[Ahub] Fix Ahub issue

changed 'auto' to 'auto &' in multiout_realizer.cpp.

Signed-off-by: SeoHyungjun <hyungjun.seo@samsung.com>

diff --git a/nntrainer/compiler/multiout_realizer.cpp b/nntrainer/compiler/multiout_realizer.cpp
index 9438e469343693fdd9e3db2227227421d71837a7..1d5ca175e6bd12b15327514678bf6122555038a7 100644 (file)
--- a/nntrainer/compiler/multiout_realizer.cpp
+++ b/nntrainer/compiler/multiout_realizer.cpp
@@ -57,7 +57,7 @@ MultioutRealizer::realize(const GraphRepresentation &reference) {
     std::vector<std::shared_ptr<LayerNode>> /**< created node */>
     multiout_nodes;
 
-  for (auto con : connections) {
+  for (auto &con : connections) {
     unsigned freq = freq_map[con];
     /// @note freq < 1 should never happen as the map entry is not created.
     /// but if it happens multiout realizer is not interested in checking if it
@@ -102,7 +102,7 @@ MultioutRealizer::realize(const GraphRepresentation &reference) {
   for (auto &node : processed) {
     ret.push_back(node);
     auto ranges = multiout_nodes[node->getName()];
-    for (auto it : ranges) {
+    for (auto &it : ranges) {
       ret.push_back(it);
     }
   }

diff --git a/nntrainer/layers/input_layer.cpp b/nntrainer/layers/input_layer.cpp
index 70a056b185d649fe0f4bfd0863fc4d5102ea918a..16d417f829d0d5e3afb183d7a2337ac3f0357080 100644 (file)
--- a/nntrainer/layers/input_layer.cpp
+++ b/nntrainer/layers/input_layer.cpp
@@ -70,7 +70,7 @@ void InputLayer::finalize(InitLayerContext &context) {
 
   std::vector<TensorDim> output_dims = context.getInputDimensions();
 
-  for (auto d : output_dims)
+  for (auto &d : output_dims)
     d.setTensorType({context.getFormat(), context.getActivationDataType()});
 
   context.setOutputDimensions(output_dims);

diff --git a/nntrainer/layers/layer_context.h b/nntrainer/layers/layer_context.h
index ad7149fec53b07a762a2da6bdd80da7bacf5efb1..35653bde0f46d5f3d35149af702994bfd2fc10f2 100644 (file)
--- a/nntrainer/layers/layer_context.h
+++ b/nntrainer/layers/layer_context.h
@@ -118,7 +118,7 @@ public:
    * @param ty data type to set
    */
   void setInputDataType(TensorDim::DataType ty) {
-    for (auto d : input_dim)
+    for (auto &d : input_dim)
       d.setDataType(ty);
   }
 

diff --git a/nntrainer/layers/layer_node.cpp b/nntrainer/layers/layer_node.cpp
index 2e9b2c23bd4bbef9e3b7d2cbb04b9f0186327e7e..cedb3caee7a7e2c25d7f5175e14fcde31445f795 100644 (file)
--- a/nntrainer/layers/layer_node.cpp
+++ b/nntrainer/layers/layer_node.cpp
@@ -523,7 +523,7 @@ LayerNode::finalize(const std::vector<TensorDim> &input_dims,
       NNTR_THROW_IF(input_dims != actual_prop_dims, std::invalid_argument)
         << "calculated input dimension is different from given input_shape "
            "property";
-      for (auto d : actual_prop_dims) {
+      for (auto &d : actual_prop_dims) {
         d.setDataType(
           str_converter<enum_class_prop_tag, nntrainer::TensorDataTypeInfo>::
             from_string(tensor_type[2]));
@@ -545,7 +545,7 @@ LayerNode::finalize(const std::vector<TensorDim> &input_dims,
       << prop_dims.size();
     actual_input_dims =
       std::vector<TensorDim>(prop_dims.begin(), prop_dims.end());
-    for (auto d : actual_input_dims) {
+    for (auto &d : actual_input_dims) {
       /// Input Tensor type of input layer needs to be float.
       d.setDataType(
         str_converter<enum_class_prop_tag,

diff --git a/nntrainer/layers/loss/loss_layer.cpp b/nntrainer/layers/loss/loss_layer.cpp
index f17b0b41a92bb8cebea6346a6e60f74b9aaa929f..40f74717f82a6d7412cdf5e59b6f6a3b1dbdd702 100644 (file)
--- a/nntrainer/layers/loss/loss_layer.cpp
+++ b/nntrainer/layers/loss/loss_layer.cpp
@@ -18,7 +18,7 @@ namespace nntrainer {
 void LossLayer::finalize(InitLayerContext &context) {
   std::vector<TensorDim> input_dim = context.getInputDimensions();
   std::vector<TensorDim> output_dim = input_dim;
-  for (auto d : output_dim)
+  for (auto &d : output_dim)
     d.setDataType(
       str_converter<enum_class_prop_tag,
                     nntrainer::TensorDataTypeInfo>::from_string("FP32"));