| AddWeightsXMLTo(void *parent) | TMVA::DNN::TBatchNormLayer< Architecture_t > | virtual |
| Backward(Tensor_t &gradients_backward, const Tensor_t &activations_backward) | TMVA::DNN::TBatchNormLayer< Architecture_t > | virtual |
| BNormDescriptors_t typedef | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| CalculateNormDim(int axis, size_t c, size_t h, size_t w) | TMVA::DNN::TBatchNormLayer< Architecture_t > | inlineprotectedstatic |
| 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 |
| fDerivatives | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fDescriptors | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fEpsilon | TMVA::DNN::TBatchNormLayer< 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 |
| fIVar | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fMomentum | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fMu | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fMu_Training | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fNormAxis | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| Forward(Tensor_t &input, bool inTraining=true) | TMVA::DNN::TBatchNormLayer< Architecture_t > | virtual |
| fOutput | TMVA::DNN::VGeneralLayer< Architecture_t > | protected |
| fReshapedData | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fTrainedBatches | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fVar | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| fVar_Training | TMVA::DNN::TBatchNormLayer< Architecture_t > | private |
| 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 |
| GetBatchMean() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetBatchMean() | TMVA::DNN::TBatchNormLayer< 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 |
| GetEpsilon() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetExtraLayerParameters() const | TMVA::DNN::TBatchNormLayer< 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 |
| GetIVariance() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetIVariance() | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetMomentum() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetMuVector() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetMuVector() | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetNormAxis() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetNTrainedBatches() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetNTrainedBatches() | TMVA::DNN::TBatchNormLayer< 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 |
| GetReshapedData() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetReshapedData() | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetVariance() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetVariance() | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetVarVector() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | inline |
| GetVarVector() | TMVA::DNN::TBatchNormLayer< 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 |
| HelperDescriptor_t typedef | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| Initialize() | TMVA::DNN::TBatchNormLayer< Architecture_t > | virtual |
| IsTraining() const | TMVA::DNN::VGeneralLayer< Architecture_t > | inline |
| Matrix_t typedef | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| Print() const | TMVA::DNN::TBatchNormLayer< Architecture_t > | virtual |
| ReadMatrixXML(void *node, const char *name, Matrix_t &matrix) | TMVA::DNN::VGeneralLayer< Architecture_t > | |
| ReadWeightsFromXML(void *parent) | TMVA::DNN::TBatchNormLayer< Architecture_t > | virtual |
| ResetTraining() | TMVA::DNN::TBatchNormLayer< Architecture_t > | inlinevirtual |
| Scalar_t typedef | TMVA::DNN::TBatchNormLayer< 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 > ¶ms) | TMVA::DNN::TBatchNormLayer< 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 |
| TBatchNormLayer(size_t batchSize, size_t inputDepth, size_t inputHeight, size_t inputWidth, const std::vector< size_t > &shape, int axis=-1, Scalar_t momentum=-1., Scalar_t epsilon=0.0001) | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| TBatchNormLayer(TBatchNormLayer< Architecture_t > *layer) | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| TBatchNormLayer(const TBatchNormLayer &) | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| Tensor_t typedef | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| 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 > | |
| ~TBatchNormLayer() | TMVA::DNN::TBatchNormLayer< Architecture_t > | |
| ~VGeneralLayer() | TMVA::DNN::VGeneralLayer< Architecture_t > | virtual |
