Base class with abstract and basic function definitions. All models will be derived from this class.
More...
#include <FgIModel.h>
Public Member Functions | |
virtual Scalar | Function (const af::array &x, af::array &outGradient) |
Cost function the given x inputs. 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... | |
int | GetDataLenght () |
Gets data lenght. More... | |
int | GetDataDimensionality () |
Gets data dimensionality. More... | |
ModelType | GetModelType () |
Gets model type. More... | |
virtual void | SetBatchSize (int size) |
Sets batch size. More... | |
int | GetBatchSize () |
Gets batch size. More... | |
void | SetIndexes (af::array &indexes) |
Sets the batch indexes. More... | |
Protected Member Functions | |
IModel (int numData, int numDimension, ModelType type) | |
Constructor. More... | |
Protected Attributes | |
ModelType | mType |
int | iN |
dataset length More... | |
int | iD |
dataset dimension More... | |
int | iBatchSize |
size of the batch More... | |
af::array | afIndexes |
indexes of /f$\mathbf{X}/f$ for batch learning 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 |
Base class with abstract and basic function definitions. All models will be derived from this class.
HmetalT, 26.10.2017.
Definition at line 102 of file FgIModel.h.
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protected |
Constructor.
Hmetal T, 16/04/2019.
numData | Number of data samples. |
numDimension | Number of data dimensions. |
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virtual |
Cost function the given x inputs.
Hmetal T, 29.11.2017.
x | The parameter input. |
outGradient | [in,out] The gradient. |
Reimplemented in NeuralEngine::MachineLearning::GPModels::AEP::SDGPLVM< Scalar >, NeuralEngine::MachineLearning::GPModels::AEP::SDGPR< Scalar >, NeuralEngine::MachineLearning::GPModels::AEP::SDGPSSM< Scalar >, NeuralEngine::MachineLearning::GPModels::AEP::SGPLVM< Scalar >, NeuralEngine::MachineLearning::GPModels::AEP::SGPR< Scalar >, and NeuralEngine::MachineLearning::GPModels::AEP::SGPSSM< Scalar >.
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pure virtual |
Gets number of parameters to be optimized.
, 26.06.2018.
Implemented in NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::DeepGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPSSBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPSSMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPLVMBaseModel< Scalar >, and NeuralEngine::MachineLearning::GPModels::SparseGPSSMBaseModel< Scalar >.
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pure virtual |
Sets the parameters for each optimization iteration.
, 26.06.2018.
param | The parameter. |
Implemented in NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::DeepGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPSSBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPSSMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPLVMBaseModel< Scalar >, and NeuralEngine::MachineLearning::GPModels::SparseGPSSMBaseModel< Scalar >.
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pure virtual |
Gets the parameters for each optimization iteration.
, 26.06.2018.
param | The parameter. |
Implemented in NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::DeepGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPSSBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPSSMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPLVMBaseModel< Scalar >, and NeuralEngine::MachineLearning::GPModels::SparseGPSSMBaseModel< Scalar >.
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pure virtual |
Updates the parameters.
, 26.06.2018.
Implemented in NeuralEngine::MachineLearning::GPModels::GPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::DeepGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::GPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPLVMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseDeepGPSSMBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPBaseModel< Scalar >, NeuralEngine::MachineLearning::GPModels::SparseGPLVMBaseModel< Scalar >, and NeuralEngine::MachineLearning::GPModels::SparseGPSSMBaseModel< Scalar >.
int NeuralEngine::MachineLearning::IModel< Scalar >::GetDataLenght | ( | ) |
Gets data lenght.
Hmetal T, 16/04/2019.
int NeuralEngine::MachineLearning::IModel< Scalar >::GetDataDimensionality | ( | ) |
Gets data dimensionality.
Hmetal T, 16/04/2019.
ModelType NeuralEngine::MachineLearning::IModel< Scalar >::GetModelType | ( | ) |
Gets model type.
Hmetal T, 16/04/2019.
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virtual |
Sets batch size.
Hmetal T, 16/04/2019.
size | The size. |
int NeuralEngine::MachineLearning::IModel< Scalar >::GetBatchSize | ( | ) |
Gets batch size.
Hmetal T, 16/04/2019.
void NeuralEngine::MachineLearning::IModel< Scalar >::SetIndexes | ( | af::array & | indexes | ) |
Sets the batch indexes.
Hmetal T, 31/08/2020.
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inlineprivate |
Definition at line 231 of file FgIModel.h.
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friend |
Definition at line 228 of file FgIModel.h.
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protected |
Definition at line 218 of file FgIModel.h.
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protected |
dataset length
Definition at line 220 of file FgIModel.h.
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protected |
dataset dimension
Definition at line 221 of file FgIModel.h.
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protected |
size of the batch
Definition at line 222 of file FgIModel.h.
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protected |
indexes of /f$\mathbf{X}/f$ for batch learning
Definition at line 223 of file FgIModel.h.
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protected |
floating point precision flag for af::array
Definition at line 225 of file FgIModel.h.