Abstract class for different GP likelihood layers. More...
#include <FgGPBaseLayer.h>


Public Member Functions | |
| GPBaseLayer (int numPoints, int outputDim, int inputDim) | |
| Constructor. More... | |
| virtual | ~GPBaseLayer () |
| Destructor. More... | |
| IKernel< Scalar > * | GetKernel () |
| Gets the kernel function. More... | |
| void | SetKernel (IKernel< Scalar > *kern) |
| Sets a kernel function. More... | |
| virtual void | InitParameters (af::array *X=nullptr) |
| virtual int | GetNumParameters () |
| Gets number of parameters to be optimized. More... | |
| virtual void | SetParameters (const af::array ¶m) |
| Sets the parameters for each optimization iteration. More... | |
| virtual af::array | GetParameters () |
| Gets the parameters for each optimization iteration. More... | |
| virtual void | ForwardPredictionPost (const af::array *mx, const af::array *vx, af::array &mout, af::array &vout) |
| Forward prediction of posterior function values. More... | |
| virtual void | SampleFromPost (const af::array &inX, af::array &outfsample) |
| Samples from posterior. More... | |
| virtual void | FixKernelParameters (bool isfixed) |
| Sets fixation for hyperparameters. More... | |
| virtual void | UpdateParameters () |
| Updates the parameters. More... | |
| virtual void | SetDataSize (int length, int dimension) override |
| Sets data size. More... | |
| void | SetStyles (std::map< std::string, Style< Scalar > > *styles) |
| Sets the syles. More... | |
| void | SetLatentDimension (int q) |
| Sets latent dimension. More... | |
Public Member Functions inherited from NeuralEngine::MachineLearning::ILayer< Scalar > | |
| ILayer (LayerType type, int numPoints, int outputDim) | |
| Constructor. More... | |
| virtual | ~ILayer ()=default |
| Destructor. More... | |
| LayerType | GetType () |
| Gets the layer type. More... | |
| virtual int | GetNumParameters ()=0 |
| Gets number of parameters to be optimized. More... | |
| virtual void | SetParameters (const af::array ¶m)=0 |
| Sets the parameters for each optimization iteration. More... | |
| virtual af::array | GetParameters ()=0 |
| Gets the parameters for each optimization iteration. More... | |
| virtual void | UpdateParameters ()=0 |
| Updates the parameters. More... | |
| virtual void | SetDataSize (int length, int dimension) |
| Sets data size. More... | |
Protected Member Functions | |
| GPBaseLayer () | |
| Default constructor. More... | |
| virtual void | ReinitParameters () |
| Reinitializes the parameters. More... | |
Protected Member Functions inherited from NeuralEngine::MachineLearning::ILayer< Scalar > | |
| ILayer () | |
| Default constructor. More... | |
Protected Attributes | |
| int | iq |
| Latent dimension. More... | |
| bool | isFixedHypers |
| IKernel< Scalar > * | kernel |
| kernel function More... | |
| std::map< std::string, Style< Scalar > > * | mStyles |
| style variable More... | |
| Scalar | JITTER |
| for kernel matrix stability (positive definiteness) More... | |
Protected Attributes inherited from NeuralEngine::MachineLearning::ILayer< Scalar > | |
| int | iD |
| data dimension More... | |
| int | iN |
| data size More... | |
| LayerType | lType |
| liklihood or gp layer More... | |
| af::dtype | m_dType |
| floating point precision flag for af::array More... | |
Private Member Functions | |
| template<class Archive > | |
| void | serialize (Archive &ar, unsigned int version) |
Friends | |
| class | boost::serialization::access |
Abstract class for different GP likelihood layers.
, 27.02.2018.
Definition at line 29 of file FgGPBaseLayer.h.
| NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >::GPBaseLayer | ( | int | numPoints, |
| int | outputDim, | ||
| int | inputDim | ||
| ) |
Constructor.
, 26.04.2018.
| numPoints | Number of training points. |
| outputDim | The output dimension. |
| inputDim | The input dimension. |
|
virtual |
Destructor.
, 26.04.2018.
|
inlineprotected |
| IKernel< Scalar > * NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >::GetKernel | ( | ) |
Gets the kernel function.
, 26.04.2018.
| void NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >::SetKernel | ( | IKernel< Scalar > * | kern | ) |
Sets a kernel function.
, 26.04.2018.
| kernel | [in,out] If non-null, the kernel. |
|
virtual |
|
virtual |
Gets number of parameters to be optimized.
, 26.06.2018.
Implements NeuralEngine::MachineLearning::ILayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
virtual |
Sets the parameters for each optimization iteration.
, 26.06.2018.
| param | The parameter. |
Implements NeuralEngine::MachineLearning::ILayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
virtual |
Gets the parameters for each optimization iteration.
, 26.06.2018.
Implements NeuralEngine::MachineLearning::ILayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
virtual |
Forward prediction of posterior function values.
, 12.06.2018.
| mout | [in,out] The m^{ }_{f}. |
| vout | [in,out] The V^{ }_{ff}. |
| mx | [in,out] The inputs mx. |
| vx | [in,out] (Optional) If non-null, the variances vx. |
Reimplemented in NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer2nd< Scalar >, and NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
virtual |
Samples from posterior.
, 12.06.2018.
| vx | [in,out] (Optional) If non-null, the variances vx. |
| mx | [in,out] The inputs mx. |
| fsample | [in,out] The m^{ }_{f}. |
| inX | The V^{ }_{ff}. |
Reimplemented in NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
virtual |
Sets fixation for hyperparameters.
Hmetal T, 16/12/2019.
| isfixed | True if isfixed. |
|
virtual |
Updates the parameters.
, 26.06.2018.
Implements NeuralEngine::MachineLearning::ILayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::AEP::SGPLayer< Scalar >, NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer< Scalar >, NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer2nd< Scalar >, and NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
overridevirtual |
Sets data size.
Hmetal T, 03/09/2020.
| length | The length. |
| dimension | The dimension. |
Reimplemented from NeuralEngine::MachineLearning::ILayer< Scalar >.
| void NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >::SetStyles | ( | std::map< std::string, Style< Scalar > > * | styles | ) |
Sets the syles.
Hmetal T, 25/09/2020.
| styles | [in,out] If non-null, the styles. |
| void NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >::SetLatentDimension | ( | int | q | ) |
Sets latent dimension.
Hmetal T, 28/06/2022.
| q | An int to process. |
|
protectedvirtual |
Reinitializes the parameters.
Hmetal T, 03/09/2020.
Reimplemented in NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >.
|
inlineprivate |
Definition at line 196 of file FgGPBaseLayer.h.
|
friend |
Definition at line 193 of file FgGPBaseLayer.h.
|
protected |
Latent dimension.
Definition at line 183 of file FgGPBaseLayer.h.
|
protected |
Definition at line 185 of file FgGPBaseLayer.h.
|
protected |
kernel function
Definition at line 187 of file FgGPBaseLayer.h.
|
protected |
style variable
Definition at line 188 of file FgGPBaseLayer.h.
|
protected |
for kernel matrix stability (positive definiteness)
Definition at line 190 of file FgGPBaseLayer.h.