mlpack
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/bicubic_interpolation.hpp>
23 #include <mlpack/methods/ann/layer/bilinear_interpolation.hpp>
24 #include <mlpack/methods/ann/layer/channel_shuffle.hpp>
25 #include <mlpack/methods/ann/layer/constant.hpp>
26 #include <mlpack/methods/ann/layer/concatenate.hpp>
27 #include <mlpack/methods/ann/layer/dropout.hpp>
28 #include <mlpack/methods/ann/layer/elu.hpp>
29 #include <mlpack/methods/ann/layer/hard_tanh.hpp>
30 #include <mlpack/methods/ann/layer/group_norm.hpp>
31 #include <mlpack/methods/ann/layer/join.hpp>
32 #include <mlpack/methods/ann/layer/layer_norm.hpp>
33 #include <mlpack/methods/ann/layer/leaky_relu.hpp>
34 #include <mlpack/methods/ann/layer/c_relu.hpp>
35 #include <mlpack/methods/ann/layer/flexible_relu.hpp>
36 #include <mlpack/methods/ann/layer/linear_no_bias.hpp>
37 #include <mlpack/methods/ann/layer/linear3d.hpp>
38 #include <mlpack/methods/ann/layer/log_softmax.hpp>
39 #include <mlpack/methods/ann/layer/lookup.hpp>
40 #include <mlpack/methods/ann/layer/multihead_attention.hpp>
41 #include <mlpack/methods/ann/layer/multiply_constant.hpp>
42 #include <mlpack/methods/ann/layer/max_pooling.hpp>
43 #include <mlpack/methods/ann/layer/mean_pooling.hpp>
44 #include <mlpack/methods/ann/layer/lp_pooling.hpp>
45 #include <mlpack/methods/ann/layer/nearest_interpolation.hpp>
46 #include <mlpack/methods/ann/layer/noisylinear.hpp>
47 #include <mlpack/methods/ann/layer/adaptive_max_pooling.hpp>
48 #include <mlpack/methods/ann/layer/adaptive_mean_pooling.hpp>
49 #include <mlpack/methods/ann/layer/parametric_relu.hpp>
50 #include <mlpack/methods/ann/layer/pixel_shuffle.hpp>
51 #include <mlpack/methods/ann/layer/positional_encoding.hpp>
52 #include <mlpack/methods/ann/layer/reinforce_normal.hpp>
53 #include <mlpack/methods/ann/layer/relu6.hpp>
54 #include <mlpack/methods/ann/layer/reparametrization.hpp>
55 #include <mlpack/methods/ann/layer/select.hpp>
56 #include <mlpack/methods/ann/layer/softmax.hpp>
57 #include <mlpack/methods/ann/layer/spatial_dropout.hpp>
58 #include <mlpack/methods/ann/layer/subview.hpp>
59 #include <mlpack/methods/ann/layer/virtual_batch_norm.hpp>
60 #include <mlpack/methods/ann/layer/hardshrink.hpp>
61 #include <mlpack/methods/ann/layer/celu.hpp>
62 #include <mlpack/methods/ann/layer/isrlu.hpp>
63 #include <mlpack/methods/ann/layer/softshrink.hpp>
64 #include <mlpack/methods/ann/layer/radial_basis_function.hpp>
65 
66 // Convolution modules.
67 #include <mlpack/methods/ann/convolution_rules/border_modes.hpp>
68 #include <mlpack/methods/ann/convolution_rules/naive_convolution.hpp>
69 #include <mlpack/methods/ann/convolution_rules/fft_convolution.hpp>
70 
71 // Regularizers.
72 #include <mlpack/methods/ann/regularizer/no_regularizer.hpp>
73 
74 // Loss function modules.
75 #include <mlpack/methods/ann/loss_functions/negative_log_likelihood.hpp>
76 
77 namespace mlpack {
78 namespace ann {
79 
80 template<typename InputDataType, typename OutputDataType> class BatchNorm;
81 template<typename InputDataType, typename OutputDataType> class DropConnect;
82 template<typename InputDataType, typename OutputDataType> class Glimpse;
83 template<typename InputDataType, typename OutputDataType> class LayerNorm;
84 template<typename InputDataType, typename OutputDataType> class LSTM;
85 template<typename InputDataType, typename OutputDataType> class GRU;
86 template<typename InputDataType, typename OutputDataType> class FastLSTM;
87 template<typename InputDataType, typename OutputDataType> class VRClassReward;
88 template<typename InputDataType, typename OutputDataType> class Concatenate;
89 template<typename InputDataType, typename OutputDataType> class Padding;
90 template<typename InputDataType, typename OutputDataType> class ReLU6;
91 
92 template<typename InputDataType,
93  typename OutputDataType,
94  typename RegularizerType>
95 class Linear;
96 
97 template<typename InputDataType,
98  typename OutputDataType,
99  typename Activation>
100 class RBF;
101 
102 template<typename InputDataType,
103  typename OutputDataType,
104  typename RegularizerType>
105 class LinearNoBias;
106 
107 template<typename InputDataType,
108  typename OutputDataType>
109 class NoisyLinear;
110 
111 template<typename InputDataType,
112  typename OutputDataType,
113  typename RegularizerType>
114 class Linear3D;
115 
116 template<typename InputDataType,
117  typename OutputDataType
118 >
119 class VirtualBatchNorm;
120 
121 template<typename InputDataType,
122  typename OutputDataType
123 >
124 class MiniBatchDiscrimination;
125 
126 template <typename InputDataType,
127  typename OutputDataType,
128  typename RegularizerType>
129 class MultiheadAttention;
130 
131 template<typename InputDataType,
132  typename OutputDataType
133 >
134 class Reparametrization;
135 
136 template<typename InputDataType,
137  typename OutputDataType,
138  typename... CustomLayers
139 >
140 class AddMerge;
141 
142 template<typename InputDataType,
143  typename OutputDataType,
144  bool residual,
145  typename... CustomLayers
146 >
147 class Sequential;
148 
149 template<typename InputDataType,
150  typename OutputDataType,
151  typename... CustomLayers
152 >
153 class Highway;
154 
155 template<typename InputDataType,
156  typename OutputDataType,
157  typename... CustomLayers
158 >
159 class Recurrent;
160 
161 template<typename InputDataType,
162  typename OutputDataType,
163  typename... CustomLayers
164 >
165 class Concat;
166 
167 template<
168  typename OutputLayerType,
169  typename InputDataType,
170  typename OutputDataType
171 >
172 class ConcatPerformance;
173 
174 template<
175  typename ForwardConvolutionRule,
176  typename BackwardConvolutionRule,
177  typename GradientConvolutionRule,
178  typename InputDataType,
179  typename OutputDataType
180 >
181 class Convolution;
182 
183 template<
184  typename ForwardConvolutionRule,
185  typename BackwardConvolutionRule,
186  typename GradientConvolutionRule,
187  typename InputDataType,
188  typename OutputDataType
189 >
190 class TransposedConvolution;
191 
192 template<
193  typename ForwardConvolutionRule,
194  typename BackwardConvolutionRule,
195  typename GradientConvolutionRule,
196  typename InputDataType,
197  typename OutputDataType
198 >
199 class AtrousConvolution;
200 
201 template<
202  typename InputDataType,
203  typename OutputDataType
204 >
205 class RecurrentAttention;
206 
207 template<typename InputDataType,
208  typename OutputDataType,
209  typename... CustomLayers
210 >
211 class MultiplyMerge;
212 
213 template <typename InputDataType,
214  typename OutputDataType,
215  typename... CustomLayers
216 >
217 class WeightNorm;
218 
219 template <typename InputDataType,
220  typename OutputDataType
221 >
222 class AdaptiveMaxPooling;
223 
224 template <typename InputDataType,
225  typename OutputDataType
226 >
227 class AdaptiveMeanPooling;
228 
229 using MoreTypes = boost::variant<
230  FlexibleReLU<arma::mat, arma::mat>*,
231  Linear3D<arma::mat, arma::mat, NoRegularizer>*,
232  LpPooling<arma::mat, arma::mat>*,
233  PixelShuffle<arma::mat, arma::mat>*,
234  ChannelShuffle<arma::mat, arma::mat>*,
235  Glimpse<arma::mat, arma::mat>*,
236  Highway<arma::mat, arma::mat>*,
237  MultiheadAttention<arma::mat, arma::mat, NoRegularizer>*,
238  Recurrent<arma::mat, arma::mat>*,
239  RecurrentAttention<arma::mat, arma::mat>*,
240  ReinforceNormal<arma::mat, arma::mat>*,
241  ReLU6<arma::mat, arma::mat>*,
242  Reparametrization<arma::mat, arma::mat>*,
243  Select<arma::mat, arma::mat>*,
244  SpatialDropout<arma::mat, arma::mat>*,
245  Subview<arma::mat, arma::mat>*,
246  VRClassReward<arma::mat, arma::mat>*,
247  VirtualBatchNorm<arma::mat, arma::mat>*,
248  RBF<arma::mat, arma::mat, GaussianFunction>*,
249  BaseLayer<GaussianFunction, arma::mat, arma::mat>*,
250  PositionalEncoding<arma::mat, arma::mat>*,
251  ISRLU<arma::mat, arma::mat>*,
252  BicubicInterpolation<arma::mat, arma::mat>*,
253  NearestInterpolation<arma::mat, arma::mat>*,
254  GroupNorm<arma::mat, arma::mat>*
255 >;
256 
257 template <typename... CustomLayers>
258 using LayerTypes = boost::variant<
259  AdaptiveMaxPooling<arma::mat, arma::mat>*,
260  AdaptiveMeanPooling<arma::mat, arma::mat>*,
261  Add<arma::mat, arma::mat>*,
262  AddMerge<arma::mat, arma::mat>*,
263  AlphaDropout<arma::mat, arma::mat>*,
264  AtrousConvolution<NaiveConvolution<ValidConvolution>,
265  NaiveConvolution<FullConvolution>,
266  NaiveConvolution<ValidConvolution>,
267  arma::mat, arma::mat>*,
268  BaseLayer<LogisticFunction, arma::mat, arma::mat>*,
269  BaseLayer<IdentityFunction, arma::mat, arma::mat>*,
270  BaseLayer<TanhFunction, arma::mat, arma::mat>*,
271  BaseLayer<SoftplusFunction, arma::mat, arma::mat>*,
272  BaseLayer<RectifierFunction, arma::mat, arma::mat>*,
273  BatchNorm<arma::mat, arma::mat>*,
274  BilinearInterpolation<arma::mat, arma::mat>*,
275  CELU<arma::mat, arma::mat>*,
276  Concat<arma::mat, arma::mat>*,
277  Concatenate<arma::mat, arma::mat>*,
278  ConcatPerformance<NegativeLogLikelihood<arma::mat, arma::mat>,
279  arma::mat, arma::mat>*,
280  Constant<arma::mat, arma::mat>*,
281  Convolution<NaiveConvolution<ValidConvolution>,
282  NaiveConvolution<FullConvolution>,
283  NaiveConvolution<ValidConvolution>, arma::mat, arma::mat>*,
284  CReLU<arma::mat, arma::mat>*,
285  DropConnect<arma::mat, arma::mat>*,
286  Dropout<arma::mat, arma::mat>*,
287  ELU<arma::mat, arma::mat>*,
288  FastLSTM<arma::mat, arma::mat>*,
289  GRU<arma::mat, arma::mat>*,
290  HardTanH<arma::mat, arma::mat>*,
291  Join<arma::mat, arma::mat>*,
292  LayerNorm<arma::mat, arma::mat>*,
293  LeakyReLU<arma::mat, arma::mat>*,
294  Linear<arma::mat, arma::mat, NoRegularizer>*,
295  LinearNoBias<arma::mat, arma::mat, NoRegularizer>*,
296  LogSoftMax<arma::mat, arma::mat>*,
297  Lookup<arma::mat, arma::mat>*,
298  LSTM<arma::mat, arma::mat>*,
299  MaxPooling<arma::mat, arma::mat>*,
300  MeanPooling<arma::mat, arma::mat>*,
301  MiniBatchDiscrimination<arma::mat, arma::mat>*,
302  MultiplyConstant<arma::mat, arma::mat>*,
303  MultiplyMerge<arma::mat, arma::mat>*,
304  NegativeLogLikelihood<arma::mat, arma::mat>*,
305  NoisyLinear<arma::mat, arma::mat>*,
306  Padding<arma::mat, arma::mat>*,
307  PReLU<arma::mat, arma::mat>*,
308  Sequential<arma::mat, arma::mat, false>*,
309  Sequential<arma::mat, arma::mat, true>*,
310  Softmax<arma::mat, arma::mat>*,
311  TransposedConvolution<NaiveConvolution<ValidConvolution>,
312  NaiveConvolution<ValidConvolution>,
313  NaiveConvolution<ValidConvolution>, arma::mat, arma::mat>*,
314  WeightNorm<arma::mat, arma::mat>*,
315  MoreTypes,
316  CustomLayers*...
317 >;
318 
319 } // namespace ann
320 } // namespace mlpack
321 
322 #endif
radial_basis_function.hpp
alpha_dropout.hpp
adaptive_mean_pooling.hpp
mlpack::ann::VRClassReward
Implementation of the variance reduced classification reinforcement layer.
Definition: layer_types.hpp:87
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::ISRLU
The ISRLU activation function, defined by.
Definition: isrlu.hpp:60
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::NearestInterpolation
Definition and Implementation of the Nearest Interpolation Layer.
Definition: nearest_interpolation.hpp:34
mlpack
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: add_to_cli11.hpp:21
mlpack::ann::Padding
Implementation of the Padding module class.
Definition: layer_types.hpp:89
mlpack::ann::VirtualBatchNorm
Declaration of the VirtualBatchNorm layer class.
Definition: layer_types.hpp:119
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:190
mlpack::ann::ReinforceNormal
Implementation of the reinforce normal layer.
Definition: reinforce_normal.hpp:34
mlpack::ann::LpPooling
Implementation of the LPPooling.
Definition: lp_pooling.hpp:32
virtual_batch_norm.hpp
mlpack::ann::Linear
Implementation of the Linear layer class.
Definition: layer_types.hpp:95
hard_tanh.hpp
mlpack::ann::GroupNorm
Declaration of the Group Normalization class.
Definition: group_norm.hpp:50
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:205
mlpack::ann::Convolution
Implementation of the Convolution class.
Definition: convolution.hpp:77
multihead_attention.hpp
mlpack::ann::PositionalEncoding
Positional Encoding injects some information about the relative or absolute position of the tokens in...
Definition: positional_encoding.hpp:37
bicubic_interpolation.hpp
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:134
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:37
mlpack::ann::WeightNorm
Declaration of the WeightNorm layer class.
Definition: layer_types.hpp:217
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::MultiheadAttention
Multihead Attention allows the model to jointly attend to information from different representation s...
Definition: layer_types.hpp:129
mlpack::ann::PReLU
The PReLU activation function, defined by (where alpha is trainable)
Definition: parametric_relu.hpp:45
nearest_interpolation.hpp
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:71
mlpack::ann::PixelShuffle
Implementation of the PixelShuffle layer.
Definition: pixel_shuffle.hpp:49
mlpack::ann::Concat
Implementation of the Concat class.
Definition: concat.hpp:43
mlpack::ann::Highway
Implementation of the Highway layer.
Definition: highway.hpp:58
mlpack::ann::LSTM
Implementation of the LSTM module class.
Definition: layer_types.hpp:84
mlpack::ann::Linear3D
Implementation of the Linear3D layer class.
Definition: layer_types.hpp:114
flexible_relu.hpp
mlpack::ann::LayerNorm
Declaration of the Layer Normalization class.
Definition: layer_norm.hpp:65
mlpack::ann::Lookup
The Lookup class stores word embeddings and retrieves them using tokens.
Definition: lookup.hpp:41
mlpack::ann::NoisyLinear
Implementation of the NoisyLinear layer class.
Definition: layer_types.hpp:109
mlpack::ann::Subview
Implementation of the subview layer.
Definition: subview.hpp:34
mlpack::ann::MiniBatchDiscrimination
Implementation of the MiniBatchDiscrimination layer.
Definition: layer_types.hpp:124
mlpack::ann::MultiplyMerge
Implementation of the MultiplyMerge module class.
Definition: layer_types.hpp:211
fft_convolution.hpp
mlpack::ann::LinearNoBias
Implementation of the LinearNoBias class.
Definition: layer_types.hpp:105
positional_encoding.hpp
mlpack::ann::CReLU
A concatenated ReLU has two outputs, one ReLU and one negative ReLU, concatenated together...
Definition: c_relu.hpp:50
group_norm.hpp
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
lp_pooling.hpp
no_regularizer.hpp
naive_convolution.hpp
channel_shuffle.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
pixel_shuffle.hpp
mlpack::ann::BicubicInterpolation
Definition and Implementation of the Bicubic Interpolation Layer.
Definition: bicubic_interpolation.hpp:38
reinforce_normal.hpp
mlpack::ann::MultiplyConstant
Implementation of the multiply constant layer.
Definition: multiply_constant.hpp:34
mlpack::ann::ChannelShuffle
Definition and implementation of the Channel Shuffle Layer.
Definition: channel_shuffle.hpp:46
spatial_dropout.hpp
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::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 *... > LayerTypes
Definition: layer_types.hpp:317
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:159
mlpack::ann::Sequential
Implementation of the Sequential class.
Definition: layer_types.hpp:147
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:100
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 > *, BicubicInterpolation< arma::mat, arma::mat > *, NearestInterpolation< arma::mat, arma::mat > *, GroupNorm< arma::mat, arma::mat > *> MoreTypes
Definition: layer_types.hpp:255
adaptive_max_pooling.hpp
mlpack::ann::SpatialDropout
Implementation of the SpatialDropout layer.
Definition: spatial_dropout.hpp:48
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