AddWeightsXMLTo(void *parent)=0 | TMVA::DNN::VGeneralLayer< Architecture_t > | pure virtual |
Backward(Tensor_t &gradients_backward, const Tensor_t &activations_backward)=0 | TMVA::DNN::VGeneralLayer< Architecture_t > | pure virtual |
CopyBiases(const std::vector< Matrix_t > &otherBiases) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
CopyParameters(const VGeneralLayer< Arch > &layer) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
CopyWeights(const std::vector< Matrix_t > &otherWeights) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
fActivationGradients | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fBatchSize | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fBiases | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fBiasGradients | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fDepth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fHeight | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInit | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInputDepth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInputHeight | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInputWidth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fIsTraining | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
Forward(Tensor_t &input, bool applyDropout=false)=0 | TMVA::DNN::VGeneralLayer< Architecture_t > | pure virtual |
fOutput | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWeightGradients | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWeights | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWidth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
GetActivationGradients() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetActivationGradients() | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetActivationGradientsAt(size_t i) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetActivationGradientsAt(size_t i) const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBatchSize() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiases() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiases() | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiasesAt(size_t i) const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiasesAt(size_t i) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiasGradients() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiasGradients() | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiasGradientsAt(size_t i) const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetBiasGradientsAt(size_t i) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetDepth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetExtraLayerParameters() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
GetHeight() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInitialization() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInputDepth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInputHeight() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInputWidth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetOutput() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetOutput() | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetOutputAt(size_t i) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetOutputAt(size_t i) const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeightGradients() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeightGradients() | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeightGradientsAt(size_t i) const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeightGradientsAt(size_t i) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeights() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeights() | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeightsAt(size_t i) const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWeightsAt(size_t i) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetWidth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
Initialize() | TMVA::DNN::VGeneralLayer< Architecture_t > | virtual |
IsTraining() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
Matrix_t typedef | TMVA::DNN::VGeneralLayer< Architecture_t > | private |
Print() const =0 | TMVA::DNN::VGeneralLayer< Architecture_t > | pure virtual |
ReadMatrixXML(void *node, const char *name, Matrix_t &matrix) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
ReadWeightsFromXML(void *parent)=0 | TMVA::DNN::VGeneralLayer< Architecture_t > | pure virtual |
ResetTraining() | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
Scalar_t typedef | TMVA::DNN::VGeneralLayer< Architecture_t > | private |
SetBatchSize(size_t batchSize) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetDepth(size_t depth) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetDropoutProbability(Scalar_t) | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
SetExtraLayerParameters(const std::vector< Matrix_t > &) | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
SetHeight(size_t height) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetInputDepth(size_t inputDepth) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetInputHeight(size_t inputHeight) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetInputWidth(size_t inputWidth) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetIsTraining(bool isTraining) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
SetWidth(size_t width) | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
Tensor_t typedef | TMVA::DNN::VGeneralLayer< Architecture_t > | private |
Update(const Scalar_t learningRate) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
UpdateBiases(const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
UpdateBiasGradients(const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
UpdateWeightGradients(const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
UpdateWeights(const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
VGeneralLayer(size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, size_t WeightsNRows, size_t WeightsNCols, size_t BiasesNSlices, size_t BiasesNRows, size_t BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
VGeneralLayer(size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, size_t Height, size_t Width, size_t WeightsNSlices, std::vector< size_t > WeightsNRows, std::vector< size_t > WeightsNCols, size_t BiasesNSlices, std::vector< size_t > BiasesNRows, std::vector< size_t > BiasesNCols, size_t OutputNSlices, size_t OutputNRows, size_t OutputNCols, EInitialization Init) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
VGeneralLayer(VGeneralLayer< Architecture_t > *layer) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
VGeneralLayer(const VGeneralLayer &) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
WriteMatrixToXML(void *node, const char *name, const Matrix_t &matrix) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
WriteTensorToXML(void *node, const char *name, const std::vector< Matrix_t > &tensor) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
~VGeneralLayer() | TMVA::DNN::VGeneralLayer< Architecture_t > | virtual |