AdaptiveMaxPooling< InputDataType, OutputDataType > Class Template Reference

Implementation of the AdaptiveMaxPooling layer. More...

Public Member Functions

 AdaptiveMaxPooling ()
 Create the AdaptiveMaxPooling object. More...

 
 AdaptiveMaxPooling (const size_t outputWidth, const size_t outputHeight)
 Create the AdaptiveMaxPooling object. More...

 
 AdaptiveMaxPooling (const std::tuple< size_t, size_t > &outputShape)
 Create the AdaptiveMaxPooling object. More...

 
template
void Backward (const arma::Mat< eT > &input, const arma::Mat< eT > &gy, arma::Mat< eT > &g)
 Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, calculating the function f(x) by propagating x backwards through f. More...

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

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

 
template
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...

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

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

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

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

 
size_t & InputWidth ()
 Modify the input width. More...

 
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...

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

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

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

 

Detailed Description


template
class mlpack::ann::AdaptiveMaxPooling< InputDataType, OutputDataType >

Implementation of the AdaptiveMaxPooling layer.

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 33 of file adaptive_max_pooling.hpp.

Constructor & Destructor Documentation

◆ AdaptiveMaxPooling() [1/3]

Create the AdaptiveMaxPooling object.

◆ AdaptiveMaxPooling() [2/3]

AdaptiveMaxPooling ( const size_t  outputWidth,
const size_t  outputHeight 
)

Create the AdaptiveMaxPooling object.

Parameters
outputWidthWidth of the output.
outputHeightHeight of the output.

◆ AdaptiveMaxPooling() [3/3]

AdaptiveMaxPooling ( const std::tuple< size_t, size_t > &  outputShape)

Create the AdaptiveMaxPooling object.

Parameters
outputShapeA two-value tuple indicating width and height of the output.

Member Function Documentation

◆ Backward()

void Backward ( const arma::Mat< eT > &  input,
const arma::Mat< eT > &  gy,
arma::Mat< eT > &  g 
)

Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, 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.

◆ Delta() [1/2]

const OutputDataType& Delta ( ) const
inline

Get the delta.

Definition at line 87 of file adaptive_max_pooling.hpp.

◆ Delta() [2/2]

OutputDataType& Delta ( )
inline

Modify the delta.

Definition at line 89 of file adaptive_max_pooling.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.

◆ InputHeight() [1/2]

size_t InputHeight ( ) const
inline

Get the input height.

Definition at line 97 of file adaptive_max_pooling.hpp.

◆ InputHeight() [2/2]

size_t& InputHeight ( )
inline

Modify the input height.

Definition at line 99 of file adaptive_max_pooling.hpp.

◆ InputSize()

size_t InputSize ( ) const
inline

Get the input size.

Definition at line 112 of file adaptive_max_pooling.hpp.

◆ InputWidth() [1/2]

size_t InputWidth ( ) const
inline

Get the input width.

Definition at line 92 of file adaptive_max_pooling.hpp.

◆ InputWidth() [2/2]

size_t& InputWidth ( )
inline

Modify the input width.

Definition at line 94 of file adaptive_max_pooling.hpp.

◆ OutputHeight() [1/2]

size_t OutputHeight ( ) const
inline

Get the output height.

Definition at line 107 of file adaptive_max_pooling.hpp.

◆ OutputHeight() [2/2]

size_t& OutputHeight ( )
inline

Modify the output height.

Definition at line 109 of file adaptive_max_pooling.hpp.

◆ OutputParameter() [1/2]

const OutputDataType& OutputParameter ( ) const
inline

Get the output parameter.

Definition at line 80 of file adaptive_max_pooling.hpp.

◆ OutputParameter() [2/2]

OutputDataType& OutputParameter ( )
inline

Modify the output parameter.

Definition at line 84 of file adaptive_max_pooling.hpp.

◆ OutputSize()

size_t OutputSize ( ) const
inline

Get the output size.

Definition at line 115 of file adaptive_max_pooling.hpp.

References Log::Fatal, and AdaptiveMaxPooling< InputDataType, OutputDataType >::serialize().

◆ OutputWidth() [1/2]

size_t OutputWidth ( ) const
inline

Get the output width.

Definition at line 102 of file adaptive_max_pooling.hpp.

◆ OutputWidth() [2/2]

size_t& OutputWidth ( )
inline

Modify the output width.

Definition at line 104 of file adaptive_max_pooling.hpp.

◆ serialize()

void serialize ( Archive &  ar,
const unsigned int  version 
)

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