NetworkRT (deallocations to be done)

tests/mnist/test_mnist.cpp

@@ -21,33 +21,52 @@ int main() {
     tkDNN::Activation l5(&net, CUDNN_ACTIVATION_RELU);
     tkDNN::Dense      l6(&net, 10, d3_bin);
     tkDNN::Softmax    l7(&net);
- 
+
+    tkDNN::NetworkRT netRT(&net);
+
     // Load input
     value_type *data;
     value_type *input_h;
     readBinaryFile(input_bin, dim.tot(), &input_h, &data);
 
-    printDeviceVector(dim.tot(), data);
-    dim.print(); //print initial dimension
-    
-    TIMER_START
+    value_type *out_data, *out_data2;
 
-    // Inference
-    data = net.infer(dim, data);
-    
-    TIMER_STOP
-    dim.print();   
+    std::cout<<"CUDNN inference:\n"; {
+        dim.print(); //print initial dimension  
+        TIMER_START
+        out_data = net.infer(dim, data);    
+        TIMER_STOP
+        dim.print();   
+    }
 
     // Print result
-    std::cout<<"\n======= RESULT =======\n";
-    printDeviceVector(dim.tot(), data);
+    //std::cout<<"\n======= CUDNN RESULT =======\n";
+    //printDeviceVector(10, out_data);
  
+    tkDNN::dataDim_t dim2(1, 1, 28, 28, 1);
+
+    std::cout<<"TENSORRT inference:\n"; {
+        dim2.print();
+        TIMER_START
+        out_data2 = netRT.infer(dim2, data);
+        TIMER_STOP
+        dim2.print();
+    }
+
+    // Print result
+    //std::cout<<"\n======= TENRT RESULT =======\n";
+    //printDeviceVector(10, out_data);
+
+    std::cout<<"\n======= CHECK RESULT =======\n";
+    std::cout<<"Diffs: "<<checkResult(dim.tot(), out_data, out_data2)<<"\n";
+
+ /*
     // Print real test
     std::cout<<"\n==== CHECK RESULT ====\n";
     value_type *out;
     value_type *out_h;
     readBinaryFile(output_bin, dim.tot(), &out_h, &out);
     printDeviceVector(dim.tot(), out);
- 
+*/ 
     return 0;
 }

tests/yolo/yolo.cpp

@@ -104,22 +104,30 @@ int main() {
     value_type *input_h;
     readBinaryFile(input_bin, dim.tot(), &input_h, &data);
 
-    dim.print(); //print initial dimension
-    
-    TIMER_START
+    tkDNN::NetworkRT netRT(&net);
 
-    // Inference
-    data = net.infer(dim, data);
-    
-    TIMER_STOP
-    dim.print();   
+    value_type *out_data, *out_data2;
+
+    std::cout<<"CUDNN inference:\n"; {
+        dim.print(); //print initial dimension  
+        TIMER_START
+        out_data = net.infer(dim, data);    
+        TIMER_STOP
+        dim.print();   
+    }
  
-    // Print real test
-    std::cout<<"\n==== CHECK RESULT ====\n";
-    value_type *out;
-    value_type *out_h;
-    readBinaryFile(output_bin, dim.tot(), &out_h, &out);
-    int diff = checkResult(dim.tot(), data, out);
-    printf("Output diffs: %d\n", diff);
+    tkDNN::dataDim_t dim2(1, 3, 608, 608, 1);
+
+    std::cout<<"TENSORRT inference:\n"; {
+        dim2.print();
+        TIMER_START
+        out_data2 = netRT.infer(dim2, data);
+        TIMER_STOP
+        dim2.print();
+    }
+
+    std::cout<<"\n======= CHECK RESULT =======\n";
+    std::cout<<"Diffs: "<<checkResult(dim.tot(), out_data, out_data2)<<"\n";
+
     return 0;
 }