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layer_types.hpp
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1 
12 #ifndef MLPACK_METHODS_ANN_LAYER_LAYER_TYPES_HPP
13 #define MLPACK_METHODS_ANN_LAYER_LAYER_TYPES_HPP
14 
15 #include <boost/variant.hpp>
16 
17 // Layer modules.
18 #include <mlpack/methods/ann/layer/add.hpp>
19 #include <mlpack/methods/ann/layer/alpha_dropout.hpp>
20 #include <mlpack/methods/ann/layer/base_layer.hpp>
21 #include <mlpack/methods/ann/layer/batch_norm.hpp>
22 #include <mlpack/methods/ann/layer/bilinear_interpolation.hpp>
23 #include <mlpack/methods/ann/layer/constant.hpp>
24 #include <mlpack/methods/ann/layer/concatenate.hpp>
25 #include <mlpack/methods/ann/layer/dropout.hpp>
26 #include <mlpack/methods/ann/layer/elu.hpp>
27 #include <mlpack/methods/ann/layer/hard_tanh.hpp>
28 #include <mlpack/methods/ann/layer/join.hpp>
29 #include <mlpack/methods/ann/layer/layer_norm.hpp>
30 #include <mlpack/methods/ann/layer/leaky_relu.hpp>
31 #include <mlpack/methods/ann/layer/c_relu.hpp>
32 #include <mlpack/methods/ann/layer/flexible_relu.hpp>
33 #include <mlpack/methods/ann/layer/linear_no_bias.hpp>
34 #include <mlpack/methods/ann/layer/log_softmax.hpp>
35 #include <mlpack/methods/ann/layer/lookup.hpp>
36 #include <mlpack/methods/ann/layer/multiply_constant.hpp>
37 #include <mlpack/methods/ann/layer/max_pooling.hpp>
38 #include <mlpack/methods/ann/layer/mean_pooling.hpp>
39 #include <mlpack/methods/ann/layer/parametric_relu.hpp>
40 #include <mlpack/methods/ann/layer/reinforce_normal.hpp>
41 #include <mlpack/methods/ann/layer/reparametrization.hpp>
42 #include <mlpack/methods/ann/layer/select.hpp>
43 #include <mlpack/methods/ann/layer/subview.hpp>
44 #include <mlpack/methods/ann/layer/virtual_batch_norm.hpp>
45 #include <mlpack/methods/ann/layer/hardshrink.hpp>
46 #include <mlpack/methods/ann/layer/celu.hpp>
47 #include <mlpack/methods/ann/layer/softshrink.hpp>
48 
49 // Convolution modules.
50 #include <mlpack/methods/ann/convolution_rules/border_modes.hpp>
51 #include <mlpack/methods/ann/convolution_rules/naive_convolution.hpp>
52 #include <mlpack/methods/ann/convolution_rules/fft_convolution.hpp>
53 
54 // Regularizers.
55 #include <mlpack/methods/ann/regularizer/no_regularizer.hpp>
56 
57 // Loss function modules.
58 #include <mlpack/methods/ann/loss_functions/negative_log_likelihood.hpp>
59 
60 namespace mlpack {
61 namespace ann {
62 
63 template<typename InputDataType, typename OutputDataType> class BatchNorm;
64 template<typename InputDataType, typename OutputDataType> class DropConnect;
65 template<typename InputDataType, typename OutputDataType> class Glimpse;
66 template<typename InputDataType, typename OutputDataType> class LayerNorm;
67 template<typename InputDataType, typename OutputDataType> class LSTM;
68 template<typename InputDataType, typename OutputDataType> class GRU;
69 template<typename InputDataType, typename OutputDataType> class FastLSTM;
70 template<typename InputDataType, typename OutputDataType> class VRClassReward;
71 template<typename InputDataType, typename OutputDataType> class Concatenate;
72 template<typename InputDataType, typename OutputDataType> class Padding;
73 
74 template<typename InputDataType,
75  typename OutputDataType,
76  typename RegularizerType>
77 class Linear;
78 
79 template<typename InputDataType,
80  typename OutputDataType,
81  typename RegularizerType>
82 class LinearNoBias;
83 
84 template<typename InputDataType,
85  typename OutputDataType
86 >
87 class VirtualBatchNorm;
88 
89 template<typename InputDataType,
90  typename OutputDataType
91 >
92 class MiniBatchDiscrimination;
93 
94 template<typename InputDataType,
95  typename OutputDataType
96 >
97 class Reparametrization;
98 
99 template<typename InputDataType,
100  typename OutputDataType,
101  typename... CustomLayers
102 >
103 class AddMerge;
104 
105 template<typename InputDataType,
106  typename OutputDataType,
107  bool residual,
108  typename... CustomLayers
109 >
110 class Sequential;
111 
112 template<typename InputDataType,
113  typename OutputDataType,
114  typename... CustomLayers
115 >
116 class Highway;
117 
118 template<typename InputDataType,
119  typename OutputDataType,
120  typename... CustomLayers
121 >
122 class Recurrent;
123 
124 template<typename InputDataType,
125  typename OutputDataType,
126  typename... CustomLayers
127 >
128 class Concat;
129 
130 template<
131  typename OutputLayerType,
132  typename InputDataType,
133  typename OutputDataType
134 >
135 class ConcatPerformance;
136 
137 template<
138  typename ForwardConvolutionRule,
139  typename BackwardConvolutionRule,
140  typename GradientConvolutionRule,
141  typename InputDataType,
142  typename OutputDataType
143 >
144 class Convolution;
145 
146 template<
147  typename ForwardConvolutionRule,
148  typename BackwardConvolutionRule,
149  typename GradientConvolutionRule,
150  typename InputDataType,
151  typename OutputDataType
152 >
153 class TransposedConvolution;
154 
155 template<
156  typename ForwardConvolutionRule,
157  typename BackwardConvolutionRule,
158  typename GradientConvolutionRule,
159  typename InputDataType,
160  typename OutputDataType
161 >
162 class AtrousConvolution;
163 
164 template<
165  typename InputDataType,
166  typename OutputDataType
167 >
168 class RecurrentAttention;
169 
170 template<typename InputDataType,
171  typename OutputDataType,
172  typename... CustomLayers
173 >
174 class MultiplyMerge;
175 
176 template <typename InputDataType,
177  typename OutputDataType,
178  typename... CustomLayers
179 >
180 class WeightNorm;
181 
182 using MoreTypes = boost::variant<
183  Recurrent<arma::mat, arma::mat>*,
184  RecurrentAttention<arma::mat, arma::mat>*,
185  ReinforceNormal<arma::mat, arma::mat>*,
186  Reparametrization<arma::mat, arma::mat>*,
187  Select<arma::mat, arma::mat>*,
188  Sequential<arma::mat, arma::mat, false>*,
189  Sequential<arma::mat, arma::mat, true>*,
190  Subview<arma::mat, arma::mat>*,
191  VRClassReward<arma::mat, arma::mat>*,
192  VirtualBatchNorm<arma::mat, arma::mat>*
193 >;
194 
195 template <typename... CustomLayers>
196 using LayerTypes = boost::variant<
197  Add<arma::mat, arma::mat>*,
198  AddMerge<arma::mat, arma::mat>*,
199  AtrousConvolution<NaiveConvolution<ValidConvolution>,
200  NaiveConvolution<FullConvolution>,
201  NaiveConvolution<ValidConvolution>,
202  arma::mat, arma::mat>*,
203  BaseLayer<LogisticFunction, arma::mat, arma::mat>*,
204  BaseLayer<IdentityFunction, arma::mat, arma::mat>*,
205  BaseLayer<TanhFunction, arma::mat, arma::mat>*,
206  BaseLayer<RectifierFunction, arma::mat, arma::mat>*,
207  BaseLayer<SoftplusFunction, arma::mat, arma::mat>*,
208  BatchNorm<arma::mat, arma::mat>*,
209  BilinearInterpolation<arma::mat, arma::mat>*,
210  Concat<arma::mat, arma::mat>*,
211  Concatenate<arma::mat, arma::mat>*,
212  ConcatPerformance<NegativeLogLikelihood<arma::mat, arma::mat>,
213  arma::mat, arma::mat>*,
214  Constant<arma::mat, arma::mat>*,
215  Convolution<NaiveConvolution<ValidConvolution>,
216  NaiveConvolution<FullConvolution>,
217  NaiveConvolution<ValidConvolution>, arma::mat, arma::mat>*,
218  TransposedConvolution<NaiveConvolution<ValidConvolution>,
219  NaiveConvolution<ValidConvolution>,
220  NaiveConvolution<ValidConvolution>, arma::mat, arma::mat>*,
221  DropConnect<arma::mat, arma::mat>*,
222  Dropout<arma::mat, arma::mat>*,
223  AlphaDropout<arma::mat, arma::mat>*,
224  ELU<arma::mat, arma::mat>*,
225  FlexibleReLU<arma::mat, arma::mat>*,
226  Glimpse<arma::mat, arma::mat>*,
227  HardTanH<arma::mat, arma::mat>*,
228  Highway<arma::mat, arma::mat>*,
229  Join<arma::mat, arma::mat>*,
230  LayerNorm<arma::mat, arma::mat>*,
231  LeakyReLU<arma::mat, arma::mat>*,
232  CReLU<arma::mat, arma::mat>*,
233  Linear<arma::mat, arma::mat, NoRegularizer>*,
234  LinearNoBias<arma::mat, arma::mat, NoRegularizer>*,
235  LogSoftMax<arma::mat, arma::mat>*,
236  Lookup<arma::mat, arma::mat>*,
237  LSTM<arma::mat, arma::mat>*,
238  GRU<arma::mat, arma::mat>*,
239  FastLSTM<arma::mat, arma::mat>*,
240  MaxPooling<arma::mat, arma::mat>*,
241  MeanPooling<arma::mat, arma::mat>*,
242  MiniBatchDiscrimination<arma::mat, arma::mat>*,
243  MultiplyConstant<arma::mat, arma::mat>*,
244  MultiplyMerge<arma::mat, arma::mat>*,
245  NegativeLogLikelihood<arma::mat, arma::mat>*,
246  Padding<arma::mat, arma::mat>*,
247  PReLU<arma::mat, arma::mat>*,
248  WeightNorm<arma::mat, arma::mat>*,
249  CELU<arma::mat, arma::mat>*,
250  MoreTypes,
251  CustomLayers*...
252 >;
253 
254 } // namespace ann
255 } // namespace mlpack
256 
257 #endif
alpha_dropout.hpp
mlpack::ann::VRClassReward
Implementation of the variance reduced classification reinforcement layer.
Definition: layer_types.hpp:70
mlpack::ann::Add
Implementation of the Add module class.
Definition: add.hpp:34
mlpack::ann::MoreTypes
boost::variant< Recurrent< arma::mat, arma::mat > *, RecurrentAttention< arma::mat, arma::mat > *, ReinforceNormal< arma::mat, arma::mat > *, Reparametrization< arma::mat, arma::mat > *, Select< arma::mat, arma::mat > *, Sequential< arma::mat, arma::mat, false > *, Sequential< arma::mat, arma::mat, true > *, Subview< arma::mat, arma::mat > *, VRClassReward< arma::mat, arma::mat > *, VirtualBatchNorm< arma::mat, arma::mat > * > MoreTypes
Definition: layer_types.hpp:193
negative_log_likelihood.hpp
mlpack::ann::Concatenate
Implementation of the Concatenate module class.
Definition: concatenate.hpp:36
log_softmax.hpp
mlpack::ann::LogSoftMax
Implementation of the log softmax layer.
Definition: log_softmax.hpp:36
mlpack::ann::AddMerge
Implementation of the AddMerge module class.
Definition: add_merge.hpp:42
multiply_constant.hpp
mlpack::ann::Padding
Implementation of the Padding module class.
Definition: layer_types.hpp:72
mlpack::ann::VirtualBatchNorm
Declaration of the VirtualBatchNorm layer class.
Definition: layer_types.hpp:87
mlpack::ann::FlexibleReLU
The FlexibleReLU activation function, defined by.
Definition: flexible_relu.hpp:59
layer_norm.hpp
mean_pooling.hpp
mlpack::ann::TransposedConvolution
Implementation of the Transposed Convolution class.
Definition: layer_types.hpp:153
mlpack::ann::ReinforceNormal
Implementation of the reinforce normal layer.
Definition: reinforce_normal.hpp:34
virtual_batch_norm.hpp
mlpack::ann::Linear
Implementation of the Linear layer class.
Definition: layer_types.hpp:77
hard_tanh.hpp
mlpack::ann::LeakyReLU
The LeakyReLU activation function, defined by.
Definition: leaky_relu.hpp:44
mlpack::ann::RecurrentAttention
This class implements the Recurrent Model for Visual Attention, using a variety of possible layer imp...
Definition: layer_types.hpp:168
mlpack::ann::Convolution
Implementation of the Convolution class.
Definition: convolution.hpp:47
mlpack::ann::MeanPooling
Implementation of the MeanPooling.
Definition: mean_pooling.hpp:33
base_layer.hpp
mlpack::ann::Reparametrization
Implementation of the Reparametrization layer class.
Definition: layer_types.hpp:97
mlpack::ann::Join
Implementation of the Join module class.
Definition: join.hpp:33
mlpack::ann::ConcatPerformance
Implementation of the concat performance class.
Definition: concat_performance.hpp:39
mlpack::ann::LayerTypes
boost::variant< Add< arma::mat, arma::mat > *, AddMerge< 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< RectifierFunction, arma::mat, arma::mat > *, BaseLayer< SoftplusFunction, arma::mat, arma::mat > *, BatchNorm< arma::mat, arma::mat > *, BilinearInterpolation< 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 > *, TransposedConvolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, DropConnect< arma::mat, arma::mat > *, Dropout< arma::mat, arma::mat > *, AlphaDropout< arma::mat, arma::mat > *, ELU< arma::mat, arma::mat > *, FlexibleReLU< arma::mat, arma::mat > *, Glimpse< arma::mat, arma::mat > *, HardTanH< arma::mat, arma::mat > *, Highway< arma::mat, arma::mat > *, Join< arma::mat, arma::mat > *, LayerNorm< arma::mat, arma::mat > *, LeakyReLU< arma::mat, arma::mat > *, CReLU< 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 > *, GRU< arma::mat, arma::mat > *, FastLSTM< 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 > *, Padding< arma::mat, arma::mat > *, PReLU< arma::mat, arma::mat > *, WeightNorm< arma::mat, arma::mat > *, CELU< arma::mat, arma::mat > *, MoreTypes, CustomLayers *... > LayerTypes
Definition: layer_types.hpp:252
mlpack::ann::WeightNorm
Declaration of the WeightNorm layer class.
Definition: layer_types.hpp:180
mlpack::ann::HardTanH
The Hard Tanh activation function, defined by.
Definition: hard_tanh.hpp:49
mlpack::ann::Select
The select module selects the specified column from a given input matrix.
Definition: select.hpp:32
mlpack::ann::NegativeLogLikelihood
Implementation of the negative log likelihood layer.
Definition: negative_log_likelihood.hpp:35
mlpack::ann::PReLU
The PReLU activation function, defined by (where alpha is trainable)
Definition: parametric_relu.hpp:45
mlpack::ann::BaseLayer
Implementation of the base layer.
Definition: base_layer.hpp:53
mlpack::ann::Concat
Implementation of the Concat class.
Definition: concat.hpp:45
mlpack::ann::Highway
Implementation of the Highway layer.
Definition: highway.hpp:60
mlpack::ann::LSTM
Implementation of the LSTM module class.
Definition: layer_types.hpp:67
flexible_relu.hpp
mlpack::ann::LayerNorm
Declaration of the Layer Normalization class.
Definition: layer_norm.hpp:65
mlpack::ann::Lookup
Implementation of the Lookup class.
Definition: lookup.hpp:35
mlpack::ann::Subview
Implementation of the subview layer.
Definition: subview.hpp:34
mlpack::ann::MiniBatchDiscrimination
Implementation of the MiniBatchDiscrimination layer.
Definition: layer_types.hpp:92
mlpack::ann::MultiplyMerge
Implementation of the MultiplyMerge module class.
Definition: layer_types.hpp:174
fft_convolution.hpp
mlpack::ann::LinearNoBias
Implementation of the LinearNoBias class.
Definition: layer_types.hpp:82
mlpack::ann::CReLU
A concatenated ReLU has two outputs, one ReLU and one negative ReLU, concatenated together...
Definition: c_relu.hpp:50
mlpack::ann::NaiveConvolution
Computes the two-dimensional convolution.
Definition: naive_convolution.hpp:35
mlpack::ann::GRU
An implementation of a gru network layer.
Definition: gru.hpp:58
mlpack::ann::Dropout
The dropout layer is a regularizer that randomly with probability &#39;ratio&#39; sets input values to zero a...
Definition: dropout.hpp:53
no_regularizer.hpp
naive_convolution.hpp
mlpack::ann::Glimpse
The glimpse layer returns a retina-like representation (down-scaled cropped images) of increasing sca...
Definition: glimpse.hpp:88
mlpack::ann::DropConnect
The DropConnect layer is a regularizer that randomly with probability ratio sets the connection value...
Definition: dropconnect.hpp:63
batch_norm.hpp
max_pooling.hpp
c_relu.hpp
reinforce_normal.hpp
mlpack::ann::MultiplyConstant
Implementation of the multiply constant layer.
Definition: multiply_constant.hpp:34
mlpack::ann::AlphaDropout
The alpha - dropout layer is a regularizer that randomly with probability &#39;ratio&#39; sets input values t...
Definition: alpha_dropout.hpp:50
mlpack::ann::CELU
The CELU activation function, defined by.
Definition: celu.hpp:60
mlpack::ann::BatchNorm
Declaration of the Batch Normalization layer class.
Definition: batch_norm.hpp:56
linear_no_bias.hpp
parametric_relu.hpp
mlpack::ann::Recurrent
Implementation of the RecurrentLayer class.
Definition: layer_types.hpp:122
mlpack::ann::Sequential
Implementation of the Sequential class.
Definition: layer_types.hpp:110
mlpack::ann::Constant
Implementation of the constant layer.
Definition: constant.hpp:34
mlpack::ann::MaxPooling
Implementation of the MaxPooling layer.
Definition: max_pooling.hpp:52
mlpack::ann::ELU
The ELU activation function, defined by.
Definition: elu.hpp:111
mlpack::ann::BilinearInterpolation
Definition and Implementation of the Bilinear Interpolation Layer.
Definition: bilinear_interpolation.hpp:39
leaky_relu.hpp
bilinear_interpolation.hpp
mlpack::ann::FastLSTM
An implementation of a faster version of the Fast LSTM network layer.
Definition: fast_lstm.hpp:66
border_modes.hpp
mlpack::ann::AtrousConvolution
Implementation of the Atrous Convolution class.
Definition: atrous_convolution.hpp:51
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