include dir fix, cmake dir

include/tkDNN/Network.h

@@ -0,0 +1,66 @@
+#ifndef NETWORK_H
+#define NETWORK_H
+
+#include "utils.h"
+
+namespace tk { namespace dnn {
+
+/**
+    Data rapresentation beetween layers
+    n = batch size
+    c = channels
+    h = heigth (lines)
+    w = width  (rows)
+    l = lenght (3rd dimension)
+*/
+struct dataDim_t {
+
+    int n, c, h, w, l;
+
+    dataDim_t() : n(1), c(1), h(1), w(1), l(1) {};
+
+    dataDim_t(int _n, int _c, int _h, int _w, int _l = 1) :
+        n(_n), c(_c), h(_h), w(_w), l(_l) {};
+
+    void print() {
+        std::cout<<"Data dim: "<<n<<" "<<c<<" "<<h<<" "<<w<<" "<<l<<"\n";
+    }
+
+    int tot() {
+        return n*c*h*w*l;
+    }
+};
+
+class Layer;
+const int MAX_LAYERS = 256;
+
+class Network {
+
+public:
+    Network(dataDim_t input_dim);
+    virtual ~Network();
+
+    /**
+        Do inferece for every added layer
+    */
+    dnnType* infer(dataDim_t &dim, dnnType* data);
+
+    bool addLayer(Layer *l);
+    void print();
+
+    cudnnDataType_t dataType;
+    cudnnTensorFormat_t tensorFormat;
+    cudnnHandle_t cudnnHandle;
+    cublasHandle_t cublasHandle;
+
+    Layer* layers[MAX_LAYERS];  //contains layers of the net
+    int num_layers; //current number of layers
+
+    dataDim_t input_dim;
+    dataDim_t getOutputDim();
+
+    bool fp16, dla;
+};
+
+}}
+#endif //NETWORK_H