Abstract class for back-constraints, a kind of prior knowledge to force topological positions of uncertain latent inputs. All types of back-constraints will be derived from this class.
More...
#include <FgIBackconstraint.h>
Public Member Functions | |
IBackconstraint (BackConstType type) | |
Constructor. More... | |
virtual | ~IBackconstraint () |
Destructor. More... | |
virtual void | Init (const af::array &Y, const af::array &X, const af::array &segments)=0 |
Initializes this object. More... | |
virtual int | GetNumParameters ()=0 |
Gets number of to be optimized parameters. More... | |
virtual void | SetParameters (const af::array ¶m)=0 |
Sets the parameters. More... | |
virtual af::array | GetParameters ()=0 |
Gets the parameters. More... | |
virtual af::array | GetConstraintX ()=0 |
Gets constraint x coordinates. More... | |
virtual af::array | BackconstraintGradient (const af::array &gX)=0 |
Back-constraint gradient. More... | |
BackConstType | GetType () |
Gets the back-constraint type. More... | |
Protected Attributes | |
int | iN |
dataset length More... | |
int | iq |
latent dimension 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) |
Private Attributes | |
BackConstType | backType |
Friends | |
class | boost::serialization::access |
Abstract class for back-constraints, a kind of prior knowledge to force topological positions of uncertain latent inputs. All types of back-constraints will be derived from this class.
HmetalT, 26.10.2017.
Definition at line 41 of file FgIBackconstraint.h.
NeuralEngine::MachineLearning::GPModels::IBackconstraint< Scalar >::IBackconstraint | ( | BackConstType | type | ) |
Constructor.
Hmetal T, 17/09/2020.
type | The type. |
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virtual |
Destructor.
Hmetal T, 17/09/2020.
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pure virtual |
Initializes this object.
Hmetal T, 17/09/2020.
Y | An af::array to process. |
X | An af::array to process. |
Implemented in NeuralEngine::MachineLearning::GPModels::KBR< Scalar >, and NeuralEngine::MachineLearning::GPModels::PTC< Scalar >.
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pure virtual |
Gets number of to be optimized parameters.
Hmetal T, 17/09/2020.
Implemented in NeuralEngine::MachineLearning::GPModels::KBR< Scalar >, and NeuralEngine::MachineLearning::GPModels::PTC< Scalar >.
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pure virtual |
Sets the parameters.
Hmetal T, 17/09/2020.
param | The parameter. |
Implemented in NeuralEngine::MachineLearning::GPModels::KBR< Scalar >, and NeuralEngine::MachineLearning::GPModels::PTC< Scalar >.
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pure virtual |
Gets the parameters.
Hmetal T, 17/09/2020.
Implemented in NeuralEngine::MachineLearning::GPModels::KBR< Scalar >, and NeuralEngine::MachineLearning::GPModels::PTC< Scalar >.
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pure virtual |
Gets constraint x coordinates.
Hmetal T, 17/09/2020.
Implemented in NeuralEngine::MachineLearning::GPModels::KBR< Scalar >, and NeuralEngine::MachineLearning::GPModels::PTC< Scalar >.
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pure virtual |
Back-constraint gradient.
Hmetal T, 17/09/2020.
gX | The gradient of \(\mathbf{X}\). |
Implemented in NeuralEngine::MachineLearning::GPModels::KBR< Scalar >, and NeuralEngine::MachineLearning::GPModels::PTC< Scalar >.
BackConstType NeuralEngine::MachineLearning::GPModels::IBackconstraint< Scalar >::GetType | ( | ) |
Gets the back-constraint type.
Hmetal T, 15/09/2020.
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inlineprivate |
Definition at line 139 of file FgIBackconstraint.h.
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friend |
Definition at line 136 of file FgIBackconstraint.h.
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protected |
dataset length
Definition at line 128 of file FgIBackconstraint.h.
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protected |
latent dimension
Definition at line 129 of file FgIBackconstraint.h.
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protected |
floating point precision flag for af::array
Definition at line 131 of file FgIBackconstraint.h.
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private |
Definition at line 134 of file FgIBackconstraint.h.