SHOGUN  4.1.0
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Modules Pages
SVRGMinimizer.h
Go to the documentation of this file.
1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2015 Wu Lin
4  * All rights reserved.
5  *
6  * Redistribution and use in source and binary forms, with or without
7  * modification, are permitted provided that the following conditions are met:
8  *
9  * 1. Redistributions of source code must retain the above copyright notice, this
10  * list of conditions and the following disclaimer.
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  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
16  * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
17  * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
18  * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
19  * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
20  * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
21  * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
22  * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
23  * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
24  * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
25  *
26  * The views and conclusions contained in the software and documentation are those
27  * of the authors and should not be interpreted as representing official policies,
28  * either expressed or implied, of the Shogun Development Team.
29  *
30  */
31 
32 #ifndef SVRGMINIMIZER_H
33 #define SVRGMINIMIZER_H
36 namespace shogun
37 {
38 
48 {
49 public:
51  SVRGMinimizer();
52 
57 
59  virtual ~SVRGMinimizer();
60 
65  virtual float64_t minimize();
66 
72  virtual void set_sgd_number_passes(int32_t sgd_passes)
73  {
74  REQUIRE(m_num_passes>0, "Must set num_passes first\n");
75  REQUIRE(sgd_passes>=0, "The number (%d) to go through data using SGD update must be positive\n",
76  sgd_passes);
77  REQUIRE(m_num_passes>sgd_passes,
78  "SVRG update is not actived because the total number (%d) to go through data",
79  " is less than the number (%d) to go through data using SGD\n",
80  m_num_passes, sgd_passes);
81  m_num_sgd_passes=sgd_passes;
82  }
83 
94  virtual void set_average_update_interval(int32_t interval)
95  {
96  REQUIRE(m_num_passes>0, "Must set num passes first\n");
97  REQUIRE(m_num_sgd_passes>=0, "Must set sgd update passes first\n");
98  REQUIRE(interval>0, "Interval (%d) must be positive\n", interval);
99  REQUIRE((m_num_passes-m_num_sgd_passes)%interval==0, "Interval is not valid\n");
100  /* if (m_num_passes-m_num_sgd_passes)%interval!=0, will affect the finaly result if we do the following operations:
101  * first do minimization, then save_to_context, and then load_from_context and finaly do minimization.
102  * If we want to get the exact result when (m_num_passes-m_num_sgd_passes)%interval!=0,
103  * we should store/restore m_average_gradient and m_previous_variable in save_to_context/load_from_context
104  */
105  m_svrg_interval=interval;
106  }
107 
108 protected:
110  virtual void init_minimization();
111 
114 
117 
120 
123 private:
125  void init();
126 };
127 
128 }
129 #endif /* SVRGMINIMIZER_H */
The class is about a stochastic cost function for stochastic average minimizers.
virtual float64_t minimize()
#define REQUIRE(x,...)
Definition: SGIO.h:206
virtual void set_average_update_interval(int32_t interval)
Definition: SVRGMinimizer.h:94
The base class for stochastic first-order gradient-based minimizers.
virtual void init_minimization()
SGVector< float64_t > m_previous_variable
double float64_t
Definition: common.h:50
SGVector< float64_t > m_average_gradient
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
virtual void set_sgd_number_passes(int32_t sgd_passes)
Definition: SVRGMinimizer.h:72
The class implements the stochastic variance reduced gradient (SVRG) minimizer.
Definition: SVRGMinimizer.h:47

SHOGUN Machine Learning Toolbox - Documentation