFO) << metric->name() << " = " << metric->score(predict_y, predict_dataset.y());
         }
+        delete model;
+        delete metric;
     }
 }
diff --git a/src/thundersvm/svm_interface_api.cpp b/src/thundersvm/svm_interface_api.cpp
@@ -87,6 +87,8 @@ extern "C" {
         if (metric) {
             LOG(INFO) << metric->name() << " = " << metric->score(predict_y, train_dataset.y()) << std::endl;
         }
+        delete model;
+        delete metric;
         return;
     }
     void thundersvm_train(int argc, char **argv) {
@@ -97,7 +99,7 @@ extern "C" {
         parser.param_cmd.kernel_type = SvmParam::RBF;
         parser.param_cmd.C = 100;
         parser.param_cmd.gamma = 0;
-        parser.param_cmd.nu = 0.1; 
+        parser.param_cmd.nu = 0.1;
         parser.param_cmd.epsilon = 0.001;
         */
         DataSet train_dataset;
@@ -155,6 +157,8 @@ extern "C" {
         if (metric) {
             LOG(INFO) << metric->name() << " = " << metric->score(predict_y, predict_dataset.y());
         }
+        delete model;
+        delete metric;
     }
 
     void thundersvm_predict(int argc, char **argv){
@@ -174,11 +178,11 @@ extern "C" {
         predict_dataset.load_from_file(predict_file_path);
         thundersvm_predict_sub(predict_dataset, parser, model_file_path, output_file_path);
     }
-    
+
     void load_from_python_interface(float *y, char **x, int len){
         dataset_python.load_from_python(y, x, len);
     }
-    
+
     void thundersvm_train_after_parse(char **option, int len, char *file_name){
         CMDParser parser;
         parser.parse_python(len, option);