nnlib/network_8h_source.html

 #ifndef NNLIB_NETWORK_H

 #define NNLIB_NETWORK_H


 #include "layer.h"

 #include "loss.h"

 #include <vector>


 #define NO_SEED (-1)


 class Network {

     DataLocation location;


     std::vector<Layer> layers;


     long long seed;


     size_t previousSize;


 public:

     explicit Network(size_t inputSize, bool useGPU = true, long long seed = NO_SEED);


     void add(size_t numNeurons, const std::string& activation = "linear");


     sTensor forward(const sTensor& batch);


     //NOLINTNEXTLINE(readability-identifier-naming)

     void train(sTensor& X, sTensor& y, int epochs, size_t batchSize, float learningRate, Loss* loss,

                std::vector<Metric*>& metrics);


 private:

     void processEpoch(std::vector<sTensor>& batches, std::vector<sTensor>& targets, std::vector<sTensor>& targetsOnHost,

                       float learningRate, Loss* loss, std::vector<Metric*>& metrics);

 };


 #endif //NNLIB_NETWORK_H

DataLocation
DataLocation
Enumerate to specify where data is located.
Definition: cache.h:24

Loss
Abstract class representing a loss function.
Definition: loss.h:21

Network
Represents a neural network.
Definition: network.h:23

Network::location
DataLocation location
The location of the network.
Definition: network.h:29

Network::forward
sTensor forward(const sTensor &batch)
Forward-propagate a batch through the network.
Definition: network.cpp:186

Network::train
void train(sTensor &X, sTensor &y, int epochs, size_t batchSize, float learningRate, Loss *loss, std::vector< Metric * > &metrics)
Train the network.
Definition: network.cpp:198

Network::layers
std::vector< Layer > layers
List of network layers.
Definition: network.h:34

Network::seed
long long seed
Seed used for random initialization.
Definition: network.h:39

Network::processEpoch
void processEpoch(std::vector< sTensor > &batches, std::vector< sTensor > &targets, std::vector< sTensor > &targetsOnHost, float learningRate, Loss *loss, std::vector< Metric * > &metrics)
Trains the model on a single epoch.
Definition: network.cpp:229

Network::add
void add(size_t numNeurons, const std::string &activation="linear")
Add a new layer to the network.
Definition: network.cpp:178

Network::previousSize
size_t previousSize
Keeps track of the size of the previous layer.
Definition: network.h:48

Network::Network
Network(size_t inputSize, bool useGPU=true, long long seed=NO_SEED)
Construct a new network.
Definition: network.cpp:166

layer.h
Header file declaring the Layer class.

loss.h
Header file declaring different loss functions.

NO_SEED
#define NO_SEED
Integer to mean that no seed was specified for the network.
Definition: network.h:18