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source: stable/HeuristicLab.Algorithms.GeneticAlgorithm/3.3/IslandGeneticAlgorithmMainLoop.cs @ 17181

Last change on this file since 17181 was 17181, checked in by swagner, 5 years ago

#2875: Merged r17180 from trunk to stable

File size: 22.7 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Operators;
26using HeuristicLab.Optimization;
27using HeuristicLab.Optimization.Operators;
28using HeuristicLab.Parameters;
29using HEAL.Attic;
30using HeuristicLab.Selection;
31
32namespace HeuristicLab.Algorithms.GeneticAlgorithm {
33  /// <summary>
34  /// An island genetic algorithm main loop operator.
35  /// </summary>
36  [Item("IslandGeneticAlgorithmMainLoop", "An island genetic algorithm main loop operator.")]
37  [StorableType("E015F135-AA23-4425-A84A-DEF880185D0A")]
38  public sealed class IslandGeneticAlgorithmMainLoop : AlgorithmOperator {
39    #region Parameter Properties
40    public ValueLookupParameter<IRandom> RandomParameter {
41      get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
42    }
43    public ValueLookupParameter<BoolValue> MaximizationParameter {
44      get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
45    }
46    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
47      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
48    }
49    public ValueLookupParameter<DoubleValue> BestKnownQualityParameter {
50      get { return (ValueLookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
51    }
52    public ValueLookupParameter<IntValue> NumberOfIslandsParameter {
53      get { return (ValueLookupParameter<IntValue>)Parameters["NumberOfIslands"]; }
54    }
55    public ValueLookupParameter<IntValue> MigrationIntervalParameter {
56      get { return (ValueLookupParameter<IntValue>)Parameters["MigrationInterval"]; }
57    }
58    public ValueLookupParameter<PercentValue> MigrationRateParameter {
59      get { return (ValueLookupParameter<PercentValue>)Parameters["MigrationRate"]; }
60    }
61    public ValueLookupParameter<IOperator> MigratorParameter {
62      get { return (ValueLookupParameter<IOperator>)Parameters["Migrator"]; }
63    }
64    public ValueLookupParameter<IOperator> EmigrantsSelectorParameter {
65      get { return (ValueLookupParameter<IOperator>)Parameters["EmigrantsSelector"]; }
66    }
67    public ValueLookupParameter<IOperator> ImmigrationReplacerParameter {
68      get { return (ValueLookupParameter<IOperator>)Parameters["ImmigrationReplacer"]; }
69    }
70    public ValueLookupParameter<IntValue> PopulationSizeParameter {
71      get { return (ValueLookupParameter<IntValue>)Parameters["PopulationSize"]; }
72    }
73    public ValueLookupParameter<IntValue> MaximumGenerationsParameter {
74      get { return (ValueLookupParameter<IntValue>)Parameters["MaximumGenerations"]; }
75    }
76    public ValueLookupParameter<IOperator> SelectorParameter {
77      get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
78    }
79    public ValueLookupParameter<IOperator> CrossoverParameter {
80      get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
81    }
82    public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
83      get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
84    }
85    public ValueLookupParameter<IOperator> MutatorParameter {
86      get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
87    }
88    public ValueLookupParameter<IOperator> EvaluatorParameter {
89      get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
90    }
91    public ValueLookupParameter<IntValue> ElitesParameter {
92      get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
93    }
94    public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
95      get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
96    }
97    public ValueLookupParameter<ResultCollection> ResultsParameter {
98      get { return (ValueLookupParameter<ResultCollection>)Parameters["Results"]; }
99    }
100    public ValueLookupParameter<IOperator> AnalyzerParameter {
101      get { return (ValueLookupParameter<IOperator>)Parameters["Analyzer"]; }
102    }
103    public ValueLookupParameter<IOperator> IslandAnalyzerParameter {
104      get { return (ValueLookupParameter<IOperator>)Parameters["IslandAnalyzer"]; }
105    }
106    public LookupParameter<IntValue> EvaluatedSolutionsParameter {
107      get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
108    }
109    public LookupParameter<IntValue> IslandGenerations {
110      get { return (LookupParameter<IntValue>)Parameters["IslandGenerations"]; }
111    }
112    public LookupParameter<IntValue> IslandEvaluatedSolutions {
113      get { return (LookupParameter<IntValue>)Parameters["IslandEvaluatedSolutions"]; }
114    }
115    public ValueLookupParameter<BoolValue> Migrate {
116      get { return (ValueLookupParameter<BoolValue>)Parameters["Migrate"]; }
117    }
118    #endregion
119
120    [StorableConstructor]
121    private IslandGeneticAlgorithmMainLoop(StorableConstructorFlag _) : base(_) { }
122    private IslandGeneticAlgorithmMainLoop(IslandGeneticAlgorithmMainLoop original, Cloner cloner)
123      : base(original, cloner) {
124    }
125    public override IDeepCloneable Clone(Cloner cloner) {
126      return new IslandGeneticAlgorithmMainLoop(this, cloner);
127    }
128    public IslandGeneticAlgorithmMainLoop()
129      : base() {
130      #region Create parameters
131      Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
132      Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
133      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
134      Parameters.Add(new ValueLookupParameter<DoubleValue>("BestKnownQuality", "The best known quality value found so far."));
135      Parameters.Add(new ValueLookupParameter<IntValue>("NumberOfIslands", "The number of islands."));
136      Parameters.Add(new ValueLookupParameter<IntValue>("MigrationInterval", "The number of generations that should pass between migration phases."));
137      Parameters.Add(new ValueLookupParameter<PercentValue>("MigrationRate", "The proportion of individuals that should migrate between the islands."));
138      Parameters.Add(new ValueLookupParameter<IOperator>("Migrator", "The migration strategy."));
139      Parameters.Add(new ValueLookupParameter<IOperator>("EmigrantsSelector", "Selects the individuals that will be migrated."));
140      Parameters.Add(new ValueLookupParameter<IOperator>("ImmigrationReplacer", "Replaces some of the original population with the immigrants."));
141      Parameters.Add(new ValueLookupParameter<IntValue>("PopulationSize", "The size of the population of solutions."));
142      Parameters.Add(new ValueLookupParameter<IntValue>("MaximumGenerations", "The maximum number of generations that the algorithm should process."));
143      Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
144      Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
145      Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
146      Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
147      Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions."));
148      Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
149      Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
150      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The results collection to store the results."));
151      Parameters.Add(new ValueLookupParameter<IOperator>("Analyzer", "The operator used to the analyze the islands."));
152      Parameters.Add(new ValueLookupParameter<IOperator>("IslandAnalyzer", "The operator used to analyze each island."));
153      Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of times a solution has been evaluated."));
154      Parameters.Add(new LookupParameter<IntValue>("IslandGenerations", "The number of generations calculated on one island."));
155      Parameters.Add(new LookupParameter<IntValue>("IslandEvaluatedSolutions", "The number of times a solution has been evaluated on one island."));
156      Parameters.Add(new ValueLookupParameter<BoolValue>("Migrate", "Migrate the island?"));
157      #endregion
158
159      #region Create operators
160      VariableCreator variableCreator = new VariableCreator();
161      UniformSubScopesProcessor uniformSubScopesProcessor0 = new UniformSubScopesProcessor();
162      VariableCreator islandVariableCreator = new VariableCreator();
163      Placeholder islandAnalyzer1 = new Placeholder();
164      LocalRandomCreator localRandomCreator = new LocalRandomCreator();
165      Placeholder analyzer1 = new Placeholder();
166      ResultsCollector resultsCollector1 = new ResultsCollector();
167      UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
168      Assigner generationsAssigner = new Assigner();
169      Assigner evaluatedSolutionsAssigner = new Assigner();
170      Placeholder selector = new Placeholder();
171      SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
172      ChildrenCreator childrenCreator = new ChildrenCreator();
173      UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
174      Placeholder crossover = new Placeholder();
175      StochasticBranch stochasticBranch = new StochasticBranch();
176      Placeholder mutator = new Placeholder();
177      SubScopesRemover subScopesRemover = new SubScopesRemover();
178      UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
179      Placeholder evaluator = new Placeholder();
180      SubScopesCounter subScopesCounter = new SubScopesCounter();
181      SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
182      BestSelector bestSelector = new BestSelector();
183      RightReducer rightReducer = new RightReducer();
184      MergingReducer mergingReducer = new MergingReducer();
185      IntCounter islandGenerationsCounter = new IntCounter();
186      Comparator checkIslandGenerationsReachedMaximum = new Comparator();
187      ConditionalBranch checkContinueEvolution = new ConditionalBranch();
188      DataReducer generationsReducer = new DataReducer();
189      DataReducer evaluatedSolutionsReducer = new DataReducer();
190      Placeholder islandAnalyzer2 = new Placeholder();
191      UniformSubScopesProcessor uniformSubScopesProcessor5 = new UniformSubScopesProcessor();
192      Placeholder emigrantsSelector = new Placeholder();
193      IntCounter migrationsCounter = new IntCounter();
194      Placeholder migrator = new Placeholder();
195      UniformSubScopesProcessor uniformSubScopesProcessor6 = new UniformSubScopesProcessor();
196      Placeholder immigrationReplacer = new Placeholder();
197      Comparator generationsComparator = new Comparator();
198      Placeholder analyzer2 = new Placeholder();
199      ConditionalBranch generationsTerminationCondition = new ConditionalBranch();
200      ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
201
202
203      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Migrations", new IntValue(0)));
204      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("GenerationsSinceLastMigration", new IntValue(0)));
205      variableCreator.CollectedValues.Add(new ValueParameter<IntValue>("Generations", new IntValue(0))); // Class IslandGeneticAlgorithm expects this to be called Generations
206
207      islandVariableCreator.CollectedValues.Add(new ValueParameter<ResultCollection>("Results", new ResultCollection()));
208      islandVariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("IslandGenerations", new IntValue(0)));
209      islandVariableCreator.CollectedValues.Add(new ValueParameter<IntValue>("IslandEvaluatedSolutions", new IntValue(0)));
210
211      islandAnalyzer1.Name = "Island Analyzer (placeholder)";
212      islandAnalyzer1.OperatorParameter.ActualName = IslandAnalyzerParameter.Name;
213
214      analyzer1.Name = "Analyzer (placeholder)";
215      analyzer1.OperatorParameter.ActualName = AnalyzerParameter.Name;
216
217      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Migrations"));
218      resultsCollector1.CollectedValues.Add(new LookupParameter<IntValue>("Generations"));
219      resultsCollector1.CollectedValues.Add(new ScopeTreeLookupParameter<ResultCollection>("IslandResults", "Result set for each island", "Results"));
220      resultsCollector1.ResultsParameter.ActualName = ResultsParameter.Name;
221
222      uniformSubScopesProcessor1.Parallel.Value = true;
223
224      generationsAssigner.Name = "Initialize Island Generations";
225      generationsAssigner.LeftSideParameter.ActualName = IslandGenerations.Name;
226      generationsAssigner.RightSideParameter.Value = new IntValue(0);
227
228      evaluatedSolutionsAssigner.Name = "Initialize Island evaluated solutions";
229      evaluatedSolutionsAssigner.LeftSideParameter.ActualName = IslandEvaluatedSolutions.Name;
230      evaluatedSolutionsAssigner.RightSideParameter.Value = new IntValue(0);
231
232      selector.Name = "Selector (placeholder)";
233      selector.OperatorParameter.ActualName = SelectorParameter.Name;
234
235      childrenCreator.ParentsPerChild = new IntValue(2);
236
237      crossover.Name = "Crossover (placeholder)";
238      crossover.OperatorParameter.ActualName = CrossoverParameter.Name;
239
240      stochasticBranch.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
241      //set it to the random number generator of the island
242      stochasticBranch.RandomParameter.ActualName = "LocalRandom";
243
244      mutator.Name = "Mutator (placeholder)";
245      mutator.OperatorParameter.ActualName = MutatorParameter.Name;
246
247      subScopesRemover.RemoveAllSubScopes = true;
248
249      evaluator.Name = "Evaluator (placeholder)";
250      evaluator.OperatorParameter.ActualName = EvaluatorParameter.Name;
251
252      subScopesCounter.Name = "Increment EvaluatedSolutions";
253      subScopesCounter.ValueParameter.ActualName = IslandEvaluatedSolutions.Name;
254
255      bestSelector.CopySelected = new BoolValue(false);
256      bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
257      bestSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
258      bestSelector.QualityParameter.ActualName = QualityParameter.Name;
259
260      islandGenerationsCounter.Name = "Increment island generatrions";
261      islandGenerationsCounter.ValueParameter.ActualName = IslandGenerations.Name;
262      islandGenerationsCounter.Increment = new IntValue(1);
263
264      checkIslandGenerationsReachedMaximum.LeftSideParameter.ActualName = IslandGenerations.Name;
265      checkIslandGenerationsReachedMaximum.RightSideParameter.ActualName = MigrationIntervalParameter.Name;
266      checkIslandGenerationsReachedMaximum.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
267      checkIslandGenerationsReachedMaximum.ResultParameter.ActualName = Migrate.Name;
268
269      checkContinueEvolution.Name = "Migrate?";
270      checkContinueEvolution.ConditionParameter.ActualName = Migrate.Name;
271      checkContinueEvolution.FalseBranch = selector;
272
273      islandAnalyzer2.Name = "Island Analyzer (placeholder)";
274      islandAnalyzer2.OperatorParameter.ActualName = IslandAnalyzerParameter.Name;
275
276      generationsReducer.Name = "Increment Generations";
277      generationsReducer.ParameterToReduce.ActualName = islandGenerationsCounter.ValueParameter.ActualName;
278      generationsReducer.TargetParameter.ActualName = "Generations";
279      generationsReducer.ReductionOperation.Value = new ReductionOperation(ReductionOperations.Min);
280      generationsReducer.TargetOperation.Value = new ReductionOperation(ReductionOperations.Sum);
281
282      evaluatedSolutionsReducer.Name = "Increment Evaluated Solutions";
283      evaluatedSolutionsReducer.ParameterToReduce.ActualName = IslandEvaluatedSolutions.Name;
284      evaluatedSolutionsReducer.TargetParameter.ActualName = EvaluatedSolutionsParameter.Name;
285      evaluatedSolutionsReducer.ReductionOperation.Value = new ReductionOperation(ReductionOperations.Sum);
286      evaluatedSolutionsReducer.TargetOperation.Value = new ReductionOperation(ReductionOperations.Sum);
287
288      emigrantsSelector.Name = "Emigrants Selector (placeholder)";
289      emigrantsSelector.OperatorParameter.ActualName = EmigrantsSelectorParameter.Name;
290
291      migrationsCounter.Name = "Increment number of Migrations";
292      migrationsCounter.ValueParameter.ActualName = "Migrations";
293      migrationsCounter.Increment = new IntValue(1);
294
295      migrator.Name = "Migrator (placeholder)";
296      migrator.OperatorParameter.ActualName = MigratorParameter.Name;
297
298      immigrationReplacer.Name = "Immigration Replacer (placeholder)";
299      immigrationReplacer.OperatorParameter.ActualName = ImmigrationReplacerParameter.Name;
300
301      generationsComparator.Name = "Generations >= MaximumGenerations ?";
302      generationsComparator.Comparison = new Comparison(ComparisonType.GreaterOrEqual);
303      generationsComparator.LeftSideParameter.ActualName = "Generations";
304      generationsComparator.ResultParameter.ActualName = "TerminateGenerations";
305      generationsComparator.RightSideParameter.ActualName = MaximumGenerationsParameter.Name;
306
307      analyzer2.Name = "Analyzer (placeholder)";
308      analyzer2.OperatorParameter.ActualName = AnalyzerParameter.Name;
309
310      generationsTerminationCondition.Name = "Terminate?";
311      generationsTerminationCondition.ConditionParameter.ActualName = "TerminateGenerations";
312
313      reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
314      reevaluateElitesBranch.Name = "Reevaluate elites ?";
315      #endregion
316
317      #region Create operator graph
318      OperatorGraph.InitialOperator = variableCreator;
319      variableCreator.Successor = uniformSubScopesProcessor0;
320      uniformSubScopesProcessor0.Operator = islandVariableCreator;
321      uniformSubScopesProcessor0.Successor = analyzer1;
322      islandVariableCreator.Successor = islandAnalyzer1;
323      // BackwardsCompatibility3.3
324      //the local randoms are created by the island GA itself and are only here to ensure same algorithm results
325      #region Backwards compatible code, remove local random creator with 3.4 and rewire the operator graph
326      islandAnalyzer1.Successor = localRandomCreator;
327      localRandomCreator.Successor = null;
328      #endregion
329      analyzer1.Successor = resultsCollector1;
330      resultsCollector1.Successor = uniformSubScopesProcessor1;
331      uniformSubScopesProcessor1.Operator = generationsAssigner;
332      uniformSubScopesProcessor1.Successor = generationsReducer;
333      generationsReducer.Successor = evaluatedSolutionsReducer;
334      evaluatedSolutionsReducer.Successor = migrationsCounter;
335      migrationsCounter.Successor = uniformSubScopesProcessor5;
336      generationsAssigner.Successor = evaluatedSolutionsAssigner;
337      evaluatedSolutionsAssigner.Successor = selector;
338      selector.Successor = subScopesProcessor1;
339      subScopesProcessor1.Operators.Add(new EmptyOperator());
340      subScopesProcessor1.Operators.Add(childrenCreator);
341      subScopesProcessor1.Successor = subScopesProcessor2;
342      childrenCreator.Successor = uniformSubScopesProcessor2;
343      uniformSubScopesProcessor2.Operator = crossover;
344      uniformSubScopesProcessor2.Successor = uniformSubScopesProcessor3;
345      crossover.Successor = stochasticBranch;
346      stochasticBranch.FirstBranch = mutator;
347      stochasticBranch.SecondBranch = null;
348      stochasticBranch.Successor = subScopesRemover;
349      mutator.Successor = null;
350      subScopesRemover.Successor = null;
351      uniformSubScopesProcessor3.Operator = evaluator;
352      uniformSubScopesProcessor3.Successor = subScopesCounter;
353      evaluator.Successor = null;
354      subScopesCounter.Successor = null;
355      subScopesProcessor2.Operators.Add(bestSelector);
356      subScopesProcessor2.Operators.Add(new EmptyOperator());
357      subScopesProcessor2.Successor = mergingReducer;
358      mergingReducer.Successor = islandAnalyzer2;
359      bestSelector.Successor = rightReducer;
360      rightReducer.Successor = reevaluateElitesBranch;
361      reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor3;
362      reevaluateElitesBranch.FalseBranch = null;
363      reevaluateElitesBranch.Successor = null;
364      islandAnalyzer2.Successor = islandGenerationsCounter;
365      islandGenerationsCounter.Successor = checkIslandGenerationsReachedMaximum;
366      checkIslandGenerationsReachedMaximum.Successor = checkContinueEvolution;
367      uniformSubScopesProcessor5.Operator = emigrantsSelector;
368      emigrantsSelector.Successor = null;
369      uniformSubScopesProcessor5.Successor = migrator;
370      migrator.Successor = uniformSubScopesProcessor6;
371      uniformSubScopesProcessor6.Operator = immigrationReplacer;
372      uniformSubScopesProcessor6.Successor = generationsComparator;
373      generationsComparator.Successor = analyzer2;
374      analyzer2.Successor = generationsTerminationCondition;
375      generationsTerminationCondition.TrueBranch = null;
376      generationsTerminationCondition.FalseBranch = uniformSubScopesProcessor1;
377      generationsTerminationCondition.Successor = null;
378      #endregion
379    }
380
381    [StorableHook(HookType.AfterDeserialization)]
382    private void AfterDeserialization() {
383      // BackwardsCompatibility3.3
384      #region Backwards compatible code, remove with 3.4
385      if (!Parameters.ContainsKey("ReevaluateElites")) {
386        Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
387      }
388      #endregion
389    }
390
391    public override IOperation Apply() {
392      if (CrossoverParameter.ActualValue == null)
393        return null;
394      return base.Apply();
395    }
396  }
397}
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