Fixed some namings so that it works again with the multiple stream update in EMADL2CPP

src/main/resources/templates/caffe2/CNNPredictor.ftl

@@ -23,7 +23,7 @@ CAFFE2_DEFINE_string(predict_net_${tc.fileNameWithoutEnding}, "./model/${tc.comp
 
 using namespace caffe2;
 
-class ${tc.fileNameWithoutEnding}{
+class ${tc.fileNameWithoutEnding}_0{
     private:
         TensorCPU input;
         Workspace workSpace;
@@ -32,11 +32,11 @@ class ${tc.fileNameWithoutEnding}{
     public:
         const std::vector<TIndex> input_shapes = {<#list tc.architecture.inputs as input>{1,${tc.join(input.definition.type.dimensions, ",")}}<#if input?has_next>,</#if></#list>};
 
-        explicit ${tc.fileNameWithoutEnding}(){
+        explicit ${tc.fileNameWithoutEnding}_0(){
             init(input_shapes);
         }
 
-        ~${tc.fileNameWithoutEnding}(){};
+        ~${tc.fileNameWithoutEnding}_0(){};
 
         void init(const std::vector<TIndex> &input_shapes){
             int n = 0;

src/main/resources/templates/caffe2/execute.ftl

@@ -3,7 +3,7 @@
     vector<float> CNN_${tc.getName(output)}(<#list shape as dim>${dim?c}<#if  dim?has_next>*</#if></#list>);
 </#list>
 
-    _cnn_.predict(<#list tc.architecture.inputs as input>CNNTranslator::translate(${input.name}<#if input.arrayAccess.isPresent()>[${input.arrayAccess.get().intValue.get()?c}]</#if>),
+    _predictor_0_.predict(<#list tc.architecture.inputs as input>CNNTranslator::translate(${input.name}<#if input.arrayAccess.isPresent()>[${input.arrayAccess.get().intValue.get()?c}]</#if>),
                 </#list><#list tc.architecture.outputs as output>CNN_${tc.getName(output)}<#if output?has_next>,
                 </#if></#list>);
 

src/test/resources/target_code/CNNPredictor_Alexnet.h

@@ -23,7 +23,7 @@ CAFFE2_DEFINE_string(predict_net, "./model/Alexnet/predict_net.pb", "The given p
 
 using namespace caffe2;
 
-class CNNPredictor_Alexnet{
+class CNNPredictor_Alexnet_0{
     private:
         TensorCPU input;
         Workspace workSpace;
@@ -32,11 +32,11 @@ class CNNPredictor_Alexnet{
     public:
         const std::vector<TIndex> input_shapes = {{1,3,224,224}};
 
-        explicit CNNPredictor_Alexnet(){
+        explicit CNNPredictor_Alexnet_0(){
             init(input_shapes);
         }
 
-        ~CNNPredictor_Alexnet(){};
+        ~CNNPredictor_Alexnet_0(){};
 
         void init(const std::vector<TIndex> &input_shapes){
             int n = 0;

src/test/resources/target_code/CNNPredictor_CifarClassifierNetwork.h

@@ -23,7 +23,7 @@ CAFFE2_DEFINE_string(predict_net, "./model/CifarClassifierNetwork/predict_net.pb
 
 using namespace caffe2;
 
-class CNNPredictor_CifarClassifierNetwork{
+class CNNPredictor_CifarClassifierNetwork_0{
     private:
         TensorCPU input;
         Workspace workSpace;
@@ -32,11 +32,11 @@ class CNNPredictor_CifarClassifierNetwork{
     public:
         const std::vector<TIndex> input_shapes = {{1,3,32,32}};
 
-        explicit CNNPredictor_CifarClassifierNetwork(){
+        explicit CNNPredictor_CifarClassifierNetwork_0(){
             init(input_shapes);
         }
 
-        ~CNNPredictor_CifarClassifierNetwork(){};
+        ~CNNPredictor_CifarClassifierNetwork_0(){};
 
         void init(const std::vector<TIndex> &input_shapes){
             int n = 0;

src/test/resources/target_code/CNNPredictor_LeNet.h

@@ -23,7 +23,7 @@ CAFFE2_DEFINE_string(predict_net_CNNPredictor_LeNet, "./model/LeNet/predict_net.
 
 using namespace caffe2;
 
-class CNNPredictor_LeNet{
+class CNNPredictor_LeNet_0{
     private:
         TensorCPU input;
         Workspace workSpace;
@@ -32,11 +32,11 @@ class CNNPredictor_LeNet{
     public:
         const std::vector<TIndex> input_shapes = {{1,1,28,28}};
 
-        explicit CNNPredictor_LeNet(){
+        explicit CNNPredictor_LeNet_0(){
             init(input_shapes);
         }
 
-        ~CNNPredictor_LeNet(){};
+        ~CNNPredictor_LeNet_0(){};
 
         void init(const std::vector<TIndex> &input_shapes){
             int n = 0;

src/test/resources/target_code/CNNPredictor_VGG16.h

@@ -23,7 +23,7 @@ CAFFE2_DEFINE_string(predict_net_CNNPredictor_VGG16, "./model/VGG16/predict_net.
 
 using namespace caffe2;
 
-class CNNPredictor_VGG16{
+class CNNPredictor_VGG16_0{
     private:
         TensorCPU input;
         Workspace workSpace;
@@ -32,11 +32,11 @@ class CNNPredictor_VGG16{
     public:
         const std::vector<TIndex> input_shapes = {{1,3,224,224}};
 
-        explicit CNNPredictor_VGG16(){
+        explicit CNNPredictor_VGG16_0(){
             init(input_shapes);
         }
 
-        ~CNNPredictor_VGG16(){};
+        ~CNNPredictor_VGG16_0(){};
 
         void init(const std::vector<TIndex> &input_shapes){
             int n = 0;

src/test/resources/target_code/execute_Alexnet

     vector<float> CNN_predictions(10);
 
-    _cnn_.predict(CNNTranslator::translate(data),
+    _predictor_0_.predict(CNNTranslator::translate(data),
                 CNN_predictions);
 
     predictions = CNNTranslator::translateToCol(CNN_predictions, std::vector<size_t> {10});
\ No newline at end of file

src/test/resources/target_code/execute_CifarClassifierNetwork

     vector<float> CNN_softmax(10);
 
-    _cnn_.predict(CNNTranslator::translate(data),
+    _predictor_0_.predict(CNNTranslator::translate(data),
                 CNN_softmax);
 
     softmax = CNNTranslator::translateToCol(CNN_softmax, std::vector<size_t> {10});
\ No newline at end of file

src/test/resources/target_code/execute_LeNet

     vector<float> CNN_predictions(10);
 
-    _cnn_.predict(CNNTranslator::translate(image),
+    _predictor_0_.predict(CNNTranslator::translate(image),
                 CNN_predictions);
 
     predictions = CNNTranslator::translateToCol(CNN_predictions, std::vector<size_t> {10});

src/test/resources/target_code/execute_VGG16

     vector<float> CNN_predictions(1000);
 
-    _cnn_.predict(CNNTranslator::translate(data),
+    _predictor_0_.predict(CNNTranslator::translate(data),
                 CNN_predictions);
 
     predictions = CNNTranslator::translateToCol(CNN_predictions, std::vector<size_t> {1000});
\ No newline at end of file