Implementation of the MeanPooling. More...

Public Member Functions
	MeanPooling ()
	Create the MeanPooling object. More...

	MeanPooling (const size_t kernelWidth, const size_t kernelHeight, const size_t strideWidth=1, const size_t strideHeight=1, const bool floor=true)
	Create the MeanPooling object using the specified number of units. More...

template < typename eT >
void	Backward (const arma::Mat< eT > &, const arma::Mat< eT > &gy, arma::Mat< eT > &g)
	Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, 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...

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

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

bool const &	Floor () const
	Get the value of the rounding operation. More...

bool &	Floor ()
	Modify the value of the rounding operation. 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...

size_t const &	InputHeight () const
	Get the input height. More...

size_t &	InputHeight ()
	Modify the input height. More...

size_t	InputSize () const
	Get the input size. More...

size_t const &	InputWidth () const
	Get the intput width. More...

size_t &	InputWidth ()
	Modify the input width. More...

size_t	KernelHeight () const
	Get the kernel height. More...

size_t &	KernelHeight ()
	Modify the kernel height. More...

size_t	KernelWidth () const
	Get the kernel width. More...

size_t &	KernelWidth ()
	Modify the kernel width. More...

size_t const &	OutputHeight () const
	Get the output height. More...

size_t &	OutputHeight ()
	Modify the output height. More...

OutputDataType const &	OutputParameter () const
	Get the output parameter. More...

OutputDataType &	OutputParameter ()
	Modify the output parameter. More...

size_t	OutputSize () const
	Get the output size. More...

size_t const &	OutputWidth () const
	Get the output width. More...

size_t &	OutputWidth ()
	Modify the output width. More...

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

size_t	StrideHeight () const
	Get the stride height. More...

size_t &	StrideHeight ()
	Modify the stride height. More...

size_t	StrideWidth () const
	Get the stride width. More...

size_t &	StrideWidth ()
	Modify the stride width. More...

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

Detailed Description

template
<
typename
InputDataType
=
arma::mat
,
typename
OutputDataType
=
arma::mat
>

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

Implementation of the MeanPooling.

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 33 of file mean_pooling.hpp.

Constructor & Destructor Documentation

◆ MeanPooling() [1/2]

MeanPooling ( )

Create the MeanPooling object.

◆ MeanPooling() [2/2]

MeanPooling	(	const size_t	kernelWidth,
		const size_t	kernelHeight,
		const size_t	strideWidth = `1`,
		const size_t	strideHeight = `1`,
		const bool	floor = `true`
	)

Create the MeanPooling object using the specified number of units.

Parameters

kernelWidth	Width of the pooling window.
kernelHeight	Height of the pooling window.
strideWidth	Width of the stride operation.
strideHeight	Width of the stride operation.
floor	Set to true to use floor method.

Member Function Documentation

◆ Backward()

void Backward	(	const arma::Mat< eT > &	,
		const arma::Mat< eT > &	gy,
		arma::Mat< eT > &	g
	)

Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, 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 84 of file mean_pooling.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 86 of file mean_pooling.hpp.

◆ Deterministic() [1/2]

bool Deterministic ( ) const

inline

Get the value of the deterministic parameter.

Definition at line 140 of file mean_pooling.hpp.

◆ Deterministic() [2/2]

bool& Deterministic ( )

inline

Modify the value of the deterministic parameter.

Definition at line 142 of file mean_pooling.hpp.

◆ Floor() [1/2]

bool const& Floor ( ) const

inline

Get the value of the rounding operation.

Definition at line 135 of file mean_pooling.hpp.

◆ Floor() [2/2]

bool& Floor ( )

inline

Modify the value of the rounding operation.

Definition at line 137 of file mean_pooling.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.

◆ InputHeight() [1/2]

size_t const& InputHeight ( ) const

inline

Get the input height.

Definition at line 94 of file mean_pooling.hpp.

◆ InputHeight() [2/2]

size_t& InputHeight ( )

inline

Modify the input height.

Definition at line 96 of file mean_pooling.hpp.

◆ InputSize()

size_t InputSize ( ) const

inline

Get the input size.

Definition at line 109 of file mean_pooling.hpp.

◆ InputWidth() [1/2]

size_t const& InputWidth ( ) const

inline

Get the intput width.

Definition at line 89 of file mean_pooling.hpp.

◆ InputWidth() [2/2]

size_t& InputWidth ( )

inline

Modify the input width.

Definition at line 91 of file mean_pooling.hpp.

◆ KernelHeight() [1/2]

size_t KernelHeight ( ) const

inline

Get the kernel height.

Definition at line 120 of file mean_pooling.hpp.

◆ KernelHeight() [2/2]

size_t& KernelHeight ( )

inline

Modify the kernel height.

Definition at line 122 of file mean_pooling.hpp.

◆ KernelWidth() [1/2]

size_t KernelWidth ( ) const

inline

Get the kernel width.

Definition at line 115 of file mean_pooling.hpp.

◆ KernelWidth() [2/2]

size_t& KernelWidth ( )

inline

Modify the kernel width.

Definition at line 117 of file mean_pooling.hpp.

◆ OutputHeight() [1/2]

size_t const& OutputHeight ( ) const

inline

Get the output height.

Definition at line 104 of file mean_pooling.hpp.

◆ OutputHeight() [2/2]

size_t& OutputHeight ( )

inline

Modify the output height.

Definition at line 106 of file mean_pooling.hpp.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 79 of file mean_pooling.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 81 of file mean_pooling.hpp.

◆ OutputSize()

size_t OutputSize ( ) const

inline

Get the output size.

Definition at line 112 of file mean_pooling.hpp.

◆ OutputWidth() [1/2]

size_t const& OutputWidth ( ) const

inline

Get the output width.

Definition at line 99 of file mean_pooling.hpp.

◆ OutputWidth() [2/2]

size_t& OutputWidth ( )

inline

Modify the output width.

Definition at line 101 of file mean_pooling.hpp.

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

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

◆ StrideHeight() [1/2]

size_t StrideHeight ( ) const

inline

Get the stride height.

Definition at line 130 of file mean_pooling.hpp.

◆ StrideHeight() [2/2]

size_t& StrideHeight ( )

inline

Modify the stride height.

Definition at line 132 of file mean_pooling.hpp.

◆ StrideWidth() [1/2]

size_t StrideWidth ( ) const

inline

Get the stride width.

Definition at line 125 of file mean_pooling.hpp.

◆ StrideWidth() [2/2]

size_t& StrideWidth ( )

inline

Modify the stride width.

Definition at line 127 of file mean_pooling.hpp.

◆ WeightSize()

size_t WeightSize ( ) const

inline

Get the size of the weights.

Definition at line 145 of file mean_pooling.hpp.

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

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

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

Public Member Functions

Detailed Description

template<typenameInputDataType=arma::mat,typenameOutputDataType=arma::mat> class mlpack::ann::MeanPooling< InputDataType, OutputDataType >

Constructor & Destructor Documentation

◆ MeanPooling() [1/2]

◆ MeanPooling() [2/2]

Member Function Documentation

◆ Backward()

◆ Delta() [1/2]

◆ Delta() [2/2]

◆ Deterministic() [1/2]

◆ Deterministic() [2/2]

◆ Floor() [1/2]

◆ Floor() [2/2]

◆ Forward()

◆ InputHeight() [1/2]

◆ InputHeight() [2/2]

◆ InputSize()

◆ InputWidth() [1/2]

◆ InputWidth() [2/2]

◆ KernelHeight() [1/2]

◆ KernelHeight() [2/2]

◆ KernelWidth() [1/2]

◆ KernelWidth() [2/2]

◆ OutputHeight() [1/2]

◆ OutputHeight() [2/2]

◆ OutputParameter() [1/2]

◆ OutputParameter() [2/2]

◆ OutputSize()

◆ OutputWidth() [1/2]

◆ OutputWidth() [2/2]

◆ serialize()

◆ StrideHeight() [1/2]

◆ StrideHeight() [2/2]

◆ StrideWidth() [1/2]

◆ StrideWidth() [2/2]

◆ WeightSize()

template
<
typename
InputDataType
=
arma::mat
,
typename
OutputDataType
=
arma::mat
>

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