tkDNN library version 0.1

CMakeLists.txt

@@ -14,5 +14,4 @@ add_library(tkDNN SHARED src/Layer.cpp src/LayerWgs.cpp
 target_link_libraries(tkDNN kernels ${CUDA_LIBRARIES} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_TOOLKIT_ROOT_DIR}/lib/libcudnn.so)
 
 add_executable(tkDNNtest tests/test.cpp)
-message(${CUDA_LIBRARIES})
 target_link_libraries(tkDNNtest tkDNN)

src/Network.cpp

@@ -1,12 +1,16 @@
 #include <iostream>
 
+#include "tkdnn.h"
 #include "Network.h"
 
 namespace tkDNN {
 
 Network::Network() {
 
-    std::cout<<"New NETWORK with CUDNN v"<<float(cudnnGetVersion())/1000<<"\n";
+    float tk_ver = float(tkDNN::getVersion())/1000;
+    float cu_ver = float(cudnnGetVersion())/1000;
+
+    std::cout<<"New NETWORK (tkDNN v"<<tk_ver<<", CUDNN v"<<cu_ver<<")\n";
     dataType = CUDNN_DATA_FLOAT;
     tensorFormat = CUDNN_TENSOR_NCHW;
 

tests/test.cpp

@@ -1,5 +1,5 @@
 #include<iostream>
-#include "Layer.h"
+#include "tkdnn.h"
 
 const char *input_bin   = "../tests/input.bin";
 const char *c0_bin      = "../tests/conv0.bin";
@@ -60,7 +60,7 @@ int main() {
     data = d4.infer(dim, data); dim.print();
     data = a4.infer(dim, data); dim.print();
     data = d5.infer(dim, data); dim.print();
-    
+
     TIMER_STOP
 
     // Print result