Davide Sapienza
03d2b88fa6
This commit adds two variables for the calibration dataset. The first is reffered to .txt file that contains the list of the absolute paths of the images for the INT8 calitration. The second is referred to .txt file that contains the list of the absolute paths of the labels of the same images above. Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
72 lines
1.4 KiB
C++
72 lines
1.4 KiB
C++
#ifndef NETWORK_H
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#define NETWORK_H
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#include <string>
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#include "utils.h"
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namespace tk { namespace dnn {
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/**
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Data rapresentation beetween layers
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n = batch size
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c = channels
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h = heigth (lines)
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w = width (rows)
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l = lenght (3rd dimension)
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*/
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struct dataDim_t {
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int n, c, h, w, l;
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dataDim_t() : n(1), c(1), h(1), w(1), l(1) {};
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dataDim_t(int _n, int _c, int _h, int _w, int _l = 1) :
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n(_n), c(_c), h(_h), w(_w), l(_l) {};
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void print() {
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std::cout<<"Data dim: "<<n<<" "<<c<<" "<<h<<" "<<w<<" "<<l<<"\n";
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}
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int tot() {
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return n*c*h*w*l;
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}
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};
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class Layer;
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const int MAX_LAYERS = 512;
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class Network {
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public:
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Network(dataDim_t input_dim);
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virtual ~Network();
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/**
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Do inferece for every added layer
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*/
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dnnType* infer(dataDim_t &dim, dnnType* data);
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bool addLayer(Layer *l);
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void print();
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const char *getNetworkRTName(char *network_name);
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cudnnDataType_t dataType;
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cudnnTensorFormat_t tensorFormat;
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cudnnHandle_t cudnnHandle;
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cublasHandle_t cublasHandle;
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Layer* layers[MAX_LAYERS]; //contains layers of the net
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int num_layers; //current number of layers
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dataDim_t input_dim;
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dataDim_t getOutputDim();
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bool fp16, dla, int8;
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bool dontLoadWeights;
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std::string fileImgList;
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std::string fileLabelList;
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};
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}}
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#endif //NETWORK_H
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