Bug fixed

Fix bugs of FNNLM when isGradEfficient is on.

source/sample/fnnlm/FNNLM.cpp

@@ -331,6 +331,7 @@ void Init(FNNModel &model)
 {
     /* create embedding parameter matrix: vSize * eSize */
     InitModelTensor2D(model.embeddingW, model.vSize, model.eSize, model);
+    model.embeddingW.SetVarFlag();
     
     /* create hidden layer parameter matrics */
     for(int i = 0; i < model.hDepth; i++){
@@ -340,15 +341,19 @@ void Init(FNNModel &model)
             InitModelTensor2D(model.hiddenW[i], (model.n - 1) * model.eSize, model.hSize, model);
         else
             InitModelTensor2D(model.hiddenW[i], model.hSize, model.hSize, model);
-        
+        model.hiddenW[i].SetVarFlag();
+
         /* bias term: a row vector of hSize entries */
         InitModelTensor1D(model.hiddenB[i], model.hSize, model);
+        model.hiddenB[i].SetVarFlag();
     }
     
     /* create the output layer parameter matrix and bias term */
     int iSize = model.hDepth == 0 ? (model.n - 1) * model.eSize : model.hSize;
     InitModelTensor2D(model.outputW, iSize, model.vSize, model);
     InitModelTensor1D(model.outputB, model.vSize, model);
+    model.outputW.SetVarFlag();
+    model.outputB.SetVarFlag();
     
     /* then, we initialize model parameters using a uniform distribution in range
        of [-minmax, minmax] */