Logo ROOT  
Reference Guide
 
Loading...
Searching...
No Matches
TMVA::DNN::TReference< AReal > Member List

This is the complete list of members for TMVA::DNN::TReference< AReal >, including all inherited members.

AdamUpdate(TMatrixT< AReal > &A, const TMatrixT< AReal > &M, const TMatrixT< AReal > &V, AReal alpha, AReal eps)TMVA::DNN::TReference< AReal >static
AdamUpdateFirstMom(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, AReal beta)TMVA::DNN::TReference< AReal >static
AdamUpdateSecondMom(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, AReal beta)TMVA::DNN::TReference< AReal >static
AddBiases(TMatrixT< AReal > &A, const TMatrixT< AReal > &biases)TMVA::DNN::TReference< AReal >static
AddConvBiases(TMatrixT< AReal > &output, const TMatrixT< AReal > &biases)TMVA::DNN::TReference< AReal >static
AddL1RegularizationGradients(TMatrixT< AReal > &A, const TMatrixT< AReal > &W, AReal weightDecay)TMVA::DNN::TReference< AReal >static
AddL2RegularizationGradients(TMatrixT< AReal > &A, const TMatrixT< AReal > &W, AReal weightDecay)TMVA::DNN::TReference< AReal >static
AddRowWise(TMatrixT< Scalar_t > &output, const TMatrixT< Scalar_t > &biases)TMVA::DNN::TReference< AReal >static
Backward(TMatrixT< Scalar_t > &activationGradientsBackward, TMatrixT< Scalar_t > &weightGradients, TMatrixT< Scalar_t > &biasGradients, TMatrixT< Scalar_t > &df, const TMatrixT< Scalar_t > &activationGradients, const TMatrixT< Scalar_t > &weights, const TMatrixT< Scalar_t > &activationBackward)TMVA::DNN::TReference< AReal >static
ConstAdd(TMatrixT< AReal > &A, AReal beta)TMVA::DNN::TReference< AReal >static
ConstMult(TMatrixT< AReal > &A, AReal beta)TMVA::DNN::TReference< AReal >static
ConvLayerBackward(std::vector< TMatrixT< AReal > > &, TMatrixT< AReal > &, TMatrixT< AReal > &, std::vector< TMatrixT< AReal > > &, const std::vector< TMatrixT< AReal > > &, const TMatrixT< AReal > &, const std::vector< TMatrixT< AReal > > &, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t)TMVA::DNN::TReference< AReal >inlinestatic
ConvLayerForward(std::vector< TMatrixT< AReal > > &, std::vector< TMatrixT< AReal > > &, const std::vector< TMatrixT< AReal > > &, const TMatrixT< AReal > &, const TMatrixT< AReal > &, const DNN::CNN::TConvParams &, EActivationFunction, std::vector< TMatrixT< AReal > > &)TMVA::DNN::TReference< AReal >inlinestatic
Copy(TMatrixT< Scalar_t > &A, const TMatrixT< Scalar_t > &B)TMVA::DNN::TReference< AReal >static
Copy(std::vector< TMatrixT< Scalar_t > > &A, const std::vector< TMatrixT< Scalar_t > > &B)TMVA::DNN::TReference< AReal >static
CopyDiffArch(TMatrixT< Scalar_t > &A, const AMatrix_t &B)TMVA::DNN::TReference< AReal >static
CopyDiffArch(std::vector< TMatrixT< Scalar_t > > &A, const std::vector< AMatrix_t > &B)TMVA::DNN::TReference< AReal >static
CorruptInput(TMatrixT< AReal > &input, TMatrixT< AReal > &corruptedInput, AReal corruptionLevel)TMVA::DNN::TReference< AReal >static
CrossEntropy(const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights)TMVA::DNN::TReference< AReal >static
CrossEntropyGradients(TMatrixT< AReal > &dY, const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights)TMVA::DNN::TReference< AReal >static
Deflatten(std::vector< TMatrixT< AReal > > &A, const TMatrixT< Scalar_t > &B, size_t index, size_t nRows, size_t nCols)TMVA::DNN::TReference< AReal >static
Downsample(TMatrixT< AReal > &A, TMatrixT< AReal > &B, const TMatrixT< AReal > &C, size_t imgHeight, size_t imgWidth, size_t fltHeight, size_t fltWidth, size_t strideRows, size_t strideCols)TMVA::DNN::TReference< AReal >static
DropoutForward(Tensor_t &A, TDescriptors *descriptors, TWorkspace *workspace, Scalar_t p)TMVA::DNN::TReference< AReal >static
DropoutForward(Matrix_t &A, Scalar_t p)TMVA::DNN::TReference< AReal >inlinestatic
EncodeInput(TMatrixT< AReal > &input, TMatrixT< AReal > &compressedInput, TMatrixT< AReal > &Weights)TMVA::DNN::TReference< AReal >static
FastTanh(Tensor_t &B)TMVA::DNN::TReference< AReal >inlinestatic
FastTanhDerivative(Tensor_t &B, const Tensor_t &A)TMVA::DNN::TReference< AReal >inlinestatic
fgRandomGenTMVA::DNN::TReference< AReal >privatestatic
Flatten(TMatrixT< AReal > &A, const std::vector< TMatrixT< AReal > > &B, size_t size, size_t nRows, size_t nCols)TMVA::DNN::TReference< AReal >static
ForwardLogReg(TMatrixT< AReal > &input, TMatrixT< AReal > &p, TMatrixT< AReal > &fWeights)TMVA::DNN::TReference< AReal >static
Gauss(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >inlinestatic
GaussDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >inlinestatic
GetRandomGenerator()TMVA::DNN::TReference< AReal >static
GRULayerBackward(TMatrixT< Scalar_t > &state_gradients_backward, TMatrixT< Scalar_t > &reset_weight_gradients, TMatrixT< Scalar_t > &update_weight_gradients, TMatrixT< Scalar_t > &candidate_weight_gradients, TMatrixT< Scalar_t > &reset_state_weight_gradients, TMatrixT< Scalar_t > &update_state_weight_gradients, TMatrixT< Scalar_t > &candidate_state_weight_gradients, TMatrixT< Scalar_t > &reset_bias_gradients, TMatrixT< Scalar_t > &update_bias_gradients, TMatrixT< Scalar_t > &candidate_bias_gradients, TMatrixT< Scalar_t > &dr, TMatrixT< Scalar_t > &du, TMatrixT< Scalar_t > &dc, const TMatrixT< Scalar_t > &precStateActivations, const TMatrixT< Scalar_t > &fReset, const TMatrixT< Scalar_t > &fUpdate, const TMatrixT< Scalar_t > &fCandidate, const TMatrixT< Scalar_t > &weights_reset, const TMatrixT< Scalar_t > &weights_update, const TMatrixT< Scalar_t > &weights_candidate, const TMatrixT< Scalar_t > &weights_reset_state, const TMatrixT< Scalar_t > &weights_update_state, const TMatrixT< Scalar_t > &weights_candidate_state, const TMatrixT< Scalar_t > &input, TMatrixT< Scalar_t > &input_gradient)TMVA::DNN::TReference< AReal >static
Hadamard(TMatrixT< AReal > &A, const TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >static
Identity(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >static
IdentityDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
Im2col(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, size_t imgHeight, size_t imgWidth, size_t fltHeight, size_t fltWidth, size_t strideRows, size_t strideCols, size_t zeroPaddingHeight, size_t zeroPaddingWidth)TMVA::DNN::TReference< AReal >static
Im2colFast(TMatrixT< AReal > &, const TMatrixT< AReal > &, const std::vector< int > &)TMVA::DNN::TReference< AReal >inlinestatic
Im2colIndices(std::vector< int > &, const TMatrixT< AReal > &, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t, size_t)TMVA::DNN::TReference< AReal >inlinestatic
InitializeGauss(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
InitializeGlorotNormal(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
InitializeGlorotUniform(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
InitializeIdentity(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
InitializeUniform(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
InitializeZero(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
L1Regularization(const TMatrixT< AReal > &W)TMVA::DNN::TReference< AReal >static
L2Regularization(const TMatrixT< AReal > &W)TMVA::DNN::TReference< AReal >static
LSTMLayerBackward(TMatrixT< Scalar_t > &state_gradients_backward, TMatrixT< Scalar_t > &cell_gradients_backward, TMatrixT< Scalar_t > &input_weight_gradients, TMatrixT< Scalar_t > &forget_weight_gradients, TMatrixT< Scalar_t > &candidate_weight_gradients, TMatrixT< Scalar_t > &output_weight_gradients, TMatrixT< Scalar_t > &input_state_weight_gradients, TMatrixT< Scalar_t > &forget_state_weight_gradients, TMatrixT< Scalar_t > &candidate_state_weight_gradients, TMatrixT< Scalar_t > &output_state_weight_gradients, TMatrixT< Scalar_t > &input_bias_gradients, TMatrixT< Scalar_t > &forget_bias_gradients, TMatrixT< Scalar_t > &candidate_bias_gradients, TMatrixT< Scalar_t > &output_bias_gradients, TMatrixT< Scalar_t > &di, TMatrixT< Scalar_t > &df, TMatrixT< Scalar_t > &dc, TMatrixT< Scalar_t > &dout, const TMatrixT< Scalar_t > &precStateActivations, const TMatrixT< Scalar_t > &precCellActivations, const TMatrixT< Scalar_t > &fInput, const TMatrixT< Scalar_t > &fForget, const TMatrixT< Scalar_t > &fCandidate, const TMatrixT< Scalar_t > &fOutput, const TMatrixT< Scalar_t > &weights_input, const TMatrixT< Scalar_t > &weights_forget, const TMatrixT< Scalar_t > &weights_candidate, const TMatrixT< Scalar_t > &weights_output, const TMatrixT< Scalar_t > &weights_input_state, const TMatrixT< Scalar_t > &weights_forget_state, const TMatrixT< Scalar_t > &weights_candidate_state, const TMatrixT< Scalar_t > &weights_output_state, const TMatrixT< Scalar_t > &input, TMatrixT< Scalar_t > &input_gradient, TMatrixT< Scalar_t > &cell_gradient, TMatrixT< Scalar_t > &cell_tanh)TMVA::DNN::TReference< AReal >static
Matrix_t typedefTMVA::DNN::TReference< AReal >
MaxPoolLayerBackward(TMatrixT< AReal > &activationGradientsBackward, const TMatrixT< AReal > &activationGradients, const TMatrixT< AReal > &indexMatrix, size_t imgHeight, size_t imgWidth, size_t fltHeight, size_t fltWidth, size_t strideRows, size_t strideCol, size_t nLocalViews)TMVA::DNN::TReference< AReal >static
MeanSquaredError(const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights)TMVA::DNN::TReference< AReal >static
MeanSquaredErrorGradients(TMatrixT< AReal > &dY, const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights)TMVA::DNN::TReference< AReal >static
MultiplyTranspose(TMatrixT< Scalar_t > &output, const TMatrixT< Scalar_t > &input, const TMatrixT< Scalar_t > &weights)TMVA::DNN::TReference< AReal >static
PrepareInternals(std::vector< TMatrixT< AReal > > &)TMVA::DNN::TReference< AReal >inlinestatic
Rearrange(std::vector< TMatrixT< AReal > > &out, const std::vector< TMatrixT< AReal > > &in)TMVA::DNN::TReference< AReal >static
ReciprocalElementWise(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
ReconstructInput(TMatrixT< AReal > &compressedInput, TMatrixT< AReal > &reconstructedInput, TMatrixT< AReal > &fWeights)TMVA::DNN::TReference< AReal >static
RecurrentLayerBackward(TMatrixT< Scalar_t > &state_gradients_backward, TMatrixT< Scalar_t > &input_weight_gradients, TMatrixT< Scalar_t > &state_weight_gradients, TMatrixT< Scalar_t > &bias_gradients, TMatrixT< Scalar_t > &df, const TMatrixT< Scalar_t > &state, const TMatrixT< Scalar_t > &weights_input, const TMatrixT< Scalar_t > &weights_state, const TMatrixT< Scalar_t > &input, TMatrixT< Scalar_t > &input_gradient)TMVA::DNN::TReference< AReal >static
Relu(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >static
ReluDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >inlinestatic
Reshape(TMatrixT< AReal > &A, const TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >static
RotateWeights(TMatrixT< AReal > &A, const TMatrixT< AReal > &B, size_t filterDepth, size_t filterHeight, size_t filterWidth, size_t numFilters)TMVA::DNN::TReference< AReal >static
Scalar_t typedefTMVA::DNN::TReference< AReal >
ScaleAdd(TMatrixT< Scalar_t > &A, const TMatrixT< Scalar_t > &B, Scalar_t beta=1.0)TMVA::DNN::TReference< AReal >static
ScaleAdd(std::vector< TMatrixT< Scalar_t > > &A, const std::vector< TMatrixT< Scalar_t > > &B, Scalar_t beta=1.0)TMVA::DNN::TReference< AReal >static
SetRandomSeed(size_t seed)TMVA::DNN::TReference< AReal >static
Sigmoid(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >static
Sigmoid(TMatrixT< AReal > &YHat, const TMatrixT< AReal > &)TMVA::DNN::TReference< AReal >static
SigmoidDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >inlinestatic
Softmax(TMatrixT< AReal > &YHat, const TMatrixT< AReal > &)TMVA::DNN::TReference< AReal >static
SoftmaxAE(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
SoftmaxCrossEntropy(const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights)TMVA::DNN::TReference< AReal >static
SoftmaxCrossEntropyGradients(TMatrixT< AReal > &dY, const TMatrixT< AReal > &Y, const TMatrixT< AReal > &output, const TMatrixT< AReal > &weights)TMVA::DNN::TReference< AReal >static
SoftSign(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >inlinestatic
SoftSignDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >inlinestatic
SqrtElementWise(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
SquareElementWise(TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
SumColumns(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >static
SymmetricRelu(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >inlinestatic
SymmetricReluDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >inlinestatic
Tanh(TMatrixT< AReal > &B)TMVA::DNN::TReference< AReal >inlinestatic
TanhDerivative(TMatrixT< AReal > &B, const TMatrixT< AReal > &A)TMVA::DNN::TReference< AReal >inlinestatic
Tensor_t typedefTMVA::DNN::TReference< AReal >
UpdateParams(TMatrixT< AReal > &x, TMatrixT< AReal > &tildeX, TMatrixT< AReal > &y, TMatrixT< AReal > &z, TMatrixT< AReal > &fVBiases, TMatrixT< AReal > &fHBiases, TMatrixT< AReal > &fWeights, TMatrixT< AReal > &VBiasError, TMatrixT< AReal > &HBiasError, AReal learningRate, size_t fBatchSize)TMVA::DNN::TReference< AReal >static
UpdateParamsLogReg(TMatrixT< AReal > &input, TMatrixT< AReal > &output, TMatrixT< AReal > &difference, TMatrixT< AReal > &p, TMatrixT< AReal > &fWeights, TMatrixT< AReal > &fBiases, AReal learningRate, size_t fBatchSize)TMVA::DNN::TReference< AReal >static