RTinference test

tests/test_rtinference/rtinference.cpp

@@ -0,0 +1,26 @@
+#include<iostream>
+#include "tkdnn.h"
+
+int main(int argc, char *argv[]) {
+
+    // Network layout
+    tkDNN::dataDim_t dim(1, 3, 608, 608, 1);
+    tkDNN::Network net(dim);
+
+    if(argc < 2 || !fileExist(argv[1]))
+        FatalError("unable to read serialRT file");
+
+    //convert network to tensorRT
+    tkDNN::NetworkRT netRT(&net, argv[1]);
+
+    dnnType *data;
+    checkCuda(cudaMalloc(&data, dim.tot()*sizeof(dnnType)));
+
+    printCenteredTitle(" TENSORRT inference ", '=', 30); {
+        TIMER_START
+        data = netRT.infer(dim, data);
+        TIMER_STOP
+    }
+    
+    return 0;
+}

tests/yolo/yolo.cpp

@@ -28,7 +28,7 @@ const char *c30_bin    = "../tests/yolo/layers/c30.bin";
 const char *g31_bin    = "../tests/yolo/layers/g31.bin";
 const char *output_bin = "../tests/yolo/layers/output.bin";
 
-int main(int argc, char *argv[]) {
+int main() {
 
     // Network layout
     tkDNN::dataDim_t dim(1, 3, 608, 608, 1);
@@ -108,7 +108,7 @@ int main(int argc, char *argv[]) {
     net.print();
 
     //convert network to tensorRT
-    tkDNN::NetworkRT netRT(&net, argv[1]);
+    tkDNN::NetworkRT netRT(&net, "yolo.rt");
 
     dnnType *out_data, *out_data2; // cudnn output, tensorRT output