machine_learning::neural_network::layers::DenseLayer Class Reference

Collaboration diagram for machine_learning::neural_network::layers::DenseLayer:

Public Member Functions
	DenseLayer (const int &neurons, const std::string &activation, const std::pair< size_t, size_t > &kernal_shape, const bool &random_kernal)
	DenseLayer (const int &neurons, const std::string &activation, const std::vector< std::valarray< double >> &kernal)
	DenseLayer (const DenseLayer &layer)=default
	~DenseLayer ()=default
DenseLayer &	operator= (const DenseLayer &layer)=default
	DenseLayer (DenseLayer &&)=default
DenseLayer &	operator= (DenseLayer &&)=default

Public Attributes
double(*	activation_function )(const double &)
double(*	dactivation_function )(const double &)
int	neurons
std::string	activation
std::vector< std::valarray< double > >	kernal

Detailed Description

neural_network::layers::DenseLayer class is used to store all necessary information about the layers (i.e. neurons, activation and kernal). This class is used by NeuralNetwork class to store layers.

Constructor & Destructor Documentation

DenseLayer() [1/4]

machine_learning::neural_network::layers::DenseLayer::DenseLayer ( const int &  neurons, const std::string &  activation, const std::pair< size_t, size_t > &  kernal_shape, const bool &  random_kernal  )

inline

Constructor for neural_network::layers::DenseLayer class

Parameters

neurons	number of neurons
activation	activation function for layer
kernal_shape	shape of kernal
random_kernal	flag for whether to intialize kernal randomly

                                                     {
                        // Choosing activation (and it's derivative)
                        if (activation == "sigmoid") {
                            activation_function = neural_network::activations::sigmoid;
                            dactivation_function = neural_network::activations::sigmoid;
                        }
                        else if (activation == "relu") {
                            activation_function = neural_network::activations::relu;
                            dactivation_function = neural_network::activations::drelu;
                        }
                        else if (activation == "tanh") {
                            activation_function = neural_network::activations::tanh;
                            dactivation_function = neural_network::activations::dtanh;
                        }
                        else if (activation == "none") {
                            // Set identity function in casse of none is supplied
                            activation_function = neural_network::util_functions::identity_function;
                            dactivation_function = neural_network::util_functions::identity_function;
                        }
                        else {
                            // If supplied activation is invalid
                            std::cerr << "ERROR: Invalid argument for layer -> constructor -> activation, ";
                            std::cerr << "Expected from {none, sigmoid, relu, tanh} got ";
                            std::cerr << activation << std::endl;
                            std::exit(EXIT_FAILURE);
                        }
                        this -> activation = activation; // Setting activation name
                        this -> neurons = neurons; // Setting number of neurons
                        // Initialize kernal according to flag
                        if(random_kernal) {
                            uniform_random_initialization(kernal, kernal_shape, -1.0, 1.0);
                        }
                        else {
                            unit_matrix_initialization(kernal, kernal_shape);
                        }
                    }

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DenseLayer() [2/4]

machine_learning::neural_network::layers::DenseLayer::DenseLayer ( const int &  neurons, const std::string &  activation, const std::vector< std::valarray< double >> &  kernal  )

inline

Constructor for neural_network::layers::DenseLayer class

Parameters

neurons	number of neurons
activation	activation function for layer
kernal	values of kernal (useful in loading model)

                                                                          {
                        // Choosing activation (and it's derivative)
                        if (activation == "sigmoid") {
                            activation_function = neural_network::activations::sigmoid;
                            dactivation_function = neural_network::activations::sigmoid;
                        }
                        else if (activation == "relu") {
                            activation_function = neural_network::activations::relu;
                            dactivation_function = neural_network::activations::drelu;
                        }
                        else if (activation == "tanh") {
                            activation_function = neural_network::activations::tanh;
                            dactivation_function = neural_network::activations::dtanh;
                        }
                        else if (activation == "none") {
                            // Set identity function in casse of none is supplied
                            activation_function = neural_network::util_functions::identity_function;
                            dactivation_function = neural_network::util_functions::identity_function;
                        }
                        else {
                            // If supplied activation is invalid
                            std::cerr << "ERROR: Invalid argument for layer -> constructor -> activation, ";
                            std::cerr << "Expected from {none, sigmoid, relu, tanh} got ";
                            std::cerr << activation << std::endl;
                            std::exit(EXIT_FAILURE);
                        }
                        this -> activation = activation; // Setting activation name
                        this -> neurons = neurons; // Setting number of neurons
                        this -> kernal = kernal;  // Setting supplied kernal values                 
                    }

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DenseLayer() [3/4]

machine_learning::neural_network::layers::DenseLayer::DenseLayer ( const DenseLayer &  layer )

default

Copy Constructor for class DenseLayer.

Parameters

model

instance of class to be copied.

~DenseLayer()

machine_learning::neural_network::layers::DenseLayer::~DenseLayer ( )

default

Destructor for class DenseLayer.

DenseLayer() [4/4]

machine_learning::neural_network::layers::DenseLayer::DenseLayer ( DenseLayer &&  )

default

Move constructor for class DenseLayer

Member Function Documentation

operator=() [1/2]

DenseLayer& machine_learning::neural_network::layers::DenseLayer::operator= ( const DenseLayer &  layer )

default

Copy assignment operator for class DenseLayer

operator=() [2/2]

DenseLayer& machine_learning::neural_network::layers::DenseLayer::operator= ( DenseLayer &&  )

default

Move assignment operator for class DenseLayer

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The documentation for this class was generated from the following file:

• machine_learning/neural_network.cpp