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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/noisylinear.hpp>
40 #include <mlpack/methods/ann/layer/adaptive_max_pooling.hpp>
41 #include <mlpack/methods/ann/layer/adaptive_mean_pooling.hpp>
42 #include <mlpack/methods/ann/layer/parametric_relu.hpp>
43 #include <mlpack/methods/ann/layer/reinforce_normal.hpp>
44 #include <mlpack/methods/ann/layer/reparametrization.hpp>
45 #include <mlpack/methods/ann/layer/select.hpp>
46 #include <mlpack/methods/ann/layer/softmax.hpp>
47 #include <mlpack/methods/ann/layer/subview.hpp>
48 #include <mlpack/methods/ann/layer/virtual_batch_norm.hpp>
49 #include <mlpack/methods/ann/layer/hardshrink.hpp>
50 #include <mlpack/methods/ann/layer/celu.hpp>
51 #include <mlpack/methods/ann/layer/softshrink.hpp>
52 #include <mlpack/methods/ann/layer/radial_basis_function.hpp>
53 
54 // Convolution modules.
55 #include <mlpack/methods/ann/convolution_rules/border_modes.hpp>
56 #include <mlpack/methods/ann/convolution_rules/naive_convolution.hpp>
57 #include <mlpack/methods/ann/convolution_rules/fft_convolution.hpp>
58 
59 // Regularizers.
60 #include <mlpack/methods/ann/regularizer/no_regularizer.hpp>
61 
62 // Loss function modules.
63 #include <mlpack/methods/ann/loss_functions/negative_log_likelihood.hpp>
64 
65 namespace mlpack {
66 namespace ann {
67 
68 template<typename InputDataType, typename OutputDataType> class BatchNorm;
69 template<typename InputDataType, typename OutputDataType> class DropConnect;
70 template<typename InputDataType, typename OutputDataType> class Glimpse;
71 template<typename InputDataType, typename OutputDataType> class LayerNorm;
72 template<typename InputDataType, typename OutputDataType> class LSTM;
73 template<typename InputDataType, typename OutputDataType> class GRU;
74 template<typename InputDataType, typename OutputDataType> class FastLSTM;
75 template<typename InputDataType, typename OutputDataType> class VRClassReward;
76 template<typename InputDataType, typename OutputDataType> class Concatenate;
77 template<typename InputDataType, typename OutputDataType> class Padding;
78 
79 template<typename InputDataType,
80  typename OutputDataType,
81  typename RegularizerType>
82 class Linear;
83 
84 template<typename InputDataType,
85  typename OutputDataType,
86  typename Activation>
87 class RBF;
88 
89 template<typename InputDataType,
90  typename OutputDataType,
91  typename RegularizerType>
92 class LinearNoBias;
93 
94 template<typename InputDataType,
95  typename OutputDataType>
96 class NoisyLinear;
97 
98 template<typename InputDataType,
99  typename OutputDataType
100 >
101 class VirtualBatchNorm;
102 
103 template<typename InputDataType,
104  typename OutputDataType
105 >
106 class MiniBatchDiscrimination;
107 
108 template<typename InputDataType,
109  typename OutputDataType
110 >
111 class Reparametrization;
112 
113 template<typename InputDataType,
114  typename OutputDataType,
115  typename... CustomLayers
116 >
117 class AddMerge;
118 
119 template<typename InputDataType,
120  typename OutputDataType,
121  bool residual,
122  typename... CustomLayers
123 >
124 class Sequential;
125 
126 template<typename InputDataType,
127  typename OutputDataType,
128  typename... CustomLayers
129 >
130 class Highway;
131 
132 template<typename InputDataType,
133  typename OutputDataType,
134  typename... CustomLayers
135 >
136 class Recurrent;
137 
138 template<typename InputDataType,
139  typename OutputDataType,
140  typename... CustomLayers
141 >
142 class Concat;
143 
144 template<
145  typename OutputLayerType,
146  typename InputDataType,
147  typename OutputDataType
148 >
149 class ConcatPerformance;
150 
151 template<
152  typename ForwardConvolutionRule,
153  typename BackwardConvolutionRule,
154  typename GradientConvolutionRule,
155  typename InputDataType,
156  typename OutputDataType
157 >
158 class Convolution;
159 
160 template<
161  typename ForwardConvolutionRule,
162  typename BackwardConvolutionRule,
163  typename GradientConvolutionRule,
164  typename InputDataType,
165  typename OutputDataType
166 >
167 class TransposedConvolution;
168 
169 template<
170  typename ForwardConvolutionRule,
171  typename BackwardConvolutionRule,
172  typename GradientConvolutionRule,
173  typename InputDataType,
174  typename OutputDataType
175 >
176 class AtrousConvolution;
177 
178 template<
179  typename InputDataType,
180  typename OutputDataType
181 >
182 class RecurrentAttention;
183 
184 template<typename InputDataType,
185  typename OutputDataType,
186  typename... CustomLayers
187 >
188 class MultiplyMerge;
189 
190 template <typename InputDataType,
191  typename OutputDataType,
192  typename... CustomLayers
193 >
194 class WeightNorm;
195 
196 template <typename InputDataType,
197  typename OutputDataType
198 >
199 class AdaptiveMaxPooling;
200 
201 template <typename InputDataType,
202  typename OutputDataType
203 >
204 class AdaptiveMeanPooling;
205 
206 using MoreTypes = boost::variant<
207  Glimpse<arma::mat, arma::mat>*,
208  Highway<arma::mat, arma::mat>*,
209  Recurrent<arma::mat, arma::mat>*,
210  RecurrentAttention<arma::mat, arma::mat>*,
211  ReinforceNormal<arma::mat, arma::mat>*,
212  Reparametrization<arma::mat, arma::mat>*,
213  Select<arma::mat, arma::mat>*,
214  Sequential<arma::mat, arma::mat, false>*,
215  Sequential<arma::mat, arma::mat, true>*,
216  Subview<arma::mat, arma::mat>*,
217  VRClassReward<arma::mat, arma::mat>*,
218  VirtualBatchNorm<arma::mat, arma::mat>*,
219  RBF<arma::mat, arma::mat, GaussianFunction>*,
220  BaseLayer<GaussianFunction, arma::mat, arma::mat>*
221 >;
222 
223 template <typename... CustomLayers>
224 using LayerTypes = boost::variant<
225  AdaptiveMaxPooling<arma::mat, arma::mat>*,
226  AdaptiveMeanPooling<arma::mat, arma::mat>*,
227  Add<arma::mat, arma::mat>*,
228  AddMerge<arma::mat, arma::mat>*,
229  AlphaDropout<arma::mat, arma::mat>*,
230  AtrousConvolution<NaiveConvolution<ValidConvolution>,
231  NaiveConvolution<FullConvolution>,
232  NaiveConvolution<ValidConvolution>,
233  arma::mat, arma::mat>*,
234  BaseLayer<LogisticFunction, arma::mat, arma::mat>*,
235  BaseLayer<IdentityFunction, arma::mat, arma::mat>*,
236  BaseLayer<TanhFunction, arma::mat, arma::mat>*,
237  BaseLayer<SoftplusFunction, arma::mat, arma::mat>*,
238  BaseLayer<RectifierFunction, arma::mat, arma::mat>*,
239  BatchNorm<arma::mat, arma::mat>*,
240  BilinearInterpolation<arma::mat, arma::mat>*,
241  CELU<arma::mat, arma::mat>*,
242  Concat<arma::mat, arma::mat>*,
243  Concatenate<arma::mat, arma::mat>*,
244  ConcatPerformance<NegativeLogLikelihood<arma::mat, arma::mat>,
245  arma::mat, arma::mat>*,
246  Constant<arma::mat, arma::mat>*,
247  Convolution<NaiveConvolution<ValidConvolution>,
248  NaiveConvolution<FullConvolution>,
249  NaiveConvolution<ValidConvolution>, arma::mat, arma::mat>*,
250  CReLU<arma::mat, arma::mat>*,
251  DropConnect<arma::mat, arma::mat>*,
252  Dropout<arma::mat, arma::mat>*,
253  ELU<arma::mat, arma::mat>*,
254  FastLSTM<arma::mat, arma::mat>*,
255  FlexibleReLU<arma::mat, arma::mat>*,
256  GRU<arma::mat, arma::mat>*,
257  HardTanH<arma::mat, arma::mat>*,
258  Join<arma::mat, arma::mat>*,
259  LayerNorm<arma::mat, arma::mat>*,
260  LeakyReLU<arma::mat, arma::mat>*,
261  Linear<arma::mat, arma::mat, NoRegularizer>*,
262  LinearNoBias<arma::mat, arma::mat, NoRegularizer>*,
263  LogSoftMax<arma::mat, arma::mat>*,
264  Lookup<arma::mat, arma::mat>*,
265  LSTM<arma::mat, arma::mat>*,
266  MaxPooling<arma::mat, arma::mat>*,
267  MeanPooling<arma::mat, arma::mat>*,
268  MiniBatchDiscrimination<arma::mat, arma::mat>*,
269  MultiplyConstant<arma::mat, arma::mat>*,
270  MultiplyMerge<arma::mat, arma::mat>*,
271  NegativeLogLikelihood<arma::mat, arma::mat>*,
272  NoisyLinear<arma::mat, arma::mat>*,
273  Padding<arma::mat, arma::mat>*,
274  PReLU<arma::mat, arma::mat>*,
275  Softmax<arma::mat, arma::mat>*,
276  TransposedConvolution<NaiveConvolution<ValidConvolution>,
277  NaiveConvolution<ValidConvolution>,
278  NaiveConvolution<ValidConvolution>, arma::mat, arma::mat>*,
279  WeightNorm<arma::mat, arma::mat>*,
280  MoreTypes,
281  CustomLayers*...
282 >;
283 
284 } // namespace ann
285 } // namespace mlpack
286 
287 #endif
radial_basis_function.hpp
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 > *, FlexibleReLU< 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 > *, Softmax< arma::mat, arma::mat > *, TransposedConvolution< NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, NaiveConvolution< ValidConvolution >, arma::mat, arma::mat > *, WeightNorm< arma::mat, arma::mat > *, MoreTypes, CustomLayers *... > LayerTypes
Definition: layer_types.hpp:282
alpha_dropout.hpp
adaptive_mean_pooling.hpp
mlpack::ann::VRClassReward
Implementation of the variance reduced classification reinforcement layer.
Definition: layer_types.hpp:75
mlpack::ann::Add
Implementation of the Add module class.
Definition: add.hpp:34
mlpack::ann::AdaptiveMaxPooling
Implementation of the AdaptiveMaxPooling layer.
Definition: adaptive_max_pooling.hpp:33
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:77
mlpack::ann::VirtualBatchNorm
Declaration of the VirtualBatchNorm layer class.
Definition: layer_types.hpp:101
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:167
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:82
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:182
mlpack::ann::Convolution
Implementation of the Convolution class.
Definition: convolution.hpp:48
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:111
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::WeightNorm
Declaration of the WeightNorm layer class.
Definition: layer_types.hpp:194
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::Softmax
Implementation of the Softmax layer.
Definition: softmax.hpp:38
mlpack::ann::PReLU
The PReLU activation function, defined by (where alpha is trainable)
Definition: parametric_relu.hpp:45
mlpack::ann::AdaptiveMeanPooling
Implementation of the AdaptiveMeanPooling.
Definition: adaptive_mean_pooling.hpp:34
mlpack::ann::BaseLayer
Implementation of the base layer.
Definition: base_layer.hpp:65
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:72
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::NoisyLinear
Implementation of the NoisyLinear layer class.
Definition: layer_types.hpp:96
mlpack::ann::Subview
Implementation of the subview layer.
Definition: subview.hpp:34
mlpack::ann::MiniBatchDiscrimination
Implementation of the MiniBatchDiscrimination layer.
Definition: layer_types.hpp:106
mlpack::ann::MultiplyMerge
Implementation of the MultiplyMerge module class.
Definition: layer_types.hpp:188
mlpack::ann::MoreTypes
boost::variant< Glimpse< arma::mat, arma::mat > *, Highway< arma::mat, arma::mat > *, 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 > *, RBF< arma::mat, arma::mat, GaussianFunction > *, BaseLayer< GaussianFunction, arma::mat, arma::mat > * > MoreTypes
Definition: layer_types.hpp:221
fft_convolution.hpp
mlpack::ann::LinearNoBias
Implementation of the LinearNoBias class.
Definition: layer_types.hpp:92
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:136
mlpack::ann::Sequential
Implementation of the Sequential class.
Definition: layer_types.hpp:124
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::RBF
Implementation of the Radial Basis Function layer.
Definition: layer_types.hpp:87
adaptive_max_pooling.hpp
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:52
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