AddWeightsXMLTo(void *parent) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inlinevirtual |
Backward(Tensor_t &gradients_backward, const Tensor_t &activations_backward) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inlinevirtual |
candidate_gate_value | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
CandidateValue(const Matrix_t &input, Matrix_t &dc) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
cell_value | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
CellBackward(Matrix_t &state_gradients_backward, Matrix_t &cell_gradients_backward, const Matrix_t &precStateActivations, const Matrix_t &precCellActivations, const Matrix_t &input_gate, const Matrix_t &forget_gate, const Matrix_t &candidate_gate, const Matrix_t &output_gate, const Matrix_t &input, Matrix_t &input_gradient, Matrix_t &di, Matrix_t &df, Matrix_t &dc, Matrix_t &dout, size_t t) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
CellForward(Matrix_t &inputGateValues, const Matrix_t &forgetGateValues, const Matrix_t &candidateValues, const Matrix_t &outputGateValues) | TMVA::DNN::RNN::TBasicLSTMLayer< 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::TBasicLSTMLayer< Architecture_t > | inline |
DoesReturnSequence() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
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 |
fCandidateBias | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fCandidateBiasGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fCandidateValue | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fCell | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fCellSize | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDepth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fDerivativesCandidate | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDerivativesForget | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDerivativesInput | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDerivativesOutput | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDescriptors | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDx | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fDy | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fF1 | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fF2 | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fForgetBiasGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fForgetGateBias | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fForgetValue | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fHeight | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInit | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInputBiasGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fInputDepth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInputGateBias | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fInputHeight | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fInputValue | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fInputWidth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fIsTraining | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
forget_gate_value | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
ForgetGate(const Matrix_t &input, Matrix_t &df) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
Forward(Tensor_t &input, bool isTraining=true) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inlinevirtual |
fOutput | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fOutputBiasGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fOutputGateBias | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fOutputValue | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fRememberState | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fReturnSequence | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fState | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fStateSize | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fTimeSteps | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightGradients | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWeightGradientsTensor | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeights | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWeightsCandidate | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsCandidateGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsCandidateState | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsCandidateStateGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsForgetGate | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsForgetGateState | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsForgetGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsForgetStateGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsInputGate | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsInputGateState | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsInputGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsInputStateGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsOutputGate | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsOutputGateState | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsOutputGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsOutputStateGradients | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWeightsTensor | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fWidth | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
fWorkspace | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fX | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
fY | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
GetActivationFunctionF1() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetActivationFunctionF2() const | TMVA::DNN::RNN::TBasicLSTMLayer< 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 |
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 |
GetCandidateBias() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateBias() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateBiasGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateBiasGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateDerivativesAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateDerivativesAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateGateTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateGateTensor() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateGateTensorAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateGateTensorAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateValue() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCandidateValue() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCell() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCell() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCellSize() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCellTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCellTensor() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCellTensorAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetCellTensorAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDepth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetDerivativesCandidate() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesCandidate() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesForget() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesForget() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesInput() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesInput() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesOutput() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDerivativesOutput() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDX() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetDY() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetExtraLayerParameters() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
GetForgetBiasGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetBiasGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetDerivativesAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetDerivativesAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateBias() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateBias() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateTensor() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateTensorAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateTensorAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateValue() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetForgetGateValue() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetHeight() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInitialization() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInputBiasGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputBiasGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputDepth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInputDerivativesAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputDerivativesAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateBias() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateBias() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateTensor() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateTensorAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateTensorAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateValue() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputGateValue() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetInputHeight() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetInputSize() const | TMVA::DNN::RNN::TBasicLSTMLayer< 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 |
GetOutputBiasGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputBiasGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputDerivativesAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputDerivativesAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateBias() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateBias() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateTensor() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateTensorAt(size_t i) const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateTensorAt(size_t i) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateValue() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetOutputGateValue() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetState() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetState() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetStateSize() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetTimeSteps() const | TMVA::DNN::RNN::TBasicLSTMLayer< 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::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightGradientsTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< 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 |
GetWeightsCandidate() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidate() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidateGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidateGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidateState() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidateState() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidateStateGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsCandidateStateGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetGate() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetGate() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetGateState() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetGateState() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsForgetStateGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputGate() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputGate() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputGateState() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputGateState() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputStateGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsInputStateGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputGate() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputGate() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputGateState() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputGateState() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputStateGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsOutputStateGradients() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsTensor() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeightsTensor() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWeigthsForgetStateGradients() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetWidth() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
GetX() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
GetY() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
HelperDescriptor_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
Initialize() | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | virtual |
InitState(DNN::EInitialization m=DNN::EInitialization::kZero) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
input_gate_value | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
InputGate(const Matrix_t &input, Matrix_t &di) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
IsTraining() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
LayerDescriptor_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
Matrix_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
output_gate_value | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | private |
OutputGate(const Matrix_t &input, Matrix_t &dout) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inline |
Print() const | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | virtual |
ReadMatrixXML(void *node, const char *name, Matrix_t &matrix) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
ReadWeightsFromXML(void *parent) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | inlinevirtual |
ResetTraining() | TMVA::DNN::VGeneralLayer< Architecture_t > | inlinevirtual |
RNNDescriptors_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
RNNWorkspace_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
Scalar_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< 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 |
TBasicLSTMLayer(size_t batchSize, size_t stateSize, size_t inputSize, size_t timeSteps, bool rememberState=false, bool returnSequence=false, DNN::EActivationFunction f1=DNN::EActivationFunction::kSigmoid, DNN::EActivationFunction f2=DNN::EActivationFunction::kTanh, bool training=true, DNN::EInitialization fA=DNN::EInitialization::kZero) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
TBasicLSTMLayer(const TBasicLSTMLayer &) | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
Tensor_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
TensorDescriptor_t typedef | TMVA::DNN::RNN::TBasicLSTMLayer< Architecture_t > | |
Update(const Scalar_t learningRate) | TMVA::DNN::RNN::TBasicLSTMLayer< 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::TBasicLSTMLayer< 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 |