layer_types.hpp File Reference

#include <boost/variant.hpp>
#include <mlpack/methods/ann/layer/add.hpp>
#include <mlpack/methods/ann/layer/alpha_dropout.hpp>
#include <mlpack/methods/ann/layer/base_layer.hpp>
#include <mlpack/methods/ann/layer/batch_norm.hpp>
#include <mlpack/methods/ann/layer/bilinear_interpolation.hpp>
#include <mlpack/methods/ann/layer/channel_shuffle.hpp>
#include <mlpack/methods/ann/layer/constant.hpp>
#include <mlpack/methods/ann/layer/concatenate.hpp>
#include <mlpack/methods/ann/layer/dropout.hpp>
#include <mlpack/methods/ann/layer/elu.hpp>
#include <mlpack/methods/ann/layer/hard_tanh.hpp>
#include <mlpack/methods/ann/layer/join.hpp>
#include <mlpack/methods/ann/layer/layer_norm.hpp>
#include <mlpack/methods/ann/layer/leaky_relu.hpp>
#include <mlpack/methods/ann/layer/c_relu.hpp>
#include <mlpack/methods/ann/layer/flexible_relu.hpp>
#include <mlpack/methods/ann/layer/linear_no_bias.hpp>
#include <mlpack/methods/ann/layer/linear3d.hpp>
#include <mlpack/methods/ann/layer/log_softmax.hpp>
#include <mlpack/methods/ann/layer/lookup.hpp>
#include <mlpack/methods/ann/layer/multihead_attention.hpp>
#include <mlpack/methods/ann/layer/multiply_constant.hpp>
#include <mlpack/methods/ann/layer/max_pooling.hpp>
#include <mlpack/methods/ann/layer/mean_pooling.hpp>
#include <mlpack/methods/ann/layer/lp_pooling.hpp>
#include <mlpack/methods/ann/layer/nearest_interpolation.hpp>
#include <mlpack/methods/ann/layer/noisylinear.hpp>
#include <mlpack/methods/ann/layer/adaptive_max_pooling.hpp>
#include <mlpack/methods/ann/layer/adaptive_mean_pooling.hpp>
#include <mlpack/methods/ann/layer/parametric_relu.hpp>
#include <mlpack/methods/ann/layer/pixel_shuffle.hpp>
#include <mlpack/methods/ann/layer/positional_encoding.hpp>
#include <mlpack/methods/ann/layer/reinforce_normal.hpp>
#include <mlpack/methods/ann/layer/relu6.hpp>
#include <mlpack/methods/ann/layer/reparametrization.hpp>
#include <mlpack/methods/ann/layer/select.hpp>
#include <mlpack/methods/ann/layer/softmax.hpp>
#include <mlpack/methods/ann/layer/spatial_dropout.hpp>
#include <mlpack/methods/ann/layer/subview.hpp>
#include <mlpack/methods/ann/layer/virtual_batch_norm.hpp>
#include <mlpack/methods/ann/layer/hardshrink.hpp>
#include <mlpack/methods/ann/layer/celu.hpp>
#include <mlpack/methods/ann/layer/isrlu.hpp>
#include <mlpack/methods/ann/layer/softshrink.hpp>
#include <mlpack/methods/ann/layer/radial_basis_function.hpp>
#include <mlpack/methods/ann/convolution_rules/border_modes.hpp>
#include <mlpack/methods/ann/convolution_rules/naive_convolution.hpp>
#include <mlpack/methods/ann/convolution_rules/fft_convolution.hpp>
#include <mlpack/methods/ann/regularizer/no_regularizer.hpp>
#include <mlpack/methods/ann/loss_functions/negative_log_likelihood.hpp>

Go to the source code of this file.

Classes
class	mlpack::ann::BatchNorm< InputDataType, OutputDataType >
	Declaration of the Batch Normalization layer 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::LayerNorm< InputDataType, OutputDataType >
	Declaration of the Layer Normalization class. More...
class	mlpack::ann::LSTM< InputDataType, OutputDataType >
	Implementation of the LSTM module class. More...
class	mlpack::ann::GRU< InputDataType, OutputDataType >
	An implementation of a gru network layer. More...
class	mlpack::ann::FastLSTM< InputDataType, OutputDataType >
	An implementation of a faster version of the Fast LSTM network layer. More...
class	mlpack::ann::VRClassReward< InputDataType, OutputDataType >
	Implementation of the variance reduced classification reinforcement layer. More...
class	mlpack::ann::Concatenate< InputDataType, OutputDataType >
	Implementation of the Concatenate module class. More...
class	mlpack::ann::Padding< InputDataType, OutputDataType >
	Implementation of the Padding module class. More...
class	mlpack::ann::ReLU6< InputDataType, OutputDataType >
class	mlpack::ann::Linear< InputDataType, OutputDataType, RegularizerType >
	Implementation of the Linear layer class. More...
class	mlpack::ann::RBF< InputDataType, OutputDataType, Activation >
	Implementation of the Radial Basis Function layer. More...
class	mlpack::ann::LinearNoBias< InputDataType, OutputDataType, RegularizerType >
	Implementation of the LinearNoBias class. More...
class	mlpack::ann::NoisyLinear< InputDataType, OutputDataType >
	Implementation of the NoisyLinear layer class. More...
class	mlpack::ann::Linear3D< InputDataType, OutputDataType, RegularizerType >
	Implementation of the Linear3D layer class. More...
class	mlpack::ann::VirtualBatchNorm< InputDataType, OutputDataType >
	Declaration of the VirtualBatchNorm layer class. More...
class	mlpack::ann::MiniBatchDiscrimination< InputDataType, OutputDataType >
	Implementation of the MiniBatchDiscrimination layer. More...
class	mlpack::ann::MultiheadAttention< InputDataType, OutputDataType, RegularizerType >
	Multihead Attention allows the model to jointly attend to information from different representation subspaces at different positions. More...
class	mlpack::ann::Reparametrization< InputDataType, OutputDataType >
	Implementation of the Reparametrization layer class. More...
class	mlpack::ann::AddMerge< InputDataType, OutputDataType, CustomLayers >
	Implementation of the AddMerge module class. More...
class	mlpack::ann::Sequential< InputDataType, OutputDataType, Residual, CustomLayers >
	Implementation of the Sequential class. More...
class	mlpack::ann::Highway< InputDataType, OutputDataType, CustomLayers >
	Implementation of the Highway layer. More...
class	mlpack::ann::Recurrent< InputDataType, OutputDataType, CustomLayers >
	Implementation of the RecurrentLayer class. More...
class	mlpack::ann::Concat< InputDataType, OutputDataType, CustomLayers >
	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::TransposedConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
	Implementation of the Transposed Convolution class. More...
class	mlpack::ann::AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
	Implementation of the Atrous Convolution 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::MultiplyMerge< InputDataType, OutputDataType, CustomLayers >
	Implementation of the MultiplyMerge module class. More...
class	mlpack::ann::WeightNorm< InputDataType, OutputDataType, CustomLayers >
	Declaration of the WeightNorm layer class. More...
class	mlpack::ann::AdaptiveMaxPooling< InputDataType, OutputDataType >
	Implementation of the AdaptiveMaxPooling layer. More...
class	mlpack::ann::AdaptiveMeanPooling< InputDataType, OutputDataType >
	Implementation of the AdaptiveMeanPooling. More...

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

Typedefs
using	mlpack::ann::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 > *>
template<typename... CustomLayers>
using	mlpack::ann::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 *... >

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.