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


Public Member Functions | |
| SparseGPBaseLayer (int numPoints, int numPseudos, int outputDim, int inputDim) | |
| Constructor. More... | |
| virtual | ~SparseGPBaseLayer () |
| Destructor. More... | |
| virtual void | ForwardPredictionPost (const af::array *mx, const af::array *vx, af::array &mout, af::array &vout) override |
| Forward prediction of posterior function values. More... | |
| virtual void | SampleFromPost (const af::array &inX, af::array &outfsample) override |
| Samples from posterior. More... | |
| void | ComputeKuu () |
| Calculates the kernel matrix of pseudo inputs. More... | |
| void | ComputeKfu (const af::array &inX) |
| Calculates the kernel matrix of inputes and pseudo inputs. More... | |
| af::array | GetPseudoInputs () |
| Gets pseudo inputs. More... | |
| virtual int | GetNumParameters () override |
| Gets number of parameters to be optimized. More... | |
| virtual void | SetParameters (const af::array ¶m) override |
| Sets the parameters for each optimization iteration. More... | |
| virtual af::array | GetParameters () override |
| Gets the parameters for each optimization iteration. More... | |
| virtual void | FixInducing (bool isfixed) |
| Set fixation for inducing inputs. More... | |
| virtual void | UpdateParameters () override |
| Updates the parameters. More... | |
| virtual void | InitParameters (af::array *X=nullptr) override |
| Initializes the parameters. More... | |
Public Member Functions inherited from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar > | |
| 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 | |
| SparseGPBaseLayer () | |
| Default constructor. More... | |
| virtual void | ReinitParameters () override |
| Reinitializes the parameters. More... | |
| virtual void | ForwardPredictionDeterministicPost (const af::array &mx, af::array *mout, af::array *vout) |
| Deterministic forward propagation through posterior. More... | |
| virtual void | ForwardPredictionRandomPost (const af::array &mx, const af::array &vx, af::array &mout, af::array &vout, PropagationMode mode=PropagationMode::MomentMatching) |
| Forward prediction through random posterior. More... | |
Protected Member Functions inherited from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar > | |
| 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 | ik |
| af::array | afMu |
| af::array | afSu |
| af::array | afInvSu |
| af::array | afInvSuMu |
| af::array | T1 |
| af::array | T2 |
| af::array | T2_R |
| af::array | afXu |
| af::array | afKuu |
| af::array | afInvKuu |
| af::array | afKfu |
| bool | isFixedInducing |
Protected Attributes inherited from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar > | |
| 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 34 of file FgSparseGPBaseLayer.h.
| NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >::SparseGPBaseLayer | ( | int | numPoints, |
| int | numPseudos, | ||
| int | outputDim, | ||
| int | inputDim | ||
| ) |
Constructor.
, 15.05.2018.
| numPoints | Number of points. |
| numPseudos | Number of pseudo inputs. |
| outputDim | The output dimension. |
| inputDim | The input dimension. |
|
virtual |
Destructor.
, 15.05.2018.
|
inlineprotected |
|
overridevirtual |
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 from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer2nd< Scalar >.
|
overridevirtual |
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 from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
| void NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >::ComputeKuu | ( | ) |
Calculates the kernel matrix of pseudo inputs.
, 15.05.2018.
| void NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >::ComputeKfu | ( | const af::array & | inX | ) |
Calculates the kernel matrix of inputes and pseudo inputs.
, 15.05.2018.
| af::array NeuralEngine::MachineLearning::GPModels::SparseGPBaseLayer< Scalar >::GetPseudoInputs | ( | ) |
Gets pseudo inputs.
Hmetal T, 17/06/2019.
|
overridevirtual |
Gets number of parameters to be optimized.
, 26.06.2018.
Reimplemented from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
|
overridevirtual |
Sets the parameters for each optimization iteration.
, 26.06.2018.
| param | The parameter. |
Reimplemented from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
|
overridevirtual |
Gets the parameters for each optimization iteration.
, 26.06.2018.
Reimplemented from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
|
virtual |
Set fixation for inducing inputs.
Hmetal T, 16/12/2019.
| isfixed | True if isfixed. |
|
overridevirtual |
Updates the parameters.
, 26.06.2018.
Reimplemented from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::AEP::SGPLayer< Scalar >, NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer< Scalar >, and NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer2nd< Scalar >.
|
overridevirtual |
Initializes the parameters.
Hmetal T, 09/12/2019.
| X | [in,out] (Optional) If non-null, an af::array to process. |
Reimplemented from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
Reimplemented in NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer< Scalar >, and NeuralEngine::MachineLearning::GPModels::PowerEP::SGPLayer2nd< Scalar >.
|
overrideprotectedvirtual |
Reinitializes the parameters.
Hmetal T, 03/09/2020.
Reimplemented from NeuralEngine::MachineLearning::GPModels::GPBaseLayer< Scalar >.
|
protectedvirtual |
Deterministic forward propagation through posterior.
Hmetal T, 01.04.2019.
| mx | [in,out] The inputs mx. |
| mout | [in,out] The m^{ }_{f}. |
| vout | [in,out] The V^{ }_{ff}. |
Reimplemented in NeuralEngine::MachineLearning::GPModels::AEP::SGPLayer< Scalar >.
|
protectedvirtual |
Forward prediction through random posterior.
, 16.05.2018.
| mx | The inputs mx. |
| vx | If non-null, the variances vx. |
| mout | [in,out] The m^{ }_{f}. |
| vout | [in,out] The V^{ }_{ff}. |
| mode | (Optional) Propagation mode. |
Reimplemented in NeuralEngine::MachineLearning::GPModels::AEP::SGPLayer< Scalar >.
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inlineprivate |
Definition at line 221 of file FgSparseGPBaseLayer.h.
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Definition at line 218 of file FgSparseGPBaseLayer.h.
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Definition at line 198 of file FgSparseGPBaseLayer.h.
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Definition at line 200 of file FgSparseGPBaseLayer.h.
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Definition at line 201 of file FgSparseGPBaseLayer.h.
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Definition at line 202 of file FgSparseGPBaseLayer.h.
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Definition at line 203 of file FgSparseGPBaseLayer.h.
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Definition at line 206 of file FgSparseGPBaseLayer.h.
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Definition at line 207 of file FgSparseGPBaseLayer.h.
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Definition at line 208 of file FgSparseGPBaseLayer.h.
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Definition at line 210 of file FgSparseGPBaseLayer.h.
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Definition at line 211 of file FgSparseGPBaseLayer.h.
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Definition at line 212 of file FgSparseGPBaseLayer.h.
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Definition at line 213 of file FgSparseGPBaseLayer.h.
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Definition at line 215 of file FgSparseGPBaseLayer.h.