Select< InputDataType, OutputDataType > Class Template Reference

The select module selects the specified column from a given input matrix. More...

Public Member Functions

 Select (const size_t index=0, const size_t elements=0)
 Create the Select object. 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 trough f. More...

 
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...

 
OutputDataType & 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::Select< InputDataType, OutputDataType >

The select module selects the specified column from a given input matrix.

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 32 of file select.hpp.

Constructor & Destructor Documentation

◆ Select()

Select ( const size_t  index = 0,
const size_t  elements = 0 
)

Create the Select object.

Parameters
indexThe column which should be extracted from the given input.
elementsThe number of elements that should be used.

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 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& Delta ( ) const
inline

Get the delta.

Definition at line 73 of file select.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

Modify the delta.

Definition at line 75 of file select.hpp.

References Select< 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& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 68 of file select.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 70 of file select.hpp.

◆ serialize()

void serialize ( Archive &  ar,
const unsigned  int 
)

Serialize the layer.

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


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/select.hpp