ReinforceNormal< InputDataType, OutputDataType > Class Template Reference

Implementation of the reinforce normal layer. More...

Public Member Functions
	ReinforceNormal (const double stdev=1.0)
	Create the ReinforceNormal object. 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 &	Delta () const
	Get the delta. More...
OutputDataType &	Delta ()
	Modify the delta. More...
bool	Deterministic () const
	Get the value of the deterministic parameter. More...
bool &	Deterministic ()
	Modify the value of the deterministic parameter. 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...
OutputDataType &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
double	Reward () const
	Get the value of the reward parameter. More...
double &	Reward ()
	Modify the value of the deterministic parameter. More...
template < typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer. More...
double	StandardDeviation () const
	Get the standard deviation used during forward and backward pass. More...

Detailed Description

template

<

typename

InputDataType

=

arma::mat

,

typename

OutputDataType

=

arma::mat

>

class mlpack::ann::ReinforceNormal< InputDataType, OutputDataType >

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).

Definition at line 34 of file reinforce_normal.hpp.

Constructor & Destructor Documentation

ReinforceNormal()

ReinforceNormal

(

const double

stdev = 1.0

)

Create the ReinforceNormal object.

Parameters

stdev

Standard deviation used during the forward and backward pass.

Member Function Documentation

Backward()

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.

Using the results from the feed forward pass.

Parameters

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

Delta() [1/2]

OutputDataType& Delta ( ) const

inline

Get the delta.

Definition at line 72 of file reinforce_normal.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 74 of file reinforce_normal.hpp.

Deterministic() [1/2]

bool Deterministic ( ) const

inline

Get the value of the deterministic parameter.

Definition at line 77 of file reinforce_normal.hpp.

Deterministic() [2/2]

bool& Deterministic ( )

inline

Modify the value of the deterministic parameter.

Definition at line 79 of file reinforce_normal.hpp.

Forward()

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.

Parameters

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

OutputParameter() [1/2]

OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 67 of file reinforce_normal.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 69 of file reinforce_normal.hpp.

Reward() [1/2]

double Reward ( ) const

inline

Get the value of the reward parameter.

Definition at line 82 of file reinforce_normal.hpp.

Reward() [2/2]

double& Reward ( )

inline

Modify the value of the deterministic parameter.

Definition at line 84 of file reinforce_normal.hpp.

serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by ReinforceNormal< InputDataType, OutputDataType >::StandardDeviation().

StandardDeviation()

double StandardDeviation ( ) const

inline

Get the standard deviation used during forward and backward pass.

Definition at line 87 of file reinforce_normal.hpp.

References ReinforceNormal< InputDataType, OutputDataType >::serialize().

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

• /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/reinforce_normal.hpp