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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 > , BicubicInterpolation< arma::mat, arma::mat > , NearestInterpolation< arma::mat, arma::mat > , GroupNorm< 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.

Classes

Namespaces

Typedefs

Detailed Description