Implementation of the reinforce normal layer. More...

Public Member Functions
	ReinforceNormal (const double stdev=1.0)
	Create the ReinforceNormal object. More...

template<typename eT >
void	Forward (const arma::Mat< eT > &input, arma::Mat< eT > &output)
	Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. More...

template<typename DataType >
void	Backward (const DataType &input, const DataType &, DataType &g)
	Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f. More...

OutputDataType &	OutputParameter () const
	Get the output parameter.

OutputDataType &	OutputParameter ()
	Modify the output parameter.

OutputDataType &	Delta () const
	Get the delta.

OutputDataType &	Delta ()
	Modify the delta.

bool	Deterministic () const
	Get the value of the deterministic parameter.

bool &	Deterministic ()
	Modify the value of the deterministic parameter.

double	Reward () const
	Get the value of the reward parameter.

double &	Reward ()
	Modify the value of the deterministic parameter.

double	StandardDeviation () const
	Get the standard deviation used during forward and backward pass.

template<typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer.

Detailed Description

Implementation of the reinforce normal layer.

The reinforce normal layer implements the REINFORCE algorithm for the normal distribution.

Template Parameters

InputDataType	Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataType	Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).

Constructor & Destructor Documentation

template<typename InputDataType , typename OutputDataType >

mlpack::ann::ReinforceNormal< InputDataType, OutputDataType >::ReinforceNormal ( const double stdev = 1.0 )

Create the ReinforceNormal object.

Parameters

stdev Standard deviation used during the forward and backward pass.

template<typename InputDataType , typename OutputDataType >

template<typename DataType >

void mlpack::ann::ReinforceNormal< InputDataType, OutputDataType >::Backward	(	const DataType &	input,
		const DataType &	,
		DataType &	g
	)

Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f.

Using the results from the feed forward pass.

Parameters

input	The propagated input activation.
*	(gy) The backpropagated error.
g	The calculated gradient.

template<typename InputDataType , typename OutputDataType >

template<typename eT >

void mlpack::ann::ReinforceNormal< InputDataType, OutputDataType >::Forward	(	const arma::Mat< eT > &	input,
		arma::Mat< eT > &	output
	)

Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f.

Parameters

input	Input data used for evaluating the specified function.
output	Resulting output activation.

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