Padding< InputDataType, OutputDataType > Class Template Reference

Implementation of the Padding module class. More...

Public Member Functions

 Padding (const size_t padWLeft=0, const size_t padWRight=0, const size_t padHTop=0, const size_t padHBottom=0)
 Create the Padding object using the specified number of output 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, calculating the function f(x) by propagating x backwards trough f. 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...

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

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

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

 

Detailed Description


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

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

Implementation of the Padding module class.

The Padding module applies a bias term to the incoming data.

Template Parameters
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 68 of file layer_types.hpp.

Constructor & Destructor Documentation

◆ Padding()

Padding ( const size_t  padWLeft = 0,
const size_t  padWRight = 0,
const size_t  padHTop = 0,
const size_t  padHBottom = 0 
)

Create the Padding object using the specified number of output units.

Parameters
padWLeftLeft padding width of the input.
padWLeftRight padding width of the input.
padHTopTop padding height of the input.
padHBottomBottom padding height of the input.

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 trough f.

Using the results from the feed forward pass.

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

◆ Delta() [1/2]

OutputDataType const& Delta ( ) const
inline

Get the delta.

Definition at line 80 of file padding.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

Modify the delta.

Definition at line 82 of file padding.hpp.

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

◆ 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.

◆ OutputParameter() [1/2]

OutputDataType const& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 75 of file padding.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 77 of file padding.hpp.

◆ serialize()

void serialize ( Archive &  ar,
const unsigned  int 
)

Serialize the layer.

Referenced by Padding< InputDataType, OutputDataType >::Delta().


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