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layer_types.hpp File Reference
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Classes

class  mlpack::ann::AddMerge< InputDataType, OutputDataType >
 Implementation of the AddMerge module class. More...
 
class  mlpack::ann::Concat< InputDataType, OutputDataType >
 Implementation of the Concat class. More...
 
class  mlpack::ann::ConcatPerformance< OutputLayerType, InputDataType, OutputDataType >
 Implementation of the concat performance class. More...
 
class  mlpack::ann::Convolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
 Implementation of the Convolution class. More...
 
class  mlpack::ann::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  mlpack::ann::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  mlpack::ann::Linear< InputDataType, OutputDataType >
 Implementation of the Linear layer class. More...
 
class  mlpack::ann::LinearNoBias< InputDataType, OutputDataType >
 Implementation of the LinearNoBias class. More...
 
class  mlpack::ann::LSTM< InputDataType, OutputDataType >
 An implementation of a lstm network layer. More...
 
class  mlpack::ann::Recurrent< InputDataType, OutputDataType >
 Implementation of the RecurrentLayer class. More...
 
class  mlpack::ann::RecurrentAttention< InputDataType, OutputDataType >
 This class implements the Recurrent Model for Visual Attention, using a variety of possible layer implementations. More...
 
class  mlpack::ann::Sequential< InputDataType, OutputDataType >
 Implementation of the Sequential class. More...
 
class  mlpack::ann::VRClassReward< InputDataType, OutputDataType >
 Implementation of the variance reduced classification reinforcement layer. More...
 

Namespaces

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

Typedefs

using mlpack::ann::LayerTypes = boost::variant< Add< arma::mat, arma::mat > *, AddMerge< arma::mat, arma::mat > *, BaseLayer< LogisticFunction, arma::mat, arma::mat > *, BaseLayer< IdentityFunction, arma::mat, arma::mat > *, BaseLayer< TanhFunction, arma::mat, arma::mat > *, BaseLayer< RectifierFunction, arma::mat, arma::mat > *, Concat< 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 > *, DropConnect< arma::mat, arma::mat > *, Dropout< arma::mat, arma::mat > *, Glimpse< arma::mat, arma::mat > *, HardTanH< arma::mat, arma::mat > *, Join< arma::mat, arma::mat > *, LeakyReLU< arma::mat, arma::mat > *, Linear< arma::mat, arma::mat > *, LinearNoBias< arma::mat, arma::mat > *, 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 > *, MeanSquaredError< arma::mat, arma::mat > *, MultiplyConstant< arma::mat, arma::mat > *, NegativeLogLikelihood< arma::mat, arma::mat > *, PReLU< arma::mat, arma::mat > *, Recurrent< arma::mat, arma::mat > *, RecurrentAttention< arma::mat, arma::mat > *, ReinforceNormal< arma::mat, arma::mat > *, Select< arma::mat, arma::mat > *, Sequential< arma::mat, arma::mat > *, VRClassReward< 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.