AddWeightsXMLTo(void *parent) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | virtual |
Backward(Tensor_t &gradients_backward, const Tensor_t &activations_backward) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inlinevirtual |
CellBackward(Matrix_t &state_gradients_backward, const Matrix_t &precStateActivations, const Matrix_t &input, Matrix_t &input_gradient, Matrix_t &dF) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
CellForward(const Matrix_t &input, Matrix_t &dF) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
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 > | |
DoesRememberState() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
DoesReturnSequence() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
fActivationDesc | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fActivationGradients | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fBatchSize | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fBiases | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fBiasGradients | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fCell | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fDepth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fDerivatives | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fDescriptors | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fDx | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fDy | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fF | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
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 isTraining=true) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | virtual |
fOutput | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fRememberState | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fReturnSequence | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fState | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fStateSize | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fTimeSteps | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWeightGradients | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWeightGradientsTensor | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWeightInputGradients | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWeights | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWeightsInput | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWeightsState | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWeightStateGradients | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWeightsTensor | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fWidth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWorkspace | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fX | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
fY | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | private |
GetActivationFunction() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
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 |
GetBiasesState() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetBiasesState() const | TMVA::DNN::RNN::TBasicRNNLayer< 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 |
GetBiasStateGradients() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetBiasStateGradients() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetCell() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetCell() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetDepth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetDerivatives() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetDerivatives() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetDX() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetDY() | TMVA::DNN::RNN::TBasicRNNLayer< 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 |
GetInputSize() const | TMVA::DNN::RNN::TBasicRNNLayer< 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 |
GetState() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetState() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetStateSize() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetTimeSteps() const | TMVA::DNN::RNN::TBasicRNNLayer< 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 |
GetWeightGradientsTensor() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightGradientsTensor() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightInputGradients() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightInputGradients() const | TMVA::DNN::RNN::TBasicRNNLayer< 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 |
GetWeightsInput() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightsInput() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightsState() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightsState() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightStateGradients() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightStateGradients() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightsTensor() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWeightsTensor() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetWidth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetX() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
GetY() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | inline |
HelperDescriptor_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
Initialize() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | virtual |
InitState(DNN::EInitialization m=DNN::EInitialization::kZero) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
InitTensors() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
IsTraining() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
LayerDescriptor_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
Matrix_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
Print() const | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | virtual |
ReadMatrixXML(void *node, const char *name, Matrix_t &matrix) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
ReadWeightsFromXML(void *parent) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | virtual |
ResetTraining() | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
RNNDescriptors_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
RNNWorkspace_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
Scalar_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
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 |
TBasicRNNLayer(size_t batchSize, size_t stateSize, size_t inputSize, size_t timeSteps, bool rememberState=false, bool returnSequence=false, DNN::EActivationFunction f=DNN::EActivationFunction::kTanh, bool training=true, DNN::EInitialization fA=DNN::EInitialization::kZero) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
TBasicRNNLayer(const TBasicRNNLayer &) | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
Tensor_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
TensorDescriptor_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | |
Update(const Scalar_t learningRate) | TMVA::DNN::RNN::TBasicRNNLayer< 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 > | |
WeightsDescriptor_t typedef | TMVA::DNN::RNN::TBasicRNNLayer< 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 > | |
~TBasicRNNLayer() | TMVA::DNN::RNN::TBasicRNNLayer< Architecture_t > | virtual |
~VGeneralLayer() | TMVA::DNN::VGeneralLayer< Architecture_t > | virtual |