#include <RecurrentNeuralNetwork.h>

Inheritance diagram for panann::RecurrentNeuralNetwork:

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Collaboration diagram for panann::RecurrentNeuralNetwork:

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Classes
struct	CellLayer

struct	LongShortTermMemoryCell

Public Member Functions
	RecurrentNeuralNetwork (const RecurrentNeuralNetwork &)=delete

RecurrentNeuralNetwork &	operator= (const RecurrentNeuralNetwork &)=delete

void	SetCellMemorySize (size_t memory_size)

size_t	GetCellMemorySize () const

void	RunForward (const std::vector< double > &input) override

std::vector< double > &	GetCellStates ()

void	AddHiddenLayer (size_t neuron_count)=delete

void	AddHiddenLayer (size_t cell_count, const std::vector< size_t > &cell_memory_sizes={})

void	Construct () override

Public Member Functions inherited from panann::Perceptron
	Perceptron (const Perceptron &)=delete

Perceptron &	operator= (const Perceptron &)=delete

void	SetErrorCostFunction (ErrorCostFunction mode)

ErrorCostFunction	GetErrorCostFunction () const

void	SetHiddenNeuronActivationFunctionType (ActivationFunctionType type)

ActivationFunctionType	GetHiddenNeuronActivationFunctionType () const

void	SetOutputNeuronActivationFunctionType (ActivationFunctionType type)

ActivationFunctionType	GetOutputNeuronActivationFunctionType () const

void	InitializeWeightsRandom (double min=-1.0, double max=1.0)

void	InitializeWeights (const TrainingData &training_data)

void	RunBackward (const std::vector< double > &output)

double	GetError (const std::vector< double > &output)

double	GetError (const TrainingData &training_data)

std::vector< double > &	GetWeights ()

void	SetWeights (const std::vector< double > &weights)

void	GetOutput (std::vector< double > *output) const

bool	IsConstructed () const

void	EnableErrorShaping ()

void	DisableErrorShaping ()

Public Member Functions inherited from panann::MultiLayerNeuralTopology
	MultiLayerNeuralTopology (const MultiLayerNeuralTopology &)=delete

MultiLayerNeuralTopology &	operator= (const MultiLayerNeuralTopology &)=delete

void	AddHiddenLayer (size_t neuron_count)

void	EnableShortcutConnections ()

void	DisableShortcutConnections ()

void	ConstructTopology ()

bool	IsTopologyConstructed () const

size_t	GetHiddenLayerCount () const

const Layer &	GetHiddenLayer (size_t layer_index) const

size_t	GetInputConnectionCount () const

size_t	GetOutputConnectionCount () const

const InputConnection &	GetInputConnection (size_t index) const

const OutputConnection &	GetOutputConnection (size_t index) const

Public Member Functions inherited from panann::NeuronContainer
	NeuronContainer (const NeuronContainer &)=delete

NeuronContainer &	operator= (const NeuronContainer &)=delete

void	SetInputNeuronCount (size_t input_neuron_count)

size_t	GetInputNeuronCount () const

void	SetOutputNeuronCount (size_t output_neuron_count)

size_t	GetOutputNeuronCount () const

size_t	GetNeuronCount () const

const Neuron &	GetNeuron (size_t neuron_index) const

Protected Member Functions
void	ConnectFully () override

void	FixNeuronConnectionIndices () override

void	InitializeHiddenNeurons () override

void	AllocateCellStates ()

bool	AreCellStatesAllocated () const

void	UpdateCellState (const LongShortTermMemoryCell &cell)

size_t	AddCellMemoryStates (size_t count)

size_t	GetCellCount () const

LongShortTermMemoryCell &	GetCell (size_t index)

size_t	GetCellLayerCount () const

CellLayer &	GetCellLayer (size_t index)

void	InitializeCellNeurons (const LongShortTermMemoryCell &cell, size_t input_connection_count, size_t output_connection_count)

void	InitializeCellNeuronsOneGate (size_t neuron_start_index, size_t neurons_per_gate, ActivationFunctionType activation_function, size_t input_connection_count, size_t output_connection_count)

Protected Member Functions inherited from panann::Perceptron
void	AllocateWeights ()

bool	AreWeightsAllocated () const

void	InitializeNeurons ()

void	ComputeNeuronValue (size_t neuron_index)

void	ComputeNeuronValueRange (size_t neuron_start_index, size_t neuron_count)

void	ComputeNeuronError (size_t neuron_index)

void	ResetOutputLayerError ()

void	CalculateOutputLayerError (const std::vector< double > &output)

double	GetError () const

RandomWrapper &	GetRandom ()

size_t	GetWeightCount () const

double &	GetWeight (size_t index)

Protected Member Functions inherited from panann::MultiLayerNeuralTopology
Layer &	GetHiddenLayer (size_t layer_index)

InputConnection &	GetInputConnection (size_t index)

OutputConnection &	GetOutputConnection (size_t index)

size_t	AddInputConnections (size_t count)

size_t	AddOutputConnections (size_t count)

void	AllocateConnections ()

bool	AreConnectionsAllocated () const

void	ConnectLayerToNeuron (size_t from_neuron_index, size_t from_neuron_count, size_t to_neuron_index)

void	ConnectLayers (size_t from_neuron_index, size_t from_neuron_count, size_t to_neuron_index, size_t to_neuron_count)

void	ConnectBiasNeuron (size_t bias_neuron_index, size_t to_neuron_index, size_t to_neuron_count)

void	ConnectNeurons (size_t from_neuron_index, size_t to_neuron_index)

Protected Member Functions inherited from panann::NeuronContainer
size_t	GetHiddenNeuronStartIndex () const

size_t	GetInputNeuronStartIndex () const

size_t	GetOutputNeuronStartIndex () const

size_t	GetBiasNeuronStartIndex () const

size_t	GetHiddenNeuronCount () const

size_t	GetBiasNeuronCount () const

size_t	AddHiddenNeurons (size_t count)

void	AddBiasNeurons (size_t count)

void	AllocateNeurons ()

bool	AreNeuronsAllocated () const

void	SetNeuronActivationFunction (size_t neuron_index, ActivationFunctionType type)

Neuron &	GetNeuron (size_t neuron_index)

Neuron &	GetInputNeuron (size_t input_neuron_index)

Neuron &	GetOutputNeuron (size_t output_neuron_index)

Neuron &	GetBiasNeuron (size_t bias_neuron_index)

Neuron &	GetHiddenNeuron (size_t hidden_neuron_index)

const Neuron &	GetOutputNeuron (size_t output_neuron_index) const

Additional Inherited Members
Public Types inherited from panann::Perceptron
enum	ErrorCostFunction : uint8_t { MeanSquareError = 1, MeanAbsoluteError }

Detailed Description

A recurrent artificial neural network made out of long short term memory cells.

This network doesn't contain ordinary hidden neurons organized into layers. Instead, each layer contains a set of recurrent cells which are each made of a number of hidden units grouped into gates.

Note: RecurrentNeuralNetwork does not support any training algorithms, currently.

Member Function Documentation

◆ AddHiddenLayer()

void panann::RecurrentNeuralNetwork::AddHiddenLayer	(	size_t	cell_count,
		const std::vector< size_t > &	cell_memory_sizes = `{}`
	)

Add a hidden layer of LSTM cells.
Each cell may have a different cell memory size passed via |cell_memory_sizes|. If the vector doesn't contain an element for a cell or if that element is 0, the cell memory size for that cell will be the default returned via GetCellMemorySize().

See also: GetCellMemorySize()

◆ Construct()

void panann::RecurrentNeuralNetwork::Construct ( )

overridevirtual

Build the neural network.
After construction, the network topology may not be modified.

Reimplemented from panann::Perceptron.

◆ FixNeuronConnectionIndices()

void panann::RecurrentNeuralNetwork::FixNeuronConnectionIndices ( )

overrideprotectedvirtual

Set the input and output connection indices assigned to each neuron into the neurons themselves.

Reimplemented from panann::MultiLayerNeuralTopology.

◆ GetCellStates()

std::vector< double > & panann::RecurrentNeuralNetwork::GetCellStates ( )

Get a writable vector of memory state for all cells in the network.

◆ InitializeCellNeurons()

void panann::RecurrentNeuralNetwork::InitializeCellNeurons	(	const LongShortTermMemoryCell &	cell,
		size_t	input_connection_count,
		size_t	output_connection_count
	)

protected

◆ InitializeCellNeuronsOneGate()

void panann::RecurrentNeuralNetwork::InitializeCellNeuronsOneGate	(	size_t	neuron_start_index,
		size_t	neurons_per_gate,
		ActivationFunctionType	activation_function,
		size_t	input_connection_count,
		size_t	output_connection_count
	)

protected

Initialize the neurons in one gate of a cell.

◆ InitializeHiddenNeurons()

void panann::RecurrentNeuralNetwork::InitializeHiddenNeurons ( )

overrideprotectedvirtual

Set the default activation function etc for all hidden neurons in the network.

Reimplemented from panann::Perceptron.

◆ RunForward()

void panann::RecurrentNeuralNetwork::RunForward ( const std::vector< double > & input )

overridevirtual

Run the network forward on a set of inputs.
The values computed by running the network will be stored in the output neurons.
Works by assigning the values in the input parameter into each input neuron and pulling those values through the hidden layers, calculating the output of each neuron as the result of executing the activation function on the sum of the incoming values multiplied by their connection weights.

Parameters

input Must have the same number of elements as this network has input neurons.

Reimplemented from panann::Perceptron.

◆ SetCellMemorySize()

void panann::RecurrentNeuralNetwork::SetCellMemorySize ( size_t memory_size )

Set the number of memory states which each cell will contain by default.
This value has a quadratic effect on the size of the network topology. Increasing the number of cell memory states increases the number of neurons in each cell gate - effectively, increasing this value by one increases the number of hidden neurons in the network topology by 5 per LSTM cell. Default: 200

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

src/RecurrentNeuralNetwork.h
src/RecurrentNeuralNetwork.cc

Classes

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ AddHiddenLayer()

◆ Construct()

◆ FixNeuronConnectionIndices()

◆ GetCellStates()

◆ InitializeCellNeurons()

◆ InitializeCellNeuronsOneGate()

◆ InitializeHiddenNeurons()

◆ RunForward()

◆ SetCellMemorySize()