template<typename Architecture_t, typename Layer_t = VGeneralLayer<Architecture_t>, typename DeepNet_t = TDeepNet<Architecture_t, Layer_t>>
class TMVA::DNN::VOptimizer< Architecture_t, Layer_t, DeepNet_t >
Generic Optimizer class.
This class represents the general class for all optimizers in the Deep Learning Module.
Definition at line 45 of file Optimizer.h.
template<typename Architecture_t , typename Layer_t = VGeneralLayer<Architecture_t>, typename DeepNet_t = TDeepNet<Architecture_t, Layer_t>>
| virtual void TMVA::DNN::VOptimizer< Architecture_t, Layer_t, DeepNet_t >::UpdateBiases |
( |
size_t |
layerIndex, |
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std::vector< Matrix_t > & |
biases, |
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const std::vector< Matrix_t > & |
biasGradients |
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) |
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protectedpure virtual |
Update the biases, given the current bias gradients.
Implemented in TMVA::DNN::TAdadelta< Architecture_t, Layer_t, DeepNet_t >, TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t >, TMVA::DNN::TAdam< Architecture_t, Layer_t, DeepNet_t >, TMVA::DNN::TRMSProp< Architecture_t, Layer_t, DeepNet_t >, and TMVA::DNN::TSGD< Architecture_t, Layer_t, DeepNet_t >.
template<typename Architecture_t , typename Layer_t = VGeneralLayer<Architecture_t>, typename DeepNet_t = TDeepNet<Architecture_t, Layer_t>>
| virtual void TMVA::DNN::VOptimizer< Architecture_t, Layer_t, DeepNet_t >::UpdateWeights |
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size_t |
layerIndex, |
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std::vector< Matrix_t > & |
weights, |
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const std::vector< Matrix_t > & |
weightGradients |
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) |
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protectedpure virtual |
Update the weights, given the current weight gradients.
Implemented in TMVA::DNN::TAdadelta< Architecture_t, Layer_t, DeepNet_t >, TMVA::DNN::TAdagrad< Architecture_t, Layer_t, DeepNet_t >, TMVA::DNN::TAdam< Architecture_t, Layer_t, DeepNet_t >, TMVA::DNN::TRMSProp< Architecture_t, Layer_t, DeepNet_t >, and TMVA::DNN::TSGD< Architecture_t, Layer_t, DeepNet_t >.