[16276] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17180] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[16276] | 4 | *
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| 5 | * This file is part of HeuristicLab.
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| 6 | *
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| 7 | * HeuristicLab is free software: you can redistribute it and/or modify
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| 8 | * it under the terms of the GNU General Public License as published by
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| 9 | * the Free Software Foundation, either version 3 of the License, or
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| 10 | * (at your option) any later version.
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| 11 | *
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| 12 | * HeuristicLab is distributed in the hope that it will be useful,
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| 13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 15 | * GNU General Public License for more details.
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| 16 | *
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| 17 | * You should have received a copy of the GNU General Public License
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| 18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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| 19 | */
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| 20 | #endregion
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| 21 |
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| 22 | using System;
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| 23 | using System.Collections.Generic;
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| 24 | using System.Linq;
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| 25 | using System.Runtime.InteropServices;
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| 26 | using HeuristicLab.Common;
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| 27 | using HeuristicLab.Core;
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[16277] | 28 | using HeuristicLab.Data;
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[16276] | 29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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[16277] | 30 | using HeuristicLab.Parameters;
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[16565] | 31 | using HEAL.Attic;
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[16276] | 32 |
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| 33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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[16565] | 34 | [StorableType("91723319-8F15-4D33-B277-40AC7C7CF9AE")]
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[16276] | 35 | [Item("SymbolicDataAnalysisExpressionTreeNativeInterpreter", "An interpreter that wraps a native dll")]
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| 36 | public class SymbolicDataAnalysisExpressionTreeNativeInterpreter : ParameterizedNamedItem, ISymbolicDataAnalysisExpressionTreeInterpreter {
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[16277] | 37 | private const string EvaluatedSolutionsParameterName = "EvaluatedSolutions";
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[16276] | 38 |
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[16277] | 39 | #region parameters
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| 40 | public IFixedValueParameter<IntValue> EvaluatedSolutionsParameter {
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| 41 | get { return (IFixedValueParameter<IntValue>)Parameters[EvaluatedSolutionsParameterName]; }
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| 42 | }
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| 43 | #endregion
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| 44 |
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| 45 | #region properties
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| 46 | public int EvaluatedSolutions {
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| 47 | get { return EvaluatedSolutionsParameter.Value.Value; }
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| 48 | set { EvaluatedSolutionsParameter.Value.Value = value; }
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| 49 | }
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| 50 | #endregion
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| 51 |
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[16276] | 52 | public void ClearState() { }
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| 53 |
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[16277] | 54 | public SymbolicDataAnalysisExpressionTreeNativeInterpreter() {
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| 55 | Parameters.Add(new FixedValueParameter<IntValue>(EvaluatedSolutionsParameterName, "A counter for the total number of solutions the interpreter has evaluated", new IntValue(0)));
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| 56 | }
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[16276] | 57 |
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| 58 | [StorableConstructor]
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[16565] | 59 | protected SymbolicDataAnalysisExpressionTreeNativeInterpreter(StorableConstructorFlag _) : base(_) { }
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[16276] | 60 |
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| 61 | protected SymbolicDataAnalysisExpressionTreeNativeInterpreter(SymbolicDataAnalysisExpressionTreeNativeInterpreter original, Cloner cloner) : base(original, cloner) {
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| 62 | }
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| 63 |
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| 64 | public override IDeepCloneable Clone(Cloner cloner) {
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| 65 | return new SymbolicDataAnalysisExpressionTreeNativeInterpreter(this, cloner);
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| 66 | }
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| 67 |
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| 68 | private NativeInstruction[] Compile(ISymbolicExpressionTree tree, Func<ISymbolicExpressionTreeNode, byte> opCodeMapper) {
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| 69 | var root = tree.Root.GetSubtree(0).GetSubtree(0);
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| 70 | var code = new NativeInstruction[root.GetLength()];
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| 71 | if (root.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)");
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| 72 | code[0] = new NativeInstruction { narg = (ushort)root.SubtreeCount, opcode = opCodeMapper(root) };
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| 73 | int c = 1, i = 0;
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| 74 | foreach (var node in root.IterateNodesBreadth()) {
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| 75 | for (int j = 0; j < node.SubtreeCount; ++j) {
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| 76 | var s = node.GetSubtree(j);
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| 77 | if (s.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)");
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| 78 | code[c + j] = new NativeInstruction { narg = (ushort)s.SubtreeCount, opcode = opCodeMapper(s) };
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| 79 | }
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| 80 |
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| 81 | if (node is VariableTreeNode variable) {
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| 82 | code[i].weight = variable.Weight;
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| 83 | code[i].data = cachedData[variable.VariableName].AddrOfPinnedObject();
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| 84 | } else if (node is ConstantTreeNode constant) {
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| 85 | code[i].value = constant.Value;
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| 86 | }
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| 87 |
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| 88 | code[i].childIndex = c;
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| 89 | c += node.SubtreeCount;
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| 90 | ++i;
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| 91 | }
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| 92 | return code;
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| 93 | }
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| 94 |
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| 95 | private readonly object syncRoot = new object();
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| 96 |
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| 97 | [ThreadStatic]
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| 98 | private static Dictionary<string, GCHandle> cachedData;
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| 99 |
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[16378] | 100 | [ThreadStatic]
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[17402] | 101 | private static IDataset cachedDataset;
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[16378] | 102 |
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[16762] | 103 | private static readonly HashSet<byte> supportedOpCodes = new HashSet<byte>() {
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| 104 | (byte)OpCode.Constant,
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| 105 | (byte)OpCode.Variable,
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| 106 | (byte)OpCode.Add,
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| 107 | (byte)OpCode.Sub,
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| 108 | (byte)OpCode.Mul,
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| 109 | (byte)OpCode.Div,
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| 110 | (byte)OpCode.Exp,
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| 111 | (byte)OpCode.Log,
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| 112 | (byte)OpCode.Sin,
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| 113 | (byte)OpCode.Cos,
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| 114 | (byte)OpCode.Tan,
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| 115 | (byte)OpCode.Tanh,
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| 116 | (byte)OpCode.Power,
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| 117 | (byte)OpCode.Root,
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| 118 | (byte)OpCode.SquareRoot,
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| 119 | (byte)OpCode.Square,
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| 120 | (byte)OpCode.CubeRoot,
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| 121 | (byte)OpCode.Cube,
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| 122 | (byte)OpCode.Absolute,
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| 123 | (byte)OpCode.AnalyticQuotient
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| 124 | };
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| 125 |
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[16276] | 126 | public IEnumerable<double> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, IDataset dataset, IEnumerable<int> rows) {
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| 127 | if (!rows.Any()) return Enumerable.Empty<double>();
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| 128 |
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[17801] | 129 | if (cachedData == null || cachedDataset != dataset || cachedDataset is ModifiableDataset) {
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[16276] | 130 | InitCache(dataset);
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| 131 | }
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| 132 |
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[16762] | 133 | byte mapSupportedSymbols(ISymbolicExpressionTreeNode node) {
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| 134 | var opCode = OpCodes.MapSymbolToOpCode(node);
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| 135 | if (supportedOpCodes.Contains(opCode)) return opCode;
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| 136 | else throw new NotSupportedException($"The native interpreter does not support {node.Symbol.Name}");
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| 137 | };
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| 138 | var code = Compile(tree, mapSupportedSymbols);
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[16276] | 139 |
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| 140 | var rowsArray = rows.ToArray();
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| 141 | var result = new double[rowsArray.Length];
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| 142 |
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| 143 | NativeWrapper.GetValuesVectorized(code, code.Length, rowsArray, rowsArray.Length, result);
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[16378] | 144 |
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| 145 | // when evaluation took place without any error, we can increment the counter
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| 146 | lock (syncRoot) {
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| 147 | EvaluatedSolutions++;
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| 148 | }
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| 149 |
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[16276] | 150 | return result;
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| 151 | }
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| 152 |
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| 153 | private void InitCache(IDataset dataset) {
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[17402] | 154 | cachedDataset = dataset;
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[16379] | 155 |
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| 156 | // free handles to old data
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| 157 | if (cachedData != null) {
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| 158 | foreach (var gch in cachedData.Values) {
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| 159 | gch.Free();
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| 160 | }
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| 161 | cachedData = null;
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| 162 | }
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| 163 |
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| 164 | // cache new data
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[16276] | 165 | cachedData = new Dictionary<string, GCHandle>();
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| 166 | foreach (var v in dataset.DoubleVariables) {
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| 167 | var values = dataset.GetDoubleValues(v).ToArray();
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| 168 | var gch = GCHandle.Alloc(values, GCHandleType.Pinned);
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| 169 | cachedData[v] = gch;
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| 170 | }
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| 171 | }
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| 172 |
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| 173 | public void InitializeState() {
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| 174 | if (cachedData != null) {
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| 175 | foreach (var gch in cachedData.Values) {
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| 176 | gch.Free();
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| 177 | }
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| 178 | cachedData = null;
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| 179 | }
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[17402] | 180 | cachedDataset = null;
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[16276] | 181 | EvaluatedSolutions = 0;
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| 182 | }
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| 183 | }
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| 184 | }
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