Merge branch 'master' into custom_stack_trace_refines

paddle/gserver/layers/CudnnBatchNormLayer.cpp

@@ -114,27 +114,30 @@ void CudnnBatchNormLayer::backward(const UpdateCallback& callback) {
   } else {
     create(tmpBiasGrad_, 1, channels_, &betaGrad);
   }
-#if CUDNN_VERSION < 5000
+
   // because of the different api of cudnn v4 and v5.
-  if (weight_->getWGrad()) {
+  if (hl_get_cudnn_lib_version() < 5000) {
-    create(tmpWGrad_, 1, channels_, &gammaGrad);
+    if (weight_->getWGrad()) {
-  }
+      create(tmpWGrad_, 1, channels_, &gammaGrad);
-  if (biases_ && biases_->getWGrad()) {
+    }
-    create(tmpBiasGrad_, 1, channels_, &betaGrad);
+    if (biases_ && biases_->getWGrad()) {
+      create(tmpBiasGrad_, 1, channels_, &betaGrad);
+    }
   }
-#endif
+
   hl_batch_norm_backward(ioDesc_, input, ioDesc_, outGrad,
                          ioDesc_, inGrad, bnParamDesc_,
                          gamma, gammaGrad, betaGrad,
                          EPS, savedMean, savedInvVar);
 
-#if CUDNN_VERSION < 5000
   // because of the different api of cudnn v4 and v5.
-  if (weight_->getWGrad() && biases_->getWGrad()) {
+  if (hl_get_cudnn_lib_version() < 5000) {
-    weight_->getWGrad()->add(*tmpWGrad_);
+    if (weight_->getWGrad() && biases_->getWGrad()) {
-    biases_->getWGrad()->add(*tmpBiasGrad_);
+      weight_->getWGrad()->add(*tmpWGrad_);
+      biases_->getWGrad()->add(*tmpBiasGrad_);
+    }
   }
-#endif
+
   {
     REGISTER_TIMER_INFO("WeightUpdate", getName().c_str());
     biases_->getParameterPtr()->incUpdate(callback);