diff --git a/c/tensorNet.cpp b/c/tensorNet.cpp
index e2e19b3df..438a16291 100644
--- a/c/tensorNet.cpp
+++ b/c/tensorNet.cpp
@@ -612,7 +612,9 @@ bool tensorNet::ProfileModel(const std::string& deployFile,			   // name for caf
 			nvinfer1::ITensor* tensor = blobNameToTensor->find(outputs[n].c_str());
 		
 			if( !tensor )
+			{
 				LogError(LOG_TRT "failed to retrieve tensor for Output \"%s\"\n", outputs[n].c_str());
+			}
 			else
 			{
 			#if NV_TENSORRT_MAJOR >= 4
@@ -1136,9 +1138,13 @@ bool tensorNet::LoadNetwork( const char* prototxt_path_, const char* model_path_
 		loadedPlugins = initLibNvInferPlugins(&gLogger, "");
 
 		if( !loadedPlugins )
+		{
 			LogError(LOG_TRT "failed to load NVIDIA plugins\n");
+		}
 		else
+		{
 			LogVerbose(LOG_TRT "completed loading NVIDIA plugins.\n");
+		}
 	}
 #endif
 
diff --git a/examples/actionnet/actionnet.cpp b/examples/actionnet/actionnet.cpp
index b5a42e5a7..3ee16003b 100644
--- a/examples/actionnet/actionnet.cpp
+++ b/examples/actionnet/actionnet.cpp
@@ -149,9 +149,13 @@ int main( int argc, char** argv )
 		const int class_id = net->Classify(image, input->GetWidth(), input->GetHeight(), &confidence);
 
 		if( class_id >= 0 )
+		{
 			LogVerbose("actionnet:  %2.5f%% class #%i (%s)\n", confidence * 100.0f, class_id, net->GetClassDesc(class_id));	
+		}
 		else
+		{
 			LogError("actionnet:  failed to classify frame\n");
+		}
 
 		// overlay the results
 		if( class_id >= 0 )
@@ -194,4 +198,3 @@ int main( int argc, char** argv )
 	LogVerbose("actionnet:  shutdown complete.\n");
 	return 0;
 }
-