SHOGUN  3.2.1
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Groups Pages
NeuralLayer.h
Go to the documentation of this file.
1 /*
2  * Copyright (c) 2014, Shogun Toolbox Foundation
3  * All rights reserved.
4  *
5  * Redistribution and use in source and binary forms, with or without
6  * modification, are permitted provided that the following conditions are met:
7 
8  * 1. Redistributions of source code must retain the above copyright notice,
9  * this list of conditions and the following disclaimer.
10  *
11  * 2. Redistributions in binary form must reproduce the above copyright notice,
12  * this list of conditions and the following disclaimer in the documentation
13  * and/or other materials provided with the distribution.
14  *
15  * 3. Neither the name of the copyright holder nor the names of its
16  * contributors may be used to endorse or promote products derived from this
17  * software without specific prior written permission.
18 
19  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
20  * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
21  * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
22  * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
23  * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
24  * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
25  * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
26  * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
27  * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
28  * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
29  * POSSIBILITY OF SUCH DAMAGE.
30  *
31  * Written (W) 2014 Khaled Nasr
32  */
33 
34 #ifndef __NEURALLAYER_H__
35 #define __NEURALLAYER_H__
36 
37 #include <shogun/lib/common.h>
38 #include <shogun/base/SGObject.h>
39 #include <shogun/lib/SGMatrix.h>
40 #include <shogun/lib/SGVector.h>
42 
43 namespace shogun
44 {
45 template <class T> class SGVector;
46 
73 class CNeuralLayer : public CSGObject
74 {
75 public:
77  CNeuralLayer();
78 
83  CNeuralLayer(int32_t num_neurons);
84 
85  virtual ~CNeuralLayer();
86 
95  virtual void initialize(CDynamicObjectArray* layers,
96  SGVector<int32_t> input_indices);
97 
105  virtual void set_batch_size(int32_t batch_size);
106 
113  virtual bool is_input() { return false; }
114 
130  SGVector<bool> parameter_regularizable,
131  float64_t sigma) { }
132 
139  virtual void compute_activations(SGMatrix<float64_t> inputs) { }
140 
150  virtual void compute_activations(SGVector<float64_t> parameters,
151  CDynamicObjectArray* layers) { }
152 
181  virtual void compute_gradients(SGVector<float64_t> parameters,
182  SGMatrix<float64_t> targets,
183  CDynamicObjectArray* layers,
184  SGVector<float64_t> parameter_gradients) { }
185 
192  virtual float64_t compute_error(SGMatrix<float64_t> targets) { return 0; }
193 
202  virtual void enforce_max_norm(SGVector<float64_t> parameters,
203  float64_t max_norm) { }
204 
213  virtual void dropout_activations();
214 
229  {
230  return 0.0;
231  }
232 
237  virtual int32_t get_num_neurons() { return m_num_neurons; }
238 
243  virtual int32_t get_num_parameters() { return m_num_parameters; }
244 
250 
257  {
258  return m_activation_gradients;
259  }
260 
267  {
268  return m_local_gradients;
269  }
270 
271  virtual const char* get_name() const { return "NeuralLayer"; }
272 
273 private:
274  void init();
275 
276 public:
281 
284 
295 
296 protected:
298  int32_t m_num_neurons;
299 
302 
305 
310 
312  int32_t m_batch_size;
313 
318 
323 
329 
335 };
336 
337 }
338 #endif
virtual float64_t compute_error(SGMatrix< float64_t > targets)
Definition: NeuralLayer.h:192
virtual void initialize(CDynamicObjectArray *layers, SGVector< int32_t > input_indices)
Definition: NeuralLayer.cpp:59
SGVector< int32_t > m_input_sizes
Definition: NeuralLayer.h:309
virtual int32_t get_num_parameters()
Definition: NeuralLayer.h:243
virtual void compute_gradients(SGVector< float64_t > parameters, SGMatrix< float64_t > targets, CDynamicObjectArray *layers, SGVector< float64_t > parameter_gradients)
Definition: NeuralLayer.h:181
virtual SGMatrix< float64_t > get_activation_gradients()
Definition: NeuralLayer.h:256
SGMatrix< float64_t > m_activations
Definition: NeuralLayer.h:317
virtual int32_t get_num_neurons()
Definition: NeuralLayer.h:237
SGVector< int32_t > m_input_indices
Definition: NeuralLayer.h:304
Base class for neural network layers.
Definition: NeuralLayer.h:73
virtual void enforce_max_norm(SGVector< float64_t > parameters, float64_t max_norm)
Definition: NeuralLayer.h:202
SGMatrix< float64_t > m_activation_gradients
Definition: NeuralLayer.h:322
virtual SGMatrix< float64_t > get_activations()
Definition: NeuralLayer.h:249
SGMatrix< float64_t > m_local_gradients
Definition: NeuralLayer.h:328
virtual const char * get_name() const
Definition: NeuralLayer.h:271
virtual SGMatrix< float64_t > get_local_gradients()
Definition: NeuralLayer.h:266
virtual void initialize_parameters(SGVector< float64_t > parameters, SGVector< bool > parameter_regularizable, float64_t sigma)
Definition: NeuralLayer.h:129
Class SGObject is the base class of all shogun objects.
Definition: SGObject.h:98
virtual float64_t compute_contraction_term(SGVector< float64_t > parameters)
Definition: NeuralLayer.h:228
double float64_t
Definition: common.h:50
virtual void compute_activations(SGVector< float64_t > parameters, CDynamicObjectArray *layers)
Definition: NeuralLayer.h:150
Dynamic array class for CSGObject pointers that creates an array that can be used like a list or an a...
virtual void dropout_activations()
Definition: NeuralLayer.cpp:88
float64_t dropout_prop
Definition: NeuralLayer.h:283
virtual void set_batch_size(int32_t batch_size)
Definition: NeuralLayer.cpp:73
virtual void compute_activations(SGMatrix< float64_t > inputs)
Definition: NeuralLayer.h:139
virtual bool is_input()
Definition: NeuralLayer.h:113
SGMatrix< bool > m_dropout_mask
Definition: NeuralLayer.h:334
float64_t contraction_coefficient
Definition: NeuralLayer.h:294

SHOGUN Machine Learning Toolbox - Documentation