Implementation of the Convolution class. More...

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

	Convolution (const size_t inSize, const size_t outSize, const size_t kernelWidth, const size_t kernelHeight, const size_t strideWidth=1, const size_t strideHeight=1, const size_t padW=0, const size_t padH=0, const size_t inputWidth=0, const size_t inputHeight=0, const std::string &paddingType="None")
	Create the Convolution object using the specified number of input maps, output maps, filter size, stride and padding parameter. More...

	Convolution (const size_t inSize, const size_t outSize, const size_t kernelWidth, const size_t kernelHeight, const size_t strideWidth, const size_t strideHeight, const std::tuple< size_t, size_t > &padW, const std::tuple< size_t, size_t > &padH, const size_t inputWidth=0, const size_t inputHeight=0, const std::string &paddingType="None")
	Create the Convolution object using the specified number of input maps, output maps, filter size, stride and padding parameter. More...

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

arma::mat &	Bias ()
	Modify the bias weights of the layer. More...

const OutputDataType &	Delta () const
	Get the delta. More...

OutputDataType &	Delta ()
	Modify the delta. 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 eT >
void	Gradient (const arma::Mat< eT > &&, arma::Mat< eT > &&error, arma::Mat< eT > &&gradient)

const OutputDataType &	Gradient () const
	Get the gradient. More...

OutputDataType &	Gradient ()
	Modify the gradient. More...

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

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

const InputDataType &	InputParameter () const
	Get the input parameter. More...

InputDataType &	InputParameter ()
	Modify the input parameter. More...

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

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

size_t &	InputWidth ()
	Modify input the 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...

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

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

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

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

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

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

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

size_t	PadHBottom () const
	Get the bottom padding height. More...

size_t &	PadHBottom ()
	Modify the bottom padding height. More...

size_t	PadHTop () const
	Get the top padding height. More...

size_t &	PadHTop ()
	Modify the top padding height. More...

size_t	PadWLeft () const
	Get the left padding width. More...

size_t &	PadWLeft ()
	Modify the left padding width. More...

size_t	PadWRight () const
	Get the right padding width. More...

size_t &	PadWRight ()
	Modify the right padding width. More...

const OutputDataType &	Parameters () const
	Get the parameters. More...

OutputDataType &	Parameters ()
	Modify the parameters. More...

void	Reset ()

template < typename Archive >
void	serialize (Archive &ar, const unsigned int)
	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...

Detailed Description

template<typename ForwardConvolutionRule = NaiveConvolution<ValidConvolution>, typename BackwardConvolutionRule = NaiveConvolution<FullConvolution>, typename GradientConvolutionRule = NaiveConvolution<ValidConvolution>, typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >

Implementation of the Convolution class.

The Convolution class represents a single layer of a neural network.

Template Parameters

ForwardConvolutionRule	Convolution to perform forward process.
BackwardConvolutionRule	Convolution to perform backward process.
GradientConvolutionRule	Convolution to calculate gradient.
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 47 of file convolution.hpp.

Constructor & Destructor Documentation

◆ Convolution() [1/3]

Convolution ( )

Create the Convolution object.

◆ Convolution() [2/3]

Convolution	(	const size_t	inSize,
		const size_t	outSize,
		const size_t	kernelWidth,
		const size_t	kernelHeight,
		const size_t	strideWidth = `1`,
		const size_t	strideHeight = `1`,
		const size_t	padW = `0`,
		const size_t	padH = `0`,
		const size_t	inputWidth = `0`,
		const size_t	inputHeight = `0`,
		const std::string &	paddingType = `"None"`
	)

Create the Convolution object using the specified number of input maps, output maps, filter size, stride and padding parameter.

Parameters

inSize	The number of input maps.
outSize	The number of output maps.
kernelWidth	Width of the filter/kernel.
kernelHeight	Height of the filter/kernel.
strideWidth	Stride of filter application in the x direction.
strideHeight	Stride of filter application in the y direction.
padW	Padding width of the input.
padH	Padding height of the input.
inputWidth	The width of the input data.
inputHeight	The height of the input data.
paddingType	The type of padding (Valid or Same). Defaults to None.

◆ Convolution() [3/3]

Convolution	(	const size_t	inSize,
		const size_t	outSize,
		const size_t	kernelWidth,
		const size_t	kernelHeight,
		const size_t	strideWidth,
		const size_t	strideHeight,
		const std::tuple< size_t, size_t > &	padW,
		const std::tuple< size_t, size_t > &	padH,
		const size_t	inputWidth = `0`,
		const size_t	inputHeight = `0`,
		const std::string &	paddingType = `"None"`
	)

Create the Convolution object using the specified number of input maps, output maps, filter size, stride and padding parameter.

Parameters

inSize	The number of input maps.
outSize	The number of output maps.
kernelWidth	Width of the filter/kernel.
kernelHeight	Height of the filter/kernel.
strideWidth	Stride of filter application in the x direction.
strideHeight	Stride of filter application in the y direction.
padW	A two-value tuple indicating padding widths of the input. First value is padding at left side. Second value is padding on right side.
padH	A two-value tuple indicating padding heights of the input. First value is padding at top. Second value is padding on bottom.
inputWidth	The width of the input data.
inputHeight	The height of the input data.
paddingType	The type of padding (Valid or Same). Defaults to None.

Member Function Documentation

◆ Backward()

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

◆ Bias()

arma::mat& Bias ( )

inline

Modify the bias weights of the layer.

Definition at line 246 of file convolution.hpp.

References Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >::serialize().

◆ Delta() [1/2]

const OutputDataType& Delta ( ) const

inline

Get the delta.

Definition at line 170 of file convolution.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 172 of file convolution.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.

◆ Gradient() [1/3]

void Gradient	(	const arma::Mat< eT > &&	,
		arma::Mat< eT > &&	error,
		arma::Mat< eT > &&	gradient
	)

◆ Gradient() [2/3]

const OutputDataType& Gradient ( ) const

inline

Get the gradient.

Definition at line 175 of file convolution.hpp.

◆ Gradient() [3/3]

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 177 of file convolution.hpp.

◆ InputHeight() [1/2]

const size_t& InputHeight ( ) const

inline

Get the input height.

Definition at line 185 of file convolution.hpp.

◆ InputHeight() [2/2]

size_t& InputHeight ( )

inline

Modify the input height.

Definition at line 187 of file convolution.hpp.

◆ InputParameter() [1/2]

const InputDataType& InputParameter ( ) const

inline

Get the input parameter.

Definition at line 160 of file convolution.hpp.

◆ InputParameter() [2/2]

InputDataType& InputParameter ( )

inline

Modify the input parameter.

Definition at line 162 of file convolution.hpp.

◆ InputSize()

size_t InputSize ( ) const

inline

Get the input size.

Definition at line 200 of file convolution.hpp.

◆ InputWidth() [1/2]

const size_t& InputWidth ( ) const

inline

Get the input width.

Definition at line 180 of file convolution.hpp.

◆ InputWidth() [2/2]

size_t& InputWidth ( )

inline

Modify input the width.

Definition at line 182 of file convolution.hpp.

◆ KernelHeight() [1/2]

size_t KernelHeight ( ) const

inline

Get the kernel height.

Definition at line 211 of file convolution.hpp.

◆ KernelHeight() [2/2]

size_t& KernelHeight ( )

inline

Modify the kernel height.

Definition at line 213 of file convolution.hpp.

◆ KernelWidth() [1/2]

size_t KernelWidth ( ) const

inline

Get the kernel width.

Definition at line 206 of file convolution.hpp.

◆ KernelWidth() [2/2]

size_t& KernelWidth ( )

inline

Modify the kernel width.

Definition at line 208 of file convolution.hpp.

◆ OutputHeight() [1/2]

const size_t& OutputHeight ( ) const

inline

Get the output height.

Definition at line 195 of file convolution.hpp.

◆ OutputHeight() [2/2]

size_t& OutputHeight ( )

inline

Modify the output height.

Definition at line 197 of file convolution.hpp.

◆ OutputParameter() [1/2]

const OutputDataType& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 165 of file convolution.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 167 of file convolution.hpp.

◆ OutputSize()

size_t OutputSize ( ) const

inline

Get the output size.

Definition at line 203 of file convolution.hpp.

◆ OutputWidth() [1/2]

const size_t& OutputWidth ( ) const

inline

Get the output width.

Definition at line 190 of file convolution.hpp.

◆ OutputWidth() [2/2]

size_t& OutputWidth ( )

inline

Modify the output width.

Definition at line 192 of file convolution.hpp.

◆ PadHBottom() [1/2]

size_t PadHBottom ( ) const

inline

Get the bottom padding height.

Definition at line 231 of file convolution.hpp.

◆ PadHBottom() [2/2]

size_t& PadHBottom ( )

inline

Modify the bottom padding height.

Definition at line 233 of file convolution.hpp.

◆ PadHTop() [1/2]

size_t PadHTop ( ) const

inline

Get the top padding height.

Definition at line 226 of file convolution.hpp.

◆ PadHTop() [2/2]

size_t& PadHTop ( )

inline

Modify the top padding height.

Definition at line 228 of file convolution.hpp.

◆ PadWLeft() [1/2]

size_t PadWLeft ( ) const

inline

Get the left padding width.

Definition at line 236 of file convolution.hpp.

◆ PadWLeft() [2/2]

size_t& PadWLeft ( )

inline

Modify the left padding width.

Definition at line 238 of file convolution.hpp.

◆ PadWRight() [1/2]

size_t PadWRight ( ) const

inline

Get the right padding width.

Definition at line 241 of file convolution.hpp.

◆ PadWRight() [2/2]

size_t& PadWRight ( )

inline

Modify the right padding width.

Definition at line 243 of file convolution.hpp.

◆ Parameters() [1/2]

const OutputDataType& Parameters ( ) const

inline

Get the parameters.

Definition at line 155 of file convolution.hpp.

◆ Parameters() [2/2]

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 157 of file convolution.hpp.

◆ Reset()

void Reset ( )

◆ serialize()

void serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the layer.

Referenced by Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >::Bias().

◆ StrideHeight() [1/2]

size_t StrideHeight ( ) const

inline

Get the stride height.

Definition at line 221 of file convolution.hpp.

◆ StrideHeight() [2/2]

size_t& StrideHeight ( )

inline

Modify the stride height.

Definition at line 223 of file convolution.hpp.

◆ StrideWidth() [1/2]

size_t StrideWidth ( ) const

inline

Get the stride width.

Definition at line 216 of file convolution.hpp.

◆ StrideWidth() [2/2]

size_t& StrideWidth ( )

inline

Modify the stride width.

Definition at line 218 of file convolution.hpp.

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

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

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ Convolution() [1/3]

◆ Convolution() [2/3]

◆ Convolution() [3/3]

Member Function Documentation

◆ Backward()

◆ Bias()

◆ Delta() [1/2]

◆ Delta() [2/2]

◆ Forward()

◆ Gradient() [1/3]

◆ Gradient() [2/3]

◆ Gradient() [3/3]

◆ InputHeight() [1/2]

◆ InputHeight() [2/2]

◆ InputParameter() [1/2]

◆ InputParameter() [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]

◆ PadHBottom() [1/2]

◆ PadHBottom() [2/2]

◆ PadHTop() [1/2]

◆ PadHTop() [2/2]

◆ PadWLeft() [1/2]

◆ PadWLeft() [2/2]

◆ PadWRight() [1/2]

◆ PadWRight() [2/2]

◆ Parameters() [1/2]

◆ Parameters() [2/2]

◆ Reset()

◆ serialize()

◆ StrideHeight() [1/2]

◆ StrideHeight() [2/2]

◆ StrideWidth() [1/2]

◆ StrideWidth() [2/2]