Free cookie consent management tool by TermsFeed Policy Generator

source: branches/GP-MoveOperators/HeuristicLab.Algorithms.GradientDescent/3.3/LbfgsInitializer.cs @ 9921

Last change on this file since 9921 was 8473, checked in by gkronber, 12 years ago

#1902 worked on GPR: added line chart, made parameters of mean and covariance functions readable, removed target variable scaling, moved noise hyperparameter for likelihood function to the end of the parameter list, added methods to calculate the predicted variance, removed limits for scale of covariance functions and introduced exception handling to catch non-spd or singular cov matrixes, implemented rational quadratic covariance function, added unit test case from GBML book (however it does not work as the book seemingly uses a noise-less likelihood function)

File size: 4.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Linq;
24using HeuristicLab.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.RealVectorEncoding;
28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Algorithms.GradientDescent {
33  [StorableClass]
34  [Item(Name = "LBFGS Initializer", Description = "Initializes the necessary data structures for the LM-BFGS algorithm.")]
35  public sealed class LbfgsInitializer : SingleSuccessorOperator {
36    private const string PointParameterName = "Point";
37    private const string StateParameterName = "State";
38    private const string IterationsParameterName = "Iterations";
39    private const string ApproximateGradientsParameterName = "ApproximateGradients";
40
41    #region Parameter Properties
42    // in
43    public ILookupParameter<IntValue> IterationsParameter {
44      get { return (ILookupParameter<IntValue>)Parameters[IterationsParameterName]; }
45    }
46    public ILookupParameter<RealVector> PointParameter {
47      get { return (ILookupParameter<RealVector>)Parameters[PointParameterName]; }
48    }
49    // out
50    public ILookupParameter<LbfgsState> StateParameter {
51      get { return (ILookupParameter<LbfgsState>)Parameters[StateParameterName]; }
52    }
53    public ILookupParameter<BoolValue> ApproximateGradientsParameter {
54      get { return (ILookupParameter<BoolValue>)Parameters[ApproximateGradientsParameterName]; }
55    }
56
57
58    #endregion
59
60    #region Properties
61    private RealVector Point { get { return PointParameter.ActualValue; } }
62    private IntValue Iterations { get { return IterationsParameter.ActualValue; } }
63    private BoolValue ApproximateGradients { get { return ApproximateGradientsParameter.ActualValue; } }
64    #endregion
65
66    [StorableConstructor]
67    private LbfgsInitializer(bool deserializing) : base(deserializing) { }
68    private LbfgsInitializer(LbfgsInitializer original, Cloner cloner) : base(original, cloner) { }
69    public LbfgsInitializer()
70      : base() {
71      // in
72      Parameters.Add(new LookupParameter<RealVector>(PointParameterName, "The initial point for the LM-BFGS algorithm."));
73      Parameters.Add(new LookupParameter<IntValue>(IterationsParameterName, "The maximal number of iterations for the LM-BFGS algorithm."));
74      Parameters.Add(new LookupParameter<BoolValue>(ApproximateGradientsParameterName,
75                                                    "Flag that indicates if gradients should be approximated."));
76      // out
77      Parameters.Add(new LookupParameter<LbfgsState>(StateParameterName, "The state of the LM-BFGS algorithm."));
78    }
79
80    public override IDeepCloneable Clone(Cloner cloner) {
81      return new LbfgsInitializer(this, cloner);
82    }
83
84    public override IOperation Apply() {
85      double[] initialPoint = Point.ToArray();
86      int n = initialPoint.Length;
87      alglib.minlbfgs.minlbfgsstate state = new alglib.minlbfgs.minlbfgsstate();
88      if (ApproximateGradients.Value) {
89        alglib.minlbfgs.minlbfgscreatef(n, Math.Min(n, 10), initialPoint, 1E-5, state);
90      } else {
91        alglib.minlbfgs.minlbfgscreate(n, Math.Min(n, 10), initialPoint, state);
92      }
93      alglib.minlbfgs.minlbfgssetcond(state, 0.0, 0, 0, Iterations.Value);
94      alglib.minlbfgs.minlbfgssetxrep(state, true);
95
96      PointParameter.ActualValue = new RealVector(initialPoint);
97      StateParameter.ActualValue = new LbfgsState(state);
98      return base.Apply();
99    }
100  }
101}
Note: See TracBrowser for help on using the repository browser.