Implementation of the multiply constant layer. More...

Public Member Functions
	MultiplyConstant (const double scalar=1.0)
	Create the MultiplyConstant object.

	MultiplyConstant (const MultiplyConstant &layer)
	Copy Constructor.

	MultiplyConstant (MultiplyConstant &&layer)
	Move Constructor.

MultiplyConstant &	operator= (const MultiplyConstant &layer)
	Copy assignment operator.

MultiplyConstant &	operator= (MultiplyConstant &&layer)
	Move assignment operator.

template<typename InputType , typename OutputType >
void	Forward (const InputType &input, OutputType &output)
	Ordinary feed forward pass of a neural network. More...

template<typename DataType >
void	Backward (const DataType &, const DataType &gy, DataType &g)
	Ordinary feed backward pass of a neural network. 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.

double	Scalar () const
	Get the scalar multiplier.

double &	Scalar ()
	Modify the scalar multiplier.

size_t	WeightSize () const
	Get the size of the weights.

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

Detailed Description

Implementation of the multiply constant layer.

The multiply constant layer multiplies the input by a (non-learnable) constant.

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).

Member Function Documentation

template<typename InputDataType , typename OutputDataType >

template<typename DataType >

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

Ordinary feed backward pass of a neural network.

The backward pass multiplies the error with the specified constant scalar value.

Parameters

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

template<typename InputDataType , typename OutputDataType >

template<typename InputType , typename OutputType >

void mlpack::ann::MultiplyConstant< InputDataType, OutputDataType >::Forward	(	const InputType &	input,
		OutputType &	output
	)

Ordinary feed forward pass of a neural network.

Multiply the input with the specified constant scalar value.

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: