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Reference Guide
TMVA::DNN::CNN::TConvLayer< Architecture_t > Class Template Reference

template<typename Architecture_t>
class TMVA::DNN::CNN::TConvLayer< Architecture_t >

Definition at line 74 of file ConvLayer.h.

Public Types

using AlgorithmBackward_t = typename Architecture_t::AlgorithmBackward_t
 
using AlgorithmDataType_t = typename Architecture_t::AlgorithmDataType_t
 
using AlgorithmForward_t = typename Architecture_t::AlgorithmForward_t
 
using AlgorithmHelper_t = typename Architecture_t::AlgorithmHelper_t
 
using HelperDescriptor_t = typename Architecture_t::ActivationDescriptor_t
 
using LayerDescriptor_t = typename Architecture_t::ConvolutionDescriptor_t
 
using Matrix_t = typename Architecture_t::Matrix_t
 
using ReduceTensorDescriptor_t = typename Architecture_t::ReduceTensorDescriptor_t
 
using Scalar_t = typename Architecture_t::Scalar_t
 
using Tensor_t = typename Architecture_t::Tensor_t
 
using WeightsDescriptor_t = typename Architecture_t::FilterDescriptor_t
 

Public Member Functions

 TConvLayer (size_t BatchSize, size_t InputDepth, size_t InputHeight, size_t InputWidth, size_t Depth, EInitialization Init, size_t FilterHeight, size_t FilterWidth, size_t StrideRows, size_t StrideCols, size_t PaddingHeight, size_t PaddingWidth, Scalar_t DropoutProbability, EActivationFunction f, ERegularization Reg, Scalar_t WeightDecay)
 Constructor. More...
 
 TConvLayer (TConvLayer< Architecture_t > *layer)
 Copy the conv layer provided as a pointer. More...
 
 TConvLayer (const TConvLayer &)
 Copy constructor. More...
 
virtual ~TConvLayer ()
 Destructor. More...
 
virtual void AddWeightsXMLTo (void *parent)
 Writes the information and the weights about the layer in an XML node. More...
 
void Backward (Tensor_t &gradients_backward, const Tensor_t &activations_backward)
 Compute weight, bias and activation gradients. More...
 
void Forward (Tensor_t &input, bool applyDropout=false)
 Computes activation of the layer for the given input. More...
 
EActivationFunction GetActivationFunction () const
 
TDescriptorsGetDescriptors ()
 
const TDescriptorsGetDescriptors () const
 
Scalar_t GetDropoutProbability () const
 
size_t GetFilterDepth () const
 Getters. More...
 
size_t GetFilterHeight () const
 
size_t GetFilterWidth () const
 
const Tensor_tGetForwardMatrices () const
 
Tensor_tGetForwardMatrices ()
 
const Tensor_tGetInputActivation () const
 
Tensor_tGetInputActivation ()
 
Matrix_tGetInputActivationAt (size_t i)
 
const Matrix_tGetInputActivationAt (size_t i) const
 
size_t GetNLocalViewPixels () const
 
size_t GetNLocalViews () const
 
size_t GetPaddingHeight () const
 
size_t GetPaddingWidth () const
 
ERegularization GetRegularization () const
 
size_t GetStrideCols () const
 
size_t GetStrideRows () const
 
Scalar_t GetWeightDecay () const
 
TWorkspaceGetWorkspace ()
 
const TWorkspaceGetWorkspace () const
 
void Print () const
 Prints the info about the layer. More...
 
virtual void ReadWeightsFromXML (void *parent)
 Read the information and the weights about the layer from XML node. More...
 
- Public Member Functions inherited from 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)
 Constructor. More...
 
 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)
 General Constructor with different weights dimension. More...
 
 VGeneralLayer (VGeneralLayer< Architecture_t > *layer)
 Copy the layer provided as a pointer. More...
 
 VGeneralLayer (const VGeneralLayer &)
 Copy Constructor. More...
 
virtual ~VGeneralLayer ()
 Virtual Destructor. More...
 
void CopyBiases (const std::vector< Matrix_t > &otherBiases)
 Copies the biases provided as an input. More...
 
template<typename Arch >
void CopyParameters (const VGeneralLayer< Arch > &layer)
 Copy all trainable weight and biases from another equivalent layer but with different architecture The function can copy also extra parameters in addition to weights and biases if they are return by the function GetExtraLayerParameters. More...
 
void CopyWeights (const std::vector< Matrix_t > &otherWeights)
 Copies the weights provided as an input. More...
 
const Tensor_tGetActivationGradients () const
 
Tensor_tGetActivationGradients ()
 
Matrix_t GetActivationGradientsAt (size_t i)
 
const Matrix_tGetActivationGradientsAt (size_t i) const
 
size_t GetBatchSize () const
 Getters. More...
 
const std::vector< Matrix_t > & GetBiases () const
 
std::vector< Matrix_t > & GetBiases ()
 
const Matrix_tGetBiasesAt (size_t i) const
 
Matrix_tGetBiasesAt (size_t i)
 
const std::vector< Matrix_t > & GetBiasGradients () const
 
std::vector< Matrix_t > & GetBiasGradients ()
 
const Matrix_tGetBiasGradientsAt (size_t i) const
 
Matrix_tGetBiasGradientsAt (size_t i)
 
size_t GetDepth () const
 
virtual std::vector< Matrix_tGetExtraLayerParameters () const
 
size_t GetHeight () const
 
EInitialization GetInitialization () const
 
size_t GetInputDepth () const
 
size_t GetInputHeight () const
 
size_t GetInputWidth () const
 
const Tensor_tGetOutput () const
 
Tensor_tGetOutput ()
 
Matrix_t GetOutputAt (size_t i)
 
const Matrix_tGetOutputAt (size_t i) const
 
const std::vector< Matrix_t > & GetWeightGradients () const
 
std::vector< Matrix_t > & GetWeightGradients ()
 
const Matrix_tGetWeightGradientsAt (size_t i) const
 
Matrix_tGetWeightGradientsAt (size_t i)
 
const std::vector< Matrix_t > & GetWeights () const
 
std::vector< Matrix_t > & GetWeights ()
 
const Matrix_tGetWeightsAt (size_t i) const
 
Matrix_tGetWeightsAt (size_t i)
 
size_t GetWidth () const
 
virtual void Initialize ()
 Initialize the weights and biases according to the given initialization method. More...
 
bool IsTraining () const
 
void ReadMatrixXML (void *node, const char *name, Matrix_t &matrix)
 
virtual void ResetTraining ()
 Reset some training flags after a loop on all batches Some layer (e.g. More...
 
void SetBatchSize (size_t batchSize)
 Setters. More...
 
void SetDepth (size_t depth)
 
virtual void SetDropoutProbability (Scalar_t)
 Set Dropout probability. More...
 
virtual void SetExtraLayerParameters (const std::vector< Matrix_t > &)
 
void SetHeight (size_t height)
 
void SetInputDepth (size_t inputDepth)
 
void SetInputHeight (size_t inputHeight)
 
void SetInputWidth (size_t inputWidth)
 
void SetIsTraining (bool isTraining)
 
void SetWidth (size_t width)
 
void Update (const Scalar_t learningRate)
 Updates the weights and biases, given the learning rate. More...
 
void UpdateBiases (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
 Updates the biases, given the gradients and the learning rate. More...
 
void UpdateBiasGradients (const std::vector< Matrix_t > &biasGradients, const Scalar_t learningRate)
 Updates the bias gradients, given some other weight gradients and learning rate. More...
 
void UpdateWeightGradients (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
 Updates the weight gradients, given some other weight gradients and learning rate. More...
 
void UpdateWeights (const std::vector< Matrix_t > &weightGradients, const Scalar_t learningRate)
 Updates the weights, given the gradients and the learning rate,. More...
 
void WriteMatrixToXML (void *node, const char *name, const Matrix_t &matrix)
 
void WriteTensorToXML (void *node, const char *name, const std::vector< Matrix_t > &tensor)
 helper functions for XML More...
 

Static Public Member Functions

static size_t calculateDimension (size_t imgDim, size_t fltDim, size_t padding, size_t stride)
 
static size_t calculateNLocalViewPixels (size_t depth, size_t height, size_t width)
 
static size_t calculateNLocalViews (size_t inputHeight, size_t filterHeight, size_t paddingHeight, size_t strideRows, size_t inputWidth, size_t filterWidth, size_t paddingWidth, size_t strideCols)
 

Protected Attributes

TDescriptorsfDescriptors = nullptr
 Keeps the convolution, activations and filter descriptors. More...
 
Scalar_t fDropoutProbability
 Probability that an input is active. More...
 
size_t fFilterDepth
 The depth of the filter. More...
 
size_t fFilterHeight
 The height of the filter. More...
 
size_t fFilterWidth
 The width of the filter. More...
 
size_t fNLocalViewPixels
 The number of pixels in one local image view. More...
 
size_t fNLocalViews
 The number of local views in one image. More...
 
size_t fStrideCols
 The number of column pixels to slid the filter each step. More...
 
size_t fStrideRows
 The number of row pixels to slid the filter each step. More...
 
TWorkspacefWorkspace = nullptr
 
- Protected Attributes inherited from TMVA::DNN::VGeneralLayer< Architecture_t >
Tensor_t fActivationGradients
 Gradients w.r.t. the activations of this layer. More...
 
size_t fBatchSize
 Batch size used for training and evaluation. More...
 
std::vector< Matrix_tfBiases
 The biases associated to the layer. More...
 
std::vector< Matrix_tfBiasGradients
 Gradients w.r.t. the bias values of the layer. More...
 
size_t fDepth
 The depth of the layer. More...
 
size_t fHeight
 The height of the layer. More...
 
EInitialization fInit
 The initialization method. More...
 
size_t fInputDepth
 The depth of the previous layer or input. More...
 
size_t fInputHeight
 The height of the previous layer or input. More...
 
size_t fInputWidth
 The width of the previous layer or input. More...
 
bool fIsTraining
 Flag indicating the mode. More...
 
Tensor_t fOutput
 Activations of this layer. More...
 
std::vector< Matrix_tfWeightGradients
 Gradients w.r.t. the weights of the layer. More...
 
std::vector< Matrix_tfWeights
 The weights associated to the layer. More...
 
size_t fWidth
 The width of this layer. More...
 

Private Member Functions

void FreeWorkspace ()
 
void InitializeDescriptors ()
 
void InitializeWorkspace ()
 
void ReleaseDescriptors ()
 

Private Attributes

std::vector< int > fBackwardIndices
 Vector of indices used for a fast Im2Col in backward pass. More...
 
EActivationFunction fF
 Activation function of the layer. More...
 
Tensor_t fForwardTensor
 Cache tensor used for speeding-up the forward pass. More...
 
Tensor_t fInputActivation
 First output of this layer after conv, before activation. More...
 
size_t fPaddingHeight
 The number of zero layers added top and bottom of the input. More...
 
size_t fPaddingWidth
 The number of zero layers left and right of the input. More...
 
ERegularization fReg
 The regularization method. More...
 
Scalar_t fWeightDecay
 The weight decay. More...
 

#include <TMVA/DNN/CNN/ConvLayer.h>

Inheritance diagram for TMVA::DNN::CNN::TConvLayer< Architecture_t >:
[legend]

Member Typedef Documentation

◆ AlgorithmBackward_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmBackward_t = typename Architecture_t::AlgorithmBackward_t

Definition at line 85 of file ConvLayer.h.

◆ AlgorithmDataType_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmDataType_t = typename Architecture_t::AlgorithmDataType_t

Definition at line 90 of file ConvLayer.h.

◆ AlgorithmForward_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmForward_t = typename Architecture_t::AlgorithmForward_t

Definition at line 84 of file ConvLayer.h.

◆ AlgorithmHelper_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::AlgorithmHelper_t = typename Architecture_t::AlgorithmHelper_t

Definition at line 86 of file ConvLayer.h.

◆ HelperDescriptor_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::HelperDescriptor_t = typename Architecture_t::ActivationDescriptor_t

Definition at line 82 of file ConvLayer.h.

◆ LayerDescriptor_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::LayerDescriptor_t = typename Architecture_t::ConvolutionDescriptor_t

Definition at line 80 of file ConvLayer.h.

◆ Matrix_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::Matrix_t = typename Architecture_t::Matrix_t

Definition at line 77 of file ConvLayer.h.

◆ ReduceTensorDescriptor_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::ReduceTensorDescriptor_t = typename Architecture_t::ReduceTensorDescriptor_t

Definition at line 87 of file ConvLayer.h.

◆ Scalar_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::Scalar_t = typename Architecture_t::Scalar_t

Definition at line 78 of file ConvLayer.h.

◆ Tensor_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::Tensor_t = typename Architecture_t::Tensor_t

Definition at line 76 of file ConvLayer.h.

◆ WeightsDescriptor_t

template<typename Architecture_t>
using TMVA::DNN::CNN::TConvLayer< Architecture_t >::WeightsDescriptor_t = typename Architecture_t::FilterDescriptor_t

Definition at line 81 of file ConvLayer.h.

Constructor & Destructor Documentation

◆ TConvLayer() [1/3]

template<typename Architecture_t >
TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer ( size_t  BatchSize,
size_t  InputDepth,
size_t  InputHeight,
size_t  InputWidth,
size_t  Depth,
EInitialization  Init,
size_t  FilterHeight,
size_t  FilterWidth,
size_t  StrideRows,
size_t  StrideCols,
size_t  PaddingHeight,
size_t  PaddingWidth,
Scalar_t  DropoutProbability,
EActivationFunction  f,
ERegularization  Reg,
Scalar_t  WeightDecay 
)

Constructor.

Definition at line 221 of file ConvLayer.h.

◆ TConvLayer() [2/3]

template<typename Architecture_t >
TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer ( TConvLayer< Architecture_t > *  layer)

Copy the conv layer provided as a pointer.

Definition at line 256 of file ConvLayer.h.

◆ TConvLayer() [3/3]

template<typename Architecture_t >
TMVA::DNN::CNN::TConvLayer< Architecture_t >::TConvLayer ( const TConvLayer< Architecture_t > &  convLayer)

Copy constructor.

Definition at line 275 of file ConvLayer.h.

◆ ~TConvLayer()

template<typename Architecture_t >
TMVA::DNN::CNN::TConvLayer< Architecture_t >::~TConvLayer ( )
virtual

Destructor.

Definition at line 293 of file ConvLayer.h.

Member Function Documentation

◆ AddWeightsXMLTo()

template<typename Architecture_t >
void TMVA::DNN::CNN::TConvLayer< Architecture_t >::AddWeightsXMLTo ( void parent)
virtual

Writes the information and the weights about the layer in an XML node.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 368 of file ConvLayer.h.

◆ Backward()

template<typename Architecture_t >
auto TMVA::DNN::CNN::TConvLayer< Architecture_t >::Backward ( Tensor_t gradients_backward,
const Tensor_t activations_backward 
)
virtual

Compute weight, bias and activation gradients.

Uses the precomputed first partial derviatives of the activation function computed during forward propagation and modifies them. Must only be called directly at the corresponding call to Forward(...).

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 325 of file ConvLayer.h.

◆ calculateDimension()

template<typename Architecture_t >
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::calculateDimension ( size_t  imgDim,
size_t  fltDim,
size_t  padding,
size_t  stride 
)
static

Definition at line 401 of file ConvLayer.h.

◆ calculateNLocalViewPixels()

template<typename Architecture_t>
static size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::calculateNLocalViewPixels ( size_t  depth,
size_t  height,
size_t  width 
)
inlinestatic

Definition at line 96 of file ConvLayer.h.

◆ calculateNLocalViews()

template<typename Architecture_t >
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::calculateNLocalViews ( size_t  inputHeight,
size_t  filterHeight,
size_t  paddingHeight,
size_t  strideRows,
size_t  inputWidth,
size_t  filterWidth,
size_t  paddingWidth,
size_t  strideCols 
)
static

Definition at line 412 of file ConvLayer.h.

◆ Forward()

template<typename Architecture_t >
auto TMVA::DNN::CNN::TConvLayer< Architecture_t >::Forward ( Tensor_t input,
bool  applyDropout = false 
)
virtual

Computes activation of the layer for the given input.

The input must be in 3D tensor form with the different matrices corresponding to different events in the batch. Computes activations as well as the first partial derivative of the activation function at those activations.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 310 of file ConvLayer.h.

◆ FreeWorkspace()

template<typename Architecture_t >
void TMVA::DNN::CNN::TConvLayer< Architecture_t >::FreeWorkspace ( )
private

Definition at line 444 of file ConvLayer.h.

◆ GetActivationFunction()

template<typename Architecture_t>
EActivationFunction TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetActivationFunction ( ) const
inline

Definition at line 203 of file ConvLayer.h.

◆ GetDescriptors() [1/2]

template<typename Architecture_t>
TDescriptors* TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDescriptors ( )
inline

Definition at line 208 of file ConvLayer.h.

◆ GetDescriptors() [2/2]

template<typename Architecture_t>
const TDescriptors* TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDescriptors ( ) const
inline

Definition at line 209 of file ConvLayer.h.

◆ GetDropoutProbability()

template<typename Architecture_t>
Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetDropoutProbability ( ) const
inline

Definition at line 192 of file ConvLayer.h.

◆ GetFilterDepth()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterDepth ( ) const
inline

Getters.

Definition at line 179 of file ConvLayer.h.

◆ GetFilterHeight()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterHeight ( ) const
inline

Definition at line 180 of file ConvLayer.h.

◆ GetFilterWidth()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetFilterWidth ( ) const
inline

Definition at line 181 of file ConvLayer.h.

◆ GetForwardMatrices() [1/2]

template<typename Architecture_t>
const Tensor_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetForwardMatrices ( ) const
inline

Definition at line 200 of file ConvLayer.h.

◆ GetForwardMatrices() [2/2]

template<typename Architecture_t>
Tensor_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetForwardMatrices ( )
inline

Definition at line 201 of file ConvLayer.h.

◆ GetInputActivation() [1/2]

template<typename Architecture_t>
const Tensor_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivation ( ) const
inline

Definition at line 194 of file ConvLayer.h.

◆ GetInputActivation() [2/2]

template<typename Architecture_t>
Tensor_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivation ( )
inline

Definition at line 195 of file ConvLayer.h.

◆ GetInputActivationAt() [1/2]

template<typename Architecture_t>
Matrix_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivationAt ( size_t  i)
inline

Definition at line 197 of file ConvLayer.h.

◆ GetInputActivationAt() [2/2]

template<typename Architecture_t>
const Matrix_t& TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetInputActivationAt ( size_t  i) const
inline

Definition at line 198 of file ConvLayer.h.

◆ GetNLocalViewPixels()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetNLocalViewPixels ( ) const
inline

Definition at line 189 of file ConvLayer.h.

◆ GetNLocalViews()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetNLocalViews ( ) const
inline

Definition at line 190 of file ConvLayer.h.

◆ GetPaddingHeight()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetPaddingHeight ( ) const
inline

Definition at line 186 of file ConvLayer.h.

◆ GetPaddingWidth()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetPaddingWidth ( ) const
inline

Definition at line 187 of file ConvLayer.h.

◆ GetRegularization()

template<typename Architecture_t>
ERegularization TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetRegularization ( ) const
inline

Definition at line 204 of file ConvLayer.h.

◆ GetStrideCols()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetStrideCols ( ) const
inline

Definition at line 184 of file ConvLayer.h.

◆ GetStrideRows()

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetStrideRows ( ) const
inline

Definition at line 183 of file ConvLayer.h.

◆ GetWeightDecay()

template<typename Architecture_t>
Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWeightDecay ( ) const
inline

Definition at line 205 of file ConvLayer.h.

◆ GetWorkspace() [1/2]

template<typename Architecture_t>
TWorkspace* TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWorkspace ( )
inline

Definition at line 211 of file ConvLayer.h.

◆ GetWorkspace() [2/2]

template<typename Architecture_t>
const TWorkspace* TMVA::DNN::CNN::TConvLayer< Architecture_t >::GetWorkspace ( ) const
inline

Definition at line 212 of file ConvLayer.h.

◆ InitializeDescriptors()

template<typename Architecture_t >
void TMVA::DNN::CNN::TConvLayer< Architecture_t >::InitializeDescriptors ( )
private

Definition at line 424 of file ConvLayer.h.

◆ InitializeWorkspace()

template<typename Architecture_t >
void TMVA::DNN::CNN::TConvLayer< Architecture_t >::InitializeWorkspace ( )
private

Definition at line 435 of file ConvLayer.h.

◆ Print()

template<typename Architecture_t >
auto TMVA::DNN::CNN::TConvLayer< Architecture_t >::Print ( ) const
virtual

Prints the info about the layer.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 346 of file ConvLayer.h.

◆ ReadWeightsFromXML()

template<typename Architecture_t >
void TMVA::DNN::CNN::TConvLayer< Architecture_t >::ReadWeightsFromXML ( void parent)
virtual

Read the information and the weights about the layer from XML node.

Implements TMVA::DNN::VGeneralLayer< Architecture_t >.

Definition at line 392 of file ConvLayer.h.

◆ ReleaseDescriptors()

template<typename Architecture_t >
void TMVA::DNN::CNN::TConvLayer< Architecture_t >::ReleaseDescriptors ( )
private

Definition at line 429 of file ConvLayer.h.

Member Data Documentation

◆ fBackwardIndices

template<typename Architecture_t>
std::vector<int> TMVA::DNN::CNN::TConvLayer< Architecture_t >::fBackwardIndices
private

Vector of indices used for a fast Im2Col in backward pass.

Definition at line 124 of file ConvLayer.h.

◆ fDescriptors

template<typename Architecture_t>
TDescriptors* TMVA::DNN::CNN::TConvLayer< Architecture_t >::fDescriptors = nullptr
protected

Keeps the convolution, activations and filter descriptors.

Definition at line 115 of file ConvLayer.h.

◆ fDropoutProbability

template<typename Architecture_t>
Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fDropoutProbability
protected

Probability that an input is active.

Definition at line 113 of file ConvLayer.h.

◆ fF

template<typename Architecture_t>
EActivationFunction TMVA::DNN::CNN::TConvLayer< Architecture_t >::fF
private

Activation function of the layer.

Definition at line 126 of file ConvLayer.h.

◆ fFilterDepth

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterDepth
protected

The depth of the filter.

Definition at line 103 of file ConvLayer.h.

◆ fFilterHeight

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterHeight
protected

The height of the filter.

Definition at line 104 of file ConvLayer.h.

◆ fFilterWidth

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fFilterWidth
protected

The width of the filter.

Definition at line 105 of file ConvLayer.h.

◆ fForwardTensor

template<typename Architecture_t>
Tensor_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fForwardTensor
private

Cache tensor used for speeding-up the forward pass.

Definition at line 130 of file ConvLayer.h.

◆ fInputActivation

template<typename Architecture_t>
Tensor_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fInputActivation
private

First output of this layer after conv, before activation.

Definition at line 122 of file ConvLayer.h.

◆ fNLocalViewPixels

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fNLocalViewPixels
protected

The number of pixels in one local image view.

Definition at line 110 of file ConvLayer.h.

◆ fNLocalViews

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fNLocalViews
protected

The number of local views in one image.

Definition at line 111 of file ConvLayer.h.

◆ fPaddingHeight

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fPaddingHeight
private

The number of zero layers added top and bottom of the input.

Definition at line 119 of file ConvLayer.h.

◆ fPaddingWidth

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fPaddingWidth
private

The number of zero layers left and right of the input.

Definition at line 120 of file ConvLayer.h.

◆ fReg

template<typename Architecture_t>
ERegularization TMVA::DNN::CNN::TConvLayer< Architecture_t >::fReg
private

The regularization method.

Definition at line 127 of file ConvLayer.h.

◆ fStrideCols

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fStrideCols
protected

The number of column pixels to slid the filter each step.

Definition at line 108 of file ConvLayer.h.

◆ fStrideRows

template<typename Architecture_t>
size_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fStrideRows
protected

The number of row pixels to slid the filter each step.

Definition at line 107 of file ConvLayer.h.

◆ fWeightDecay

template<typename Architecture_t>
Scalar_t TMVA::DNN::CNN::TConvLayer< Architecture_t >::fWeightDecay
private

The weight decay.

Definition at line 128 of file ConvLayer.h.

◆ fWorkspace

template<typename Architecture_t>
TWorkspace* TMVA::DNN::CNN::TConvLayer< Architecture_t >::fWorkspace = nullptr
protected

Definition at line 117 of file ConvLayer.h.


The documentation for this class was generated from the following file: