layer_types.hpp File Reference
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Classes

class  AdaptiveMaxPooling< InputDataType, OutputDataType >
 Implementation of the AdaptiveMaxPooling layer. More...

 
class  AdaptiveMeanPooling< InputDataType, OutputDataType >
 Implementation of the AdaptiveMeanPooling. More...

 
class  AddMerge< InputDataType, OutputDataType, CustomLayers >
 Implementation of the AddMerge module class. More...

 
class  AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
 Implementation of the Atrous Convolution class. More...

 
class  BatchNorm< InputDataType, OutputDataType >
 Declaration of the Batch Normalization layer class. More...

 
class  Concat< InputDataType, OutputDataType, CustomLayers >
 Implementation of the Concat class. More...

 
class  Concatenate< InputDataType, OutputDataType >
 Implementation of the Concatenate module class. More...

 
class  ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >
 Implementation of the concat performance class. More...

 
class  Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
 Implementation of the Convolution class. More...

 
class  DropConnect< InputDataType, OutputDataType >
 The DropConnect layer is a regularizer that randomly with probability ratio sets the connection values to zero and scales the remaining elements by factor 1 /(1 - ratio). More...

 
class  FastLSTM< InputDataType, OutputDataType >
 An implementation of a faster version of the Fast LSTM network layer. More...

 
class  Glimpse< InputDataType, OutputDataType >
 The glimpse layer returns a retina-like representation (down-scaled cropped images) of increasing scale around a given location in a given image. More...

 
class  GRU< InputDataType, OutputDataType >
 An implementation of a gru network layer. More...

 
class  Highway< InputDataType, OutputDataType, CustomLayers >
 Implementation of the Highway layer. More...

 
class  LayerNorm< InputDataType, OutputDataType >
 Declaration of the Layer Normalization class. More...

 
class  Linear< InputDataType, OutputDataType, RegularizerType >
 Implementation of the Linear layer class. More...

 
class  Linear3D< InputDataType, OutputDataType, RegularizerType >
 Implementation of the Linear3D layer class. More...

 
class  LinearNoBias< InputDataType, OutputDataType, RegularizerType >
 Implementation of the LinearNoBias class. More...

 
class  LSTM< InputDataType, OutputDataType >
 Implementation of the LSTM module class. More...

 
class  MiniBatchDiscrimination< InputDataType, OutputDataType >
 Implementation of the MiniBatchDiscrimination layer. More...

 
class  MultiheadAttention< InputDataType, OutputDataType, RegularizerType >
 Multihead Attention allows the model to jointly attend to information from different representation subspaces at different positions. More...

 
class  MultiplyMerge< InputDataType, OutputDataType, CustomLayers >
 Implementation of the MultiplyMerge module class. More...

 
class  NoisyLinear< InputDataType, OutputDataType >
 Implementation of the NoisyLinear layer class. More...

 
class  Padding< InputDataType, OutputDataType >
 Implementation of the Padding module class. More...

 
class  RBF< InputDataType, OutputDataType, Activation >
 Implementation of the Radial Basis Function layer. More...

 
class  Recurrent< InputDataType, OutputDataType, CustomLayers >
 Implementation of the RecurrentLayer class. More...

 
class  RecurrentAttention< InputDataType, OutputDataType >
 This class implements the Recurrent Model for Visual Attention, using a variety of possible layer implementations. More...

 
class  ReLU6< InputDataType, OutputDataType >
 
class  Reparametrization< InputDataType, OutputDataType >
 Implementation of the Reparametrization layer class. More...

 
class  Sequential< InputDataType, OutputDataType, Residual, CustomLayers >
 Implementation of the Sequential class. More...

 
class  TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
 Implementation of the Transposed Convolution class. More...

 
class  VirtualBatchNorm< InputDataType, OutputDataType >
 Declaration of the VirtualBatchNorm layer class. More...

 
class  VRClassReward< InputDataType, OutputDataType >
 Implementation of the variance reduced classification reinforcement layer. More...

 
class  WeightNorm< InputDataType, OutputDataType, CustomLayers >
 Declaration of the WeightNorm layer class. More...

 

Namespaces

 mlpack
 
Linear algebra utility functions, generally performed on matrices or vectors.
 
 mlpack::ann
 
Artificial Neural Network.
 

Typedefs

template<typename... CustomLayers>
using LayerTypes = boost::variant< AdaptiveMaxPooling< arma::mat, arma::mat > *, AdaptiveMeanPooling< arma::mat, arma::mat > *, Add< arma::mat, arma::mat > *, AddMerge< arma::mat, arma::mat > *, AlphaDropout< arma::mat, arma::mat > *, AtrousConvolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< FullConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, BaseLayer< LogisticFunction, arma::mat, arma::mat > *, BaseLayer< IdentityFunction, arma::mat, arma::mat > *, BaseLayer< TanhFunction, arma::mat, arma::mat > *, BaseLayer< SoftplusFunction, arma::mat, arma::mat > *, BaseLayer< RectifierFunction, arma::mat, arma::mat > *, BatchNorm< arma::mat, arma::mat > *, BilinearInterpolation< arma::mat, arma::mat > *, CELU< arma::mat, arma::mat > *, Concat< arma::mat, arma::mat > *, Concatenate< arma::mat, arma::mat > *, ConcatPerformance< NegativeLogLikelihood< arma::mat, arma::mat >, arma::mat, arma::mat > *, Constant< arma::mat, arma::mat > *, Convolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< FullConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, CReLU< arma::mat, arma::mat > *, DropConnect< arma::mat, arma::mat > *, Dropout< arma::mat, arma::mat > *, ELU< arma::mat, arma::mat > *, FastLSTM< arma::mat, arma::mat > *, GRU< arma::mat, arma::mat > *, HardTanH< arma::mat, arma::mat > *, Join< arma::mat, arma::mat > *, LayerNorm< arma::mat, arma::mat > *, LeakyReLU< arma::mat, arma::mat > *, Linear< arma::mat, arma::mat, NoRegularizer > *, LinearNoBias< arma::mat, arma::mat, NoRegularizer > *, LogSoftMax< arma::mat, arma::mat > *, Lookup< arma::mat, arma::mat > *, LSTM< arma::mat, arma::mat > *, MaxPooling< arma::mat, arma::mat > *, MeanPooling< arma::mat, arma::mat > *, MiniBatchDiscrimination< arma::mat, arma::mat > *, MultiplyConstant< arma::mat, arma::mat > *, MultiplyMerge< arma::mat, arma::mat > *, NegativeLogLikelihood< arma::mat, arma::mat > *, NoisyLinear< arma::mat, arma::mat > *, Padding< arma::mat, arma::mat > *, PReLU< arma::mat, arma::mat > *, Sequential< arma::mat, arma::mat, false > *, Sequential< arma::mat, arma::mat, true > *, Softmax< arma::mat, arma::mat > *, TransposedConvolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, WeightNorm< arma::mat, arma::mat > *, MoreTypes, CustomLayers *... >
 
using MoreTypes = boost::variant< FlexibleReLU< arma::mat, arma::mat > *, Linear3D< arma::mat, arma::mat, NoRegularizer > *, LpPooling< arma::mat, arma::mat > *, PixelShuffle< arma::mat, arma::mat > *, ChannelShuffle< arma::mat, arma::mat > *, Glimpse< arma::mat, arma::mat > *, Highway< arma::mat, arma::mat > *, MultiheadAttention< arma::mat, arma::mat, NoRegularizer > *, Recurrent< arma::mat, arma::mat > *, RecurrentAttention< arma::mat, arma::mat > *, ReinforceNormal< arma::mat, arma::mat > *, ReLU6< arma::mat, arma::mat > *, Reparametrization< arma::mat, arma::mat > *, Select< arma::mat, arma::mat > *, SpatialDropout< arma::mat, arma::mat > *, Subview< arma::mat, arma::mat > *, VRClassReward< arma::mat, arma::mat > *, VirtualBatchNorm< arma::mat, arma::mat > *, RBF< arma::mat, arma::mat, GaussianFunction > *, BaseLayer< GaussianFunction, arma::mat, arma::mat > *, PositionalEncoding< arma::mat, arma::mat > *, ISRLU< arma::mat, arma::mat > *, NearestInterpolation< arma::mat, arma::mat > *>
 

Detailed Description

Author
Marcus Edel

This provides a list of all modules that can be used to construct a model.

mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.

Definition in file layer_types.hpp.