Implementation of the Atrous Convolution class. More...

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

	AtrousConvolution (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 size_t dilationWidth=1, const size_t dilationHeight=1, const std::string &paddingType="None")
	Create the AtrousConvolution object using the specified number of input maps, output maps, filter size, stride, dilation and padding parameter. More...

	AtrousConvolution (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 size_t dilationWidth=1, const size_t dilationHeight=1, const std::string &paddingType="None")
	Create the AtrousConvolution object using the specified number of input maps, output maps, filter size, stride, dilation and padding parameter. 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, calculating the function f(x) by propagating x backwards through f. More...

arma::mat const &	Bias () const
	Get the bias of the layer. More...

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

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

OutputDataType &	Delta ()
	Modify the delta. More...

size_t	DilationHeight () const
	Get the dilation rate on the Y axis. More...

size_t &	DilationHeight ()
	Modify the dilation rate on the Y axis. More...

size_t	DilationWidth () const
	Get the dilation rate on the X axis. More...

size_t &	DilationWidth ()
	Modify the dilation rate on the X axis. 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 > &, const arma::Mat< eT > &error, arma::Mat< eT > &gradient)

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

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

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

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

size_t	InputShape () const
	Get the shape of the input. More...

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

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...

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

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

ann::Padding const &	Padding () const
	Get the internal Padding layer. More...

ann::Padding &	Padding ()
	Modify the internal Padding layer. More...

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

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

void	Reset ()

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...

arma::cube const &	Weight () const
	Get the weight of the layer. More...

arma::cube &	Weight ()
	Modify the weight of the layer. More...

size_t	WeightSize () const
	Get size of the weight matrix. 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::AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >

Implementation of the Atrous Convolution class.

The Atrous Convolution class represents a single layer of a neural network. Atrous (or Dilated) Convolutions are just simple convolutions applied to input with the defined, spaces included between the kernel cells, in order to capture a larger field of reception, without having to increase dicrete kernel sizes.

Template Parameters

ForwardConvolutionRule	Atrous Convolution to perform forward process.
BackwardConvolutionRule	Atrous Convolution to perform backward process.
GradientConvolutionRule	Atrous 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 52 of file atrous_convolution.hpp.

Constructor & Destructor Documentation

◆ AtrousConvolution() [1/3]

AtrousConvolution ( )

Create the AtrousConvolution object.

◆ AtrousConvolution() [2/3]

AtrousConvolution	(	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 size_t	dilationWidth = `1`,
		const size_t	dilationHeight = `1`,
		const std::string &	paddingType = `"None"`
	)

Create the AtrousConvolution object using the specified number of input maps, output maps, filter size, stride, dilation 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 widht of the input data.
inputHeight	The height of the input data.
dilationWidth	The space between the cells of filters in x direction.
dilationHeight	The space between the cells of filters in y direction.
paddingType	The type of padding (Valid or Same). Defaults to None.

◆ AtrousConvolution() [3/3]

AtrousConvolution	(	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 size_t	dilationWidth = `1`,
		const size_t	dilationHeight = `1`,
		const std::string &	paddingType = `"None"`
	)

Create the AtrousConvolution object using the specified number of input maps, output maps, filter size, stride, dilation 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 widht of the input data.
inputHeight	The height of the input data.
dilationWidth	The space between the cells of filters in x direction.
dilationHeight	The space between the cells of filters in y direction.
paddingType	The type of padding (Valid/Same/None). Defaults to None.

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, 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() [1/2]

arma::mat const& Bias ( ) const

inline

Get the bias of the layer.

Definition at line 182 of file atrous_convolution.hpp.

◆ Bias() [2/2]

arma::mat& Bias ( )

inline

Modify the bias of the layer.

Definition at line 184 of file atrous_convolution.hpp.

◆ Delta() [1/2]

OutputDataType const& Delta ( ) const

inline

Get the delta.

Definition at line 192 of file atrous_convolution.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )

inline

Modify the delta.

Definition at line 194 of file atrous_convolution.hpp.

◆ DilationHeight() [1/2]

size_t DilationHeight ( ) const

inline

Get the dilation rate on the Y axis.

Definition at line 253 of file atrous_convolution.hpp.

◆ DilationHeight() [2/2]

size_t& DilationHeight ( )

inline

Modify the dilation rate on the Y axis.

Definition at line 255 of file atrous_convolution.hpp.

◆ DilationWidth() [1/2]

size_t DilationWidth ( ) const

inline

Get the dilation rate on the X axis.

Definition at line 248 of file atrous_convolution.hpp.

◆ DilationWidth() [2/2]

size_t& DilationWidth ( )

inline

Modify the dilation rate on the X axis.

Definition at line 250 of file atrous_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 > &	,
		const arma::Mat< eT > &	error,
		arma::Mat< eT > &	gradient
	)

◆ Gradient() [2/3]

OutputDataType const& Gradient ( ) const

inline

Get the gradient.

Definition at line 197 of file atrous_convolution.hpp.

◆ Gradient() [3/3]

OutputDataType& Gradient ( )

inline

Modify the gradient.

Definition at line 199 of file atrous_convolution.hpp.

◆ InputHeight() [1/2]

size_t InputHeight ( ) const

inline

Get the input height.

Definition at line 207 of file atrous_convolution.hpp.

◆ InputHeight() [2/2]

size_t& InputHeight ( )

inline

Modify the input height.

Definition at line 209 of file atrous_convolution.hpp.

◆ InputShape()

size_t InputShape ( ) const

inline

Get the shape of the input.

Definition at line 269 of file atrous_convolution.hpp.

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

◆ InputSize()

size_t InputSize ( ) const

inline

Get the input size.

Definition at line 222 of file atrous_convolution.hpp.

◆ InputWidth() [1/2]

size_t InputWidth ( ) const

inline

Get the input width.

Definition at line 202 of file atrous_convolution.hpp.

◆ InputWidth() [2/2]

size_t& InputWidth ( )

inline

Modify input the width.

Definition at line 204 of file atrous_convolution.hpp.

◆ KernelHeight() [1/2]

size_t KernelHeight ( ) const

inline

Get the kernel height.

Definition at line 233 of file atrous_convolution.hpp.

◆ KernelHeight() [2/2]

size_t& KernelHeight ( )

inline

Modify the kernel height.

Definition at line 235 of file atrous_convolution.hpp.

◆ KernelWidth() [1/2]

size_t KernelWidth ( ) const

inline

Get the kernel width.

Definition at line 228 of file atrous_convolution.hpp.

◆ KernelWidth() [2/2]

size_t& KernelWidth ( )

inline

Modify the kernel width.

Definition at line 230 of file atrous_convolution.hpp.

◆ OutputHeight() [1/2]

size_t OutputHeight ( ) const

inline

Get the output height.

Definition at line 217 of file atrous_convolution.hpp.

◆ OutputHeight() [2/2]

size_t& OutputHeight ( )

inline

Modify the output height.

Definition at line 219 of file atrous_convolution.hpp.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const

inline

Get the output parameter.

Definition at line 187 of file atrous_convolution.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )

inline

Modify the output parameter.

Definition at line 189 of file atrous_convolution.hpp.

◆ OutputSize()

size_t OutputSize ( ) const

inline

Get the output size.

Definition at line 225 of file atrous_convolution.hpp.

◆ OutputWidth() [1/2]

size_t OutputWidth ( ) const

inline

Get the output width.

Definition at line 212 of file atrous_convolution.hpp.

◆ OutputWidth() [2/2]

size_t& OutputWidth ( )

inline

Modify the output width.

Definition at line 214 of file atrous_convolution.hpp.

◆ Padding() [1/2]

ann::Padding const& Padding ( ) const

inline

Get the internal Padding layer.

Definition at line 258 of file atrous_convolution.hpp.

◆ Padding() [2/2]

ann::Padding& Padding ( )

inline

Modify the internal Padding layer.

Definition at line 260 of file atrous_convolution.hpp.

◆ Parameters() [1/2]

OutputDataType const& Parameters ( ) const

inline

Get the parameters.

Definition at line 172 of file atrous_convolution.hpp.

◆ Parameters() [2/2]

OutputDataType& Parameters ( )

inline

Modify the parameters.

Definition at line 174 of file atrous_convolution.hpp.

◆ Reset()

void Reset ( )

◆ serialize()

void serialize	(	Archive &	ar,
		const uint32_t
	)

Serialize the layer.

Referenced by AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >::InputShape().

◆ StrideHeight() [1/2]

size_t StrideHeight ( ) const

inline

Get the stride height.

Definition at line 243 of file atrous_convolution.hpp.

◆ StrideHeight() [2/2]

size_t& StrideHeight ( )

inline

Modify the stride height.

Definition at line 245 of file atrous_convolution.hpp.

◆ StrideWidth() [1/2]

size_t StrideWidth ( ) const

inline

Get the stride width.

Definition at line 238 of file atrous_convolution.hpp.

◆ StrideWidth() [2/2]

size_t& StrideWidth ( )

inline

Modify the stride width.

Definition at line 240 of file atrous_convolution.hpp.

◆ Weight() [1/2]

arma::cube const& Weight ( ) const

inline

Get the weight of the layer.

Definition at line 177 of file atrous_convolution.hpp.

◆ Weight() [2/2]

arma::cube& Weight ( )

inline

Modify the weight of the layer.

Definition at line 179 of file atrous_convolution.hpp.

◆ WeightSize()

size_t WeightSize ( ) const

inline

Get size of the weight matrix.

Definition at line 263 of file atrous_convolution.hpp.

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

/home/jenkins-mlpack/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/atrous_convolution.hpp

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ AtrousConvolution() [1/3]

◆ AtrousConvolution() [2/3]

◆ AtrousConvolution() [3/3]

Member Function Documentation

◆ Backward()

◆ Bias() [1/2]

◆ Bias() [2/2]

◆ Delta() [1/2]

◆ Delta() [2/2]

◆ DilationHeight() [1/2]

◆ DilationHeight() [2/2]

◆ DilationWidth() [1/2]

◆ DilationWidth() [2/2]

◆ Forward()

◆ Gradient() [1/3]

◆ Gradient() [2/3]

◆ Gradient() [3/3]

◆ InputHeight() [1/2]

◆ InputHeight() [2/2]

◆ InputShape()

◆ 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]

◆ Padding() [1/2]

◆ Padding() [2/2]

◆ Parameters() [1/2]

◆ Parameters() [2/2]

◆ Reset()

◆ serialize()

◆ StrideHeight() [1/2]

◆ StrideHeight() [2/2]

◆ StrideWidth() [1/2]

◆ StrideWidth() [2/2]

◆ Weight() [1/2]

◆ Weight() [2/2]

◆ WeightSize()