Batchnorm eps fix, works on jetpack 4.3

src/Conv2d.cpp

@@ -117,7 +117,7 @@ dnnType* Conv2d::infer(dataDim_t &dim, dnnType* srcData) {
             dstTensorDesc, dstData, dstTensorDesc, 
             dstData, biasTensorDesc, //same tensor descriptor as bias 
             scales_d, bias_d, mean_d, variance_d, 
-            CUDNN_BN_MIN_EPSILON);
+            TKDNN_BN_MIN_EPSILON);
     }
     //update data dimensions    
     dim = output_dim;

src/LayerWgs.cpp

@@ -29,7 +29,7 @@ LayerWgs::LayerWgs(Network *net, int inputs, int outputs,
         seek += outputs;
         readBinaryFile(weights_path.c_str(), outputs, &variance_h, &variance_d, seek);
 
-        float eps = CUDNN_BN_MIN_EPSILON;
+        float eps = TKDNN_BN_MIN_EPSILON;
 
         power_h = new dnnType[outputs];
         for(int i=0; i<outputs; i++) power_h[i] = 1.0f;

src/Network.cpp

@@ -17,10 +17,6 @@ Network::Network(dataDim_t input_dim) {
              <<", CUDNN v"<<cu_ver<<")\n";
     dataType = CUDNN_DATA_FLOAT;
     tensorFormat = CUDNN_TENSOR_NCHW;
-
-    checkCUDNN( cudnnCreate(&cudnnHandle) );
-    checkERROR( cublasCreate(&cublasHandle) );
-
     num_layers = 0;
 
     fp16 = false;
@@ -38,6 +34,11 @@ Network::Network(dataDim_t input_dim) {
         std::cout<<COL_REDB<<"!! FP16 INERENCE ENABLED !!"<<COL_END<<"\n";
     if(dla)
         std::cout<<COL_GREENB<<"!! DLA INERENCE ENABLED !!"<<COL_END<<"\n";
+
+
+    checkCUDNN( cudnnCreate(&cudnnHandle) );
+    checkERROR( cublasCreate(&cublasHandle) );
+
 }
 
 Network::~Network() {