1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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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28 | using HeuristicLab.Data;
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29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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30 | using HeuristicLab.Parameters;
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31 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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34 | [StorableClass]
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35 | [Item("SymbolicDataAnalysisExpressionTreeNativeInterpreter", "An interpreter that wraps a native dll")]
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36 | public class SymbolicDataAnalysisExpressionTreeNativeInterpreter : ParameterizedNamedItem, ISymbolicDataAnalysisExpressionTreeInterpreter {
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37 | private const string EvaluatedSolutionsParameterName = "EvaluatedSolutions";
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38 |
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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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52 | public void ClearState() { }
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53 |
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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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57 |
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58 | [StorableConstructor]
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59 | protected SymbolicDataAnalysisExpressionTreeNativeInterpreter(bool deserializing) : base(deserializing) { }
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60 |
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61 |
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62 | protected SymbolicDataAnalysisExpressionTreeNativeInterpreter(SymbolicDataAnalysisExpressionTreeNativeInterpreter original, Cloner cloner) : base(original, cloner) {
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63 | }
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64 |
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65 | public override IDeepCloneable Clone(Cloner cloner) {
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66 | return new SymbolicDataAnalysisExpressionTreeNativeInterpreter(this, cloner);
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67 | }
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68 |
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69 | private NativeInstruction[] Compile(ISymbolicExpressionTree tree, Func<ISymbolicExpressionTreeNode, byte> opCodeMapper) {
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70 | var root = tree.Root.GetSubtree(0).GetSubtree(0);
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71 | var code = new NativeInstruction[root.GetLength()];
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72 | if (root.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)");
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73 | code[0] = new NativeInstruction { narg = (ushort)root.SubtreeCount, opcode = opCodeMapper(root) };
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74 | int c = 1, i = 0;
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75 | foreach (var node in root.IterateNodesBreadth()) {
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76 | for (int j = 0; j < node.SubtreeCount; ++j) {
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77 | var s = node.GetSubtree(j);
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78 | if (s.SubtreeCount > ushort.MaxValue) throw new ArgumentException("Number of subtrees is too big (>65.535)");
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79 | code[c + j] = new NativeInstruction { narg = (ushort)s.SubtreeCount, opcode = opCodeMapper(s) };
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80 | }
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81 |
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82 | if (node is VariableTreeNode variable) {
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83 | code[i].weight = variable.Weight;
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84 | code[i].data = cachedData[variable.VariableName].AddrOfPinnedObject();
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85 | } else if (node is ConstantTreeNode constant) {
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86 | code[i].value = constant.Value;
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87 | }
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88 |
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89 | code[i].childIndex = c;
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90 | c += node.SubtreeCount;
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91 | ++i;
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92 | }
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93 | return code;
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94 | }
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95 |
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96 | private readonly object syncRoot = new object();
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97 |
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98 | [ThreadStatic]
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99 | private static Dictionary<string, GCHandle> cachedData;
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100 |
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101 | public IEnumerable<double> GetSymbolicExpressionTreeValues(ISymbolicExpressionTree tree, IDataset dataset, IEnumerable<int> rows) {
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102 | if (!rows.Any()) return Enumerable.Empty<double>();
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103 |
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104 | lock (syncRoot) {
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105 | EvaluatedSolutions++; // increment the evaluated solutions counter
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106 | }
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107 |
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108 | if (cachedData == null) {
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109 | InitCache(dataset);
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110 | }
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111 |
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112 | var code = Compile(tree, OpCodes.MapSymbolToOpCode);
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113 |
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114 | var rowsArray = rows.ToArray();
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115 | var result = new double[rowsArray.Length];
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116 |
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117 | NativeWrapper.GetValuesVectorized(code, code.Length, rowsArray, rowsArray.Length, result);
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118 | return result;
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119 | }
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120 |
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121 | private void InitCache(IDataset dataset) {
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122 | cachedData = new Dictionary<string, GCHandle>();
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123 | foreach (var v in dataset.DoubleVariables) {
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124 | var values = dataset.GetDoubleValues(v).ToArray();
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125 | var gch = GCHandle.Alloc(values, GCHandleType.Pinned);
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126 | cachedData[v] = gch;
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127 | }
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128 | }
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129 |
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130 | public void InitializeState() {
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131 | if (cachedData != null) {
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132 | foreach (var gch in cachedData.Values) {
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133 | gch.Free();
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134 | }
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135 | cachedData = null;
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136 | }
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137 | EvaluatedSolutions = 0;
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138 | }
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139 | }
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140 | }
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