ReLU6< InputDataType, OutputDataType > Class Template Reference

Public Member Functions
	ReLU6 ()
	Create the ReLU6 object. More...
template < typename DataType >
void	Backward (const DataType &input, const DataType &gy, DataType &g)
	Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f. More...
OutputDataType const &	Delta () const
	Get the delta. More...
OutputDataType &	Delta ()
	Modify the delta. More...
template < typename InputType , typename OutputType >
void	Forward (const InputType &input, OutputType &output)
	Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. More...
OutputDataType const &	OutputParameter () const
	Get the output parameter. More...
OutputDataType &	OutputParameter ()
	Modify the output parameter. More...
template < typename Archive >
void	serialize (Archive &ar, const uint32_t)
	Serialize the layer. More...
size_t	WeightSize () const
	Get size of weights. More...

Detailed Description

template

<

typename

InputDataType

=

arma::mat

,

typename

OutputDataType

=

arma::mat

>

class mlpack::ann::ReLU6< InputDataType, OutputDataType >

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 90 of file layer_types.hpp.

Constructor & Destructor Documentation

ReLU6()

ReLU6

(

)

Create the ReLU6 object.

Member Function Documentation

Backward()

void Backward	(	const DataType &	input,
		const DataType &	gy,
		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 const& Delta ( ) const

inline

Get the delta.

Definition at line 76 of file relu6.hpp.

Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 78 of file relu6.hpp.

Forward()

void Forward	(	const InputType &	input,
		OutputType &	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 const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 71 of file relu6.hpp.

OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 73 of file relu6.hpp.

serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by ReLU6< InputDataType, OutputDataType >::WeightSize().

WeightSize()

size_t WeightSize ( ) const

inline

Get size of weights.

Definition at line 81 of file relu6.hpp.

References ReLU6< InputDataType, OutputDataType >::serialize().

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

• /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/layer_types.hpp
• /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/relu6.hpp