fix issue #215

Xtra-Computing · Apr 29, 2020 · 250d5a8 · 250d5a8
1 parent d3f3906
commit 250d5a8
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Showing 2 changed files with 31 additions and 8 deletions.
diff --git a/python/thundersvm/thundersvm.py b/python/thundersvm/thundersvm.py
@@ -438,7 +438,7 @@ def load_from_string(self, data):
                 thundersvm.set_memory_size(c_void_p(self.model), self.max_mem_size)
         thundersvm.load_from_string_scikit(c_void_p(self.model), data)
         self._post_load_init()
-    
+
     def _post_load_init(self):
         degree = (c_int * 1)()
         gamma = (c_float * 1)()
@@ -483,11 +483,12 @@ def _post_load_init(self):
         thundersvm.get_rho(rho, rho_size, c_void_p(self.model))
         self.intercept_ = np.frombuffer(rho, dtype=np.float32).astype(float)
 
-        # if self.kernel == 'linear':
-        #     coef = (c_float * (self.n_binary_model * self.n_sv))()
-        #     thundersvm.get_linear_coef(coef, self.n_binary_model, self.n_features, c_void_p(self.model))
-        #     self.coef_ = np.array([coef[index] for index in range(0, self.n_binary_model * self.n_features)]).astype(float)
-        #     self.coef_ = np.reshape(self.coef_, (self.n_binary_model, self.n_features))
+        if self.kernel == 'linear':
+            coef = (c_float * (self.n_binary_model * self.n_features))()
+            thundersvm.get_linear_coef(coef, self.n_binary_model, self.n_features, c_void_p(self.model))
+            self.coef_ = np.frombuffer(coef, dtype=np.float32) \
+                .astype(float) \
+                .reshape((self.n_binary_model, self.n_features))
 
         self.kernel = kernel.value.decode()
         self.degree = degree[0]
@@ -508,8 +509,8 @@ def __getstate__(self):
     def __setstate__(self, state):
       self.__dict__.update(state)
       if '_saved_as_str' in state:
-        self.load_from_string(state['_saved_as_str']) 
-    
+        self.load_from_string(state['_saved_as_str'])
+
 
 class SVC(SvmModel, ClassifierMixin):
     _impl = 'c_svc'

diff --git a/src/thundersvm/model/svmmodel.cpp b/src/thundersvm/model/svmmodel.cpp
@@ -183,6 +183,14 @@ string SvmModel::save_to_string() {
         }
         s_model << endl;
     }
+    if (param.kernel_type == SvmParam::LINEAR) {
+        s_model << "coef " << endl;
+        const float_type *linear_coef_data = linear_coef.host_data();
+        for (int i = 0; i < linear_coef.size(); i++) {
+            s_model << setprecision(16) << linear_coef_data[i] << " ";
+        }
+        s_model << endl;
+    }
     s_model << "SV " << endl;
     const float_type *coef_data = coef.host_data();
     for (int i = 0; i < sv.size(); i++) {
@@ -274,6 +282,20 @@ void SvmModel::load_from_string(string data) {
             for (int i = 0; i < n_binary_models; ++i) {
                 iss >> probB[i];
             }
+        } else if (feature == "coef"){
+            string line;
+            getline(iss, line);
+            getline(iss, line);
+            int size = 0;
+            for (int i = 0; line[i] !='\0'; i++){
+                if(line[i] == ' ')
+                    size++;
+            }
+            linear_coef.resize(size);
+            stringstream ss(line);
+            for(int i = 0; i < size; i++){
+                ss >> linear_coef.host_data()[i];
+            }
         } else if (feature == "SV") {
             sv.clear();
             coef.resize((n_classes - 1) * n_total_sv);