Merge branch 'master' into added-trainer

src/main/resources/templates/mxnet/CNNPredictor.ftl

@@ -13,8 +13,8 @@ class ${tc.fileNameWithoutEnding}{
 public:
     const std::string json_file = "model/${tc.fullArchitectureName}/${tc.architectureName}_newest-symbol.json";
     const std::string param_file = "model/${tc.fullArchitectureName}/${tc.architectureName}_newest-0000.params";
-    const std::vector<std::string> input_keys = {"data"};
-    //const std::vector<std::string> input_keys = {${tc.join(tc.architectureInputs, ",", "\"", "\"")}};
+    //const std::vector<std::string> input_keys = {"data"};
+    const std::vector<std::string> input_keys = {${tc.join(tc.architectureInputs, ",", "\"", "\"")}};
     const std::vector<std::vector<mx_uint>> input_shapes = {<#list tc.architecture.inputs as input>{1,${tc.join(input.definition.type.dimensions, ",")}}<#if input?has_next>,</#if></#list>};
     const bool use_gpu = false;
 
@@ -28,8 +28,8 @@ public:
         if(handle) MXPredFree(handle);
     }
 
-    void predict(${tc.join(tc.architectureInputs, ", ", "const vector<float> &", "")},
-                 ${tc.join(tc.architectureOutputs, ", ", "vector<float> &", "")}){
+    void predict(${tc.join(tc.architectureInputs, ", ", "const std::vector<float> &", "")},
+                 ${tc.join(tc.architectureOutputs, ", ", "std::vector<float> &", "")}){
 <#list tc.architectureInputs as inputName>
         MXPredSetInput(handle, "data", ${inputName}.data(), ${inputName}.size());
         //MXPredSetInput(handle, "${inputName}", ${inputName}.data(), ${inputName}.size());

src/test/resources/target_code/CNNPredictor_Alexnet.h

@@ -13,8 +13,8 @@ class CNNPredictor_Alexnet{
 public:
     const std::string json_file = "model/Alexnet/Alexnet_newest-symbol.json";
     const std::string param_file = "model/Alexnet/Alexnet_newest-0000.params";
-    const std::vector<std::string> input_keys = {"data"};
     //const std::vector<std::string> input_keys = {"data"};
+    const std::vector<std::string> input_keys = {"data"};
     const std::vector<std::vector<mx_uint>> input_shapes = {{1,3,224,224}};
     const bool use_gpu = false;
 
@@ -28,8 +28,8 @@ public:
         if(handle) MXPredFree(handle);
     }
 
-    void predict(const vector<float> &data,
-                 vector<float> &predictions){
+    void predict(const std::vector<float> &data,
+                 std::vector<float> &predictions){
         MXPredSetInput(handle, "data", data.data(), data.size());
         //MXPredSetInput(handle, "data", data.data(), data.size());
 

src/test/resources/target_code/CNNPredictor_CifarClassifierNetwork.h

@@ -13,8 +13,8 @@ class CNNPredictor_CifarClassifierNetwork{
 public:
     const std::string json_file = "model/CifarClassifierNetwork/CifarClassifierNetwork_newest-symbol.json";
     const std::string param_file = "model/CifarClassifierNetwork/CifarClassifierNetwork_newest-0000.params";
-    const std::vector<std::string> input_keys = {"data"};
     //const std::vector<std::string> input_keys = {"data"};
+    const std::vector<std::string> input_keys = {"data"};
     const std::vector<std::vector<mx_uint>> input_shapes = {{1,3,32,32}};
     const bool use_gpu = false;
 
@@ -28,8 +28,8 @@ public:
         if(handle) MXPredFree(handle);
     }
 
-    void predict(const vector<float> &data,
-                 vector<float> &softmax){
+    void predict(const std::vector<float> &data,
+                 std::vector<float> &softmax){
         MXPredSetInput(handle, "data", data.data(), data.size());
         //MXPredSetInput(handle, "data", data.data(), data.size());
 

src/test/resources/target_code/CNNPredictor_VGG16.h

@@ -13,8 +13,8 @@ class CNNPredictor_VGG16{
 public:
     const std::string json_file = "model/VGG16/VGG16_newest-symbol.json";
     const std::string param_file = "model/VGG16/VGG16_newest-0000.params";
-    const std::vector<std::string> input_keys = {"data"};
     //const std::vector<std::string> input_keys = {"data"};
+    const std::vector<std::string> input_keys = {"data"};
     const std::vector<std::vector<mx_uint>> input_shapes = {{1,3,224,224}};
     const bool use_gpu = false;
 
@@ -28,8 +28,8 @@ public:
         if(handle) MXPredFree(handle);
     }
 
-    void predict(const vector<float> &data,
-                 vector<float> &predictions){
+    void predict(const std::vector<float> &data,
+                 std::vector<float> &predictions){
         MXPredSetInput(handle, "data", data.data(), data.size());
         //MXPredSetInput(handle, "data", data.data(), data.size());