Implementation of the concat performance class. More...
Public Member Functions | |
| ConcatPerformance (const size_t inSize=0, OutputLayerType &&outputLayer=OutputLayerType()) | |
| Create the ConcatPerformance object. More... | |
template < typename eT > | |
| void | Backward (const arma::Mat< eT > &input, const arma::Mat< eT > &target, arma::Mat< eT > &output) |
| Ordinary feed backward pass of a neural network. More... | |
| OutputDataType & | Delta () const |
| Get the delta. More... | |
| OutputDataType & | Delta () |
| Modify the delta. More... | |
template < typename eT > | |
| double | Forward (const arma::Mat< eT > &input, arma::Mat< eT > &target) |
| size_t | InSize () const |
| Get the number of inputs. More... | |
| OutputDataType & | OutputParameter () const |
| Get the output parameter. More... | |
| OutputDataType & | OutputParameter () |
| Modify the output parameter. More... | |
template < typename Archive > | |
| void | serialize (Archive &, const uint32_t) |
| Serialize the layer. More... | |
Detailed Description
template<typename OutputLayerType = NegativeLogLikelihood<>, typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >
Implementation of the concat performance class.
The class works as a feed-forward fully connected network container which plugs performance layers together.
- Template Parameters
-
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 37 of file concat_performance.hpp.
Constructor & Destructor Documentation
◆ ConcatPerformance()
| ConcatPerformance | ( | const size_t | inSize = 0, |
| OutputLayerType && | outputLayer = OutputLayerType() |
||
| ) |
Create the ConcatPerformance object.
- Parameters
-
inSize The number of inputs. outputLayer Output layer used to evaluate the network.
Member Function Documentation
◆ Backward()
| void Backward | ( | const arma::Mat< eT > & | input, |
| const arma::Mat< eT > & | target, | ||
| arma::Mat< eT > & | output | ||
| ) |
Ordinary feed backward pass of a neural network.
The negative log likelihood layer expectes that the input contains log-probabilities for each class. The layer also expects a class index, in the range between 1 and the number of classes, as target when calling the Forward function.
- Parameters
-
input The propagated input activation. target The target vector, that contains the class index in the range between 1 and the number of classes. output The calculated error.
◆ Delta() [1/2]
|
inline |
Get the delta.
Definition at line 80 of file concat_performance.hpp.
◆ Delta() [2/2]
|
inline |
Modify the delta.
Definition at line 82 of file concat_performance.hpp.
◆ Forward()
| double Forward | ( | const arma::Mat< eT > & | input, |
| arma::Mat< eT > & | target | ||
| ) |
◆ InSize()
|
inline |
Get the number of inputs.
Definition at line 85 of file concat_performance.hpp.
References ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >::serialize().
◆ OutputParameter() [1/2]
|
inline |
Get the output parameter.
Definition at line 75 of file concat_performance.hpp.
◆ OutputParameter() [2/2]
|
inline |
Modify the output parameter.
Definition at line 77 of file concat_performance.hpp.
◆ serialize()
| void serialize | ( | Archive & | , |
| const uint32_t | |||
| ) |
Serialize the layer.
Referenced by ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >::InSize().
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/ann/layer/concat_performance.hpp