Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType > Class Template Reference

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 kW, const size_t kH, const size_t dW=1, const size_t dH=1, const size_t padW=0, const size_t padH=0, const size_t inputWidth=0, const size_t inputHeight=0)
 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...

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

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

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

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

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

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

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

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

 
size_t & OutputWidth ()
 Modify the output width. 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 unsigned int)
 Serialize the layer. 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
ForwardConvolutionRuleConvolution to perform forward process.
BackwardConvolutionRuleConvolution to perform backward process.
GradientConvolutionRuleConvolution to calculate gradient.
InputDataTypeType of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube).
OutputDataTypeType 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() [1/2]

Create the Convolution object.

◆ Convolution() [2/2]

Convolution ( const size_t  inSize,
const size_t  outSize,
const size_t  kW,
const size_t  kH,
const size_t  dW = 1,
const size_t  dH = 1,
const size_t  padW = 0,
const size_t  padH = 0,
const size_t  inputWidth = 0,
const size_t  inputHeight = 0 
)

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

Parameters
inSizeThe number of input maps.
outSizeThe number of output maps.
kWWidth of the filter/kernel.
kHHeight of the filter/kernel.
dWStride of filter application in the x direction.
dHStride of filter application in the y direction.
padWPadding width of the input.
padHPadding height of the input.
inputWidthThe width of the input data.
inputHeightThe height of the input data.

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
inputThe propagated input activation.
gyThe backpropagated error.
gThe calculated gradient.

◆ Bias()

arma::mat& Bias ( )
inline

◆ Delta() [1/2]

OutputDataType const& Delta ( ) const
inline

Get the delta.

Definition at line 136 of file convolution.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

Modify the delta.

Definition at line 138 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
inputInput data used for evaluating the specified function.
outputResulting output activation.

◆ Gradient() [1/3]

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

◆ Gradient() [2/3]

OutputDataType const& Gradient ( ) const
inline

Get the gradient.

Definition at line 141 of file convolution.hpp.

◆ Gradient() [3/3]

OutputDataType& Gradient ( )
inline

Modify the gradient.

Definition at line 143 of file convolution.hpp.

◆ InputHeight() [1/2]

size_t const& InputHeight ( ) const
inline

Get the input height.

Definition at line 151 of file convolution.hpp.

◆ InputHeight() [2/2]

size_t& InputHeight ( )
inline

Modify the input height.

Definition at line 153 of file convolution.hpp.

◆ InputParameter() [1/2]

InputDataType const& InputParameter ( ) const
inline

Get the input parameter.

Definition at line 126 of file convolution.hpp.

◆ InputParameter() [2/2]

InputDataType& InputParameter ( )
inline

Modify the input parameter.

Definition at line 128 of file convolution.hpp.

◆ InputWidth() [1/2]

size_t const& InputWidth ( ) const
inline

Get the input width.

Definition at line 146 of file convolution.hpp.

◆ InputWidth() [2/2]

size_t& InputWidth ( )
inline

Modify input the width.

Definition at line 148 of file convolution.hpp.

◆ OutputHeight() [1/2]

size_t const& OutputHeight ( ) const
inline

Get the output height.

Definition at line 161 of file convolution.hpp.

◆ OutputHeight() [2/2]

size_t& OutputHeight ( )
inline

Modify the output height.

Definition at line 163 of file convolution.hpp.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 131 of file convolution.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 133 of file convolution.hpp.

◆ OutputWidth() [1/2]

size_t const& OutputWidth ( ) const
inline

Get the output width.

Definition at line 156 of file convolution.hpp.

◆ OutputWidth() [2/2]

size_t& OutputWidth ( )
inline

Modify the output width.

Definition at line 158 of file convolution.hpp.

◆ Parameters() [1/2]

OutputDataType const& Parameters ( ) const
inline

Get the parameters.

Definition at line 121 of file convolution.hpp.

◆ Parameters() [2/2]

OutputDataType& Parameters ( )
inline

Modify the parameters.

Definition at line 123 of file convolution.hpp.

◆ Reset()

void Reset ( )

◆ serialize()

void serialize ( Archive &  ar,
const unsigned  int 
)

The documentation for this class was generated from the following file:
  • /home/jenkins-mlpack/mlpack.org/_src/mlpack-3.2.1/src/mlpack/methods/ann/layer/convolution.hpp