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annotate graal/com.oracle.max.graal.compiler/src/com/oracle/max/graal/compiler/phases/ComputeProbabilityPhase.java @ 4706:a59fe7906f0b
additional LoopFrequencyPropagationPolicy versions
author | Lukas Stadler <lukas.stadler@jku.at> |
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date | Mon, 27 Feb 2012 19:41:14 +0100 |
parents | a9181b59a6bf |
children | c4a0a220e0f3 |
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1 /* |
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2 * Copyright (c) 2011, Oracle and/or its affiliates. All rights reserved. |
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3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. |
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4 * |
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5 * This code is free software; you can redistribute it and/or modify it |
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6 * under the terms of the GNU General Public License version 2 only, as |
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7 * published by the Free Software Foundation. |
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8 * |
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9 * This code is distributed in the hope that it will be useful, but WITHOUT |
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10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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12 * version 2 for more details (a copy is included in the LICENSE file that |
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13 * accompanied this code). |
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14 * |
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15 * You should have received a copy of the GNU General Public License version |
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16 * 2 along with this work; if not, write to the Free Software Foundation, |
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17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. |
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18 * |
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19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA |
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20 * or visit www.oracle.com if you need additional information or have any |
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21 * questions. |
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22 */ |
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23 package com.oracle.max.graal.compiler.phases; |
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24 |
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25 import java.util.*; |
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26 |
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27 import com.oracle.max.criutils.*; |
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28 import com.oracle.max.graal.compiler.*; |
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29 import com.oracle.max.graal.compiler.graph.*; |
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30 import com.oracle.max.graal.debug.*; |
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31 import com.oracle.max.graal.graph.*; |
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32 import com.oracle.max.graal.lir.cfg.*; |
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33 import com.oracle.max.graal.nodes.*; |
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34 |
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35 public class ComputeProbabilityPhase extends Phase { |
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36 private static final double EPSILON = 1d / Integer.MAX_VALUE; |
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37 |
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38 /* |
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39 * The computation of absolute probabilities works in three steps: |
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40 * |
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41 * - The first step, "PropagateProbability", traverses the graph in post order (merges after their ends, ...) and keeps track of the "probability state". |
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42 * Whenever it encounters a ControlSplit it uses the split's probability information to divide the probability upon the successors. |
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43 * Whenever it encounters an Invoke it assumes that the exception edge is unlikely and propagates the whole probability to the normal successor. |
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44 * Whenever it encounters a Merge it sums up the probability of all predecessors. |
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45 * It also maintains a set of active loops (whose LoopBegin has been visited) and builds def/use information for the second step. |
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46 * |
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47 * - The third step propagates the loop frequencies and multiplies each FixedNode's probability with its loop frequency. |
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48 * |
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49 * TODO: add exception probability information to Invokes |
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50 */ |
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51 |
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52 @Override |
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53 protected void run(StructuredGraph graph) { |
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54 new PropagateProbability(graph.start()).apply(); |
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55 Debug.dump(graph, "After PropagateProbability"); |
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56 computeLoopFactors(); |
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57 Debug.dump(graph, "After computeLoopFactors"); |
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58 new PropagateLoopFrequency(graph.start()).apply(); |
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59 |
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60 ControlFlowGraph cfg = ControlFlowGraph.compute(graph, true, true, false, false); |
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61 |
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62 if (GraalOptions.LoopFrequencyPropagationPolicy < 0) { |
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63 for (Loop loop : cfg.getLoops()) { |
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64 if (loop.parent == null) { |
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65 correctLoopFrequencies(loop); |
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66 } |
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67 } |
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68 } |
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69 } |
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70 |
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71 private void correctLoopFrequencies(Loop loop) { |
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72 double frequency = ((LoopBeginNode) loop.header.getBeginNode()).loopFrequency(); |
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73 |
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74 double factor; |
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75 switch (GraalOptions.LoopFrequencyPropagationPolicy) { |
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76 case -1: |
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77 factor = 1 / frequency; |
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78 break; |
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79 case -2: |
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80 factor = (1 / frequency) * (Math.log(Math.E + frequency) - 1); |
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81 break; |
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82 default: throw GraalInternalError.shouldNotReachHere(); |
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83 } |
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84 |
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85 for (Block block : loop.blocks) { |
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86 FixedNode node = block.getBeginNode(); |
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87 |
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88 while (node != block.getEndNode()) { |
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89 node.setProbability(node.probability() * factor); |
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90 node = ((FixedWithNextNode) node).next(); |
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91 } |
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92 } |
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93 |
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94 for (Loop child : loop.children) { |
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95 correctLoopFrequencies(child); |
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96 } |
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97 } |
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98 |
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99 private void computeLoopFactors() { |
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100 for (LoopInfo info : loopInfos) { |
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101 double frequency = info.loopFrequency(); |
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102 assert frequency != -1; |
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103 } |
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104 } |
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105 |
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106 private static boolean isRelativeProbability(double prob) { |
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107 // 1.01 to allow for some rounding errors |
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108 return prob >= 0 && prob <= 1.01; |
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109 } |
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110 |
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111 public static class LoopInfo { |
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112 public final LoopBeginNode loopBegin; |
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113 |
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114 public final NodeMap<Set<LoopInfo>> requires; |
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115 |
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116 private double loopFrequency = -1; |
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117 public boolean ended = false; |
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118 |
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119 public LoopInfo(LoopBeginNode loopBegin) { |
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120 this.loopBegin = loopBegin; |
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121 this.requires = loopBegin.graph().createNodeMap(); |
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122 } |
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123 |
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124 public double loopFrequency() { |
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125 if (loopFrequency == -1 && ended) { |
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126 double backEdgeProb = 0.0; |
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127 for (LoopEndNode le : loopBegin.loopEnds()) { |
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128 double factor = 1; |
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129 Set<LoopInfo> requireds = requires.get(le); |
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130 for (LoopInfo required : requireds) { |
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131 double t = required.loopFrequency(); |
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132 if (t == -1) { |
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133 return -1; |
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134 } |
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135 factor *= t; |
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136 } |
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137 backEdgeProb += le.probability() * factor; |
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138 } |
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139 double d = backEdgeProb; |
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140 if (d < EPSILON) { |
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141 d = EPSILON; |
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142 } else if (d > loopBegin.probability() - EPSILON) { |
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143 d = loopBegin.probability() - EPSILON; |
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144 } |
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145 loopFrequency = loopBegin.probability() / (loopBegin.probability() - d); |
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146 loopBegin.setLoopFrequency(loopFrequency); |
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147 } |
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148 return loopFrequency; |
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149 } |
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150 } |
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151 |
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152 public Set<LoopInfo> loopInfos = new HashSet<>(); |
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153 public Map<MergeNode, Set<LoopInfo>> mergeLoops = new IdentityHashMap<>(); |
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154 |
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155 private class Probability implements MergeableState<Probability> { |
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156 public double probability; |
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157 public HashSet<LoopInfo> loops; |
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158 public LoopInfo loopInfo; |
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159 |
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160 public Probability(double probability, HashSet<LoopInfo> loops) { |
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161 this.probability = probability; |
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162 this.loops = new HashSet<>(4); |
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163 if (loops != null) { |
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164 this.loops.addAll(loops); |
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165 } |
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166 } |
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167 |
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168 @Override |
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169 public Probability clone() { |
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170 return new Probability(probability, loops); |
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171 } |
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172 |
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173 @Override |
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174 public boolean merge(MergeNode merge, Collection<Probability> withStates) { |
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175 if (merge.forwardEndCount() > 1) { |
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176 HashSet<LoopInfo> intersection = new HashSet<>(loops); |
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177 for (Probability other : withStates) { |
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178 intersection.retainAll(other.loops); |
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179 } |
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180 for (LoopInfo info : loops) { |
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181 if (!intersection.contains(info)) { |
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182 double loopFrequency = info.loopFrequency(); |
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183 if (loopFrequency == -1) { |
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184 return false; |
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185 } |
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186 probability *= loopFrequency; |
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187 } |
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188 } |
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189 for (Probability other : withStates) { |
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190 double prob = other.probability; |
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191 for (LoopInfo info : other.loops) { |
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192 if (!intersection.contains(info)) { |
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193 double loopFrequency = info.loopFrequency(); |
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194 if (loopFrequency == -1) { |
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195 return false; |
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196 } |
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197 prob *= loopFrequency; |
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198 } |
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199 } |
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200 probability += prob; |
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201 } |
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202 loops = intersection; |
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203 mergeLoops.put(merge, new HashSet<>(intersection)); |
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204 assert isRelativeProbability(probability) : probability; |
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205 } |
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206 return true; |
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207 } |
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208 |
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209 @Override |
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210 public void loopBegin(LoopBeginNode loopBegin) { |
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211 loopInfo = new LoopInfo(loopBegin); |
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212 loopInfos.add(loopInfo); |
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213 loops.add(loopInfo); |
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214 } |
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215 |
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216 @Override |
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217 public void loopEnds(LoopBeginNode loopBegin, Collection<Probability> loopEndStates) { |
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218 assert loopInfo != null; |
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219 List<LoopEndNode> loopEnds = loopBegin.orderedLoopEnds(); |
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220 int i = 0; |
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221 for (Probability proba : loopEndStates) { |
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222 LoopEndNode loopEnd = loopEnds.get(i++); |
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223 Set<LoopInfo> requires = loopInfo.requires.get(loopEnd); |
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224 if (requires == null) { |
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225 requires = new HashSet<>(); |
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226 loopInfo.requires.set(loopEnd, requires); |
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227 } |
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228 for (LoopInfo innerLoop : proba.loops) { |
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229 if (innerLoop != loopInfo && !this.loops.contains(innerLoop)) { |
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230 requires.add(innerLoop); |
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231 } |
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232 } |
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233 } |
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234 loopInfo.ended = true; |
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235 } |
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236 |
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|
237 @Override |
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238 public void afterSplit(FixedNode node) { |
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239 assert node.predecessor() != null; |
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240 Node pred = node.predecessor(); |
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241 if (pred instanceof Invoke) { |
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242 Invoke x = (Invoke) pred; |
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243 if (x.next() != node) { |
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244 probability = 0; |
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245 } |
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246 } else { |
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247 assert pred instanceof ControlSplitNode; |
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248 ControlSplitNode x = (ControlSplitNode) pred; |
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249 double sum = 0; |
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250 for (int i = 0; i < x.blockSuccessorCount(); i++) { |
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251 if (x.blockSuccessor(i) == node) { |
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252 sum += x.probability(i); |
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253 } |
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254 } |
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255 probability *= sum; |
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256 } |
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257 } |
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|
258 } |
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259 |
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260 private class PropagateProbability extends PostOrderNodeIterator<Probability> { |
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261 |
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262 public PropagateProbability(FixedNode start) { |
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263 super(start, new Probability(1d, null)); |
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264 } |
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265 |
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266 @Override |
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267 protected void node(FixedNode node) { |
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268 node.setProbability(state.probability); |
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269 } |
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270 } |
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271 |
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272 private class LoopCount implements MergeableState<LoopCount> { |
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273 public double count; |
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274 |
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275 public LoopCount(double count) { |
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276 this.count = count; |
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277 } |
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278 |
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279 @Override |
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280 public LoopCount clone() { |
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281 return new LoopCount(count); |
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282 } |
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283 |
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284 @Override |
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285 public boolean merge(MergeNode merge, Collection<LoopCount> withStates) { |
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286 assert merge.forwardEndCount() == withStates.size() + 1; |
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287 if (merge.forwardEndCount() > 1) { |
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288 Set<LoopInfo> loops = mergeLoops.get(merge); |
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289 assert loops != null; |
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290 double countProd = 1; |
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291 for (LoopInfo loop : loops) { |
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292 countProd *= loop.loopFrequency(); |
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293 } |
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294 count = countProd; |
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295 } |
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296 return true; |
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|
297 } |
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298 |
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299 @Override |
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300 public void loopBegin(LoopBeginNode loopBegin) { |
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301 count *= loopBegin.loopFrequency(); |
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302 } |
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303 |
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|
304 @Override |
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305 public void loopEnds(LoopBeginNode loopBegin, Collection<LoopCount> loopEndStates) { |
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306 // nothing to do... |
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|
307 } |
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308 |
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|
309 @Override |
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|
310 public void afterSplit(FixedNode node) { |
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|
311 // nothing to do... |
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|
312 } |
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|
313 } |
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|
314 |
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|
315 private class PropagateLoopFrequency extends PostOrderNodeIterator<LoopCount> { |
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316 |
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|
317 private final FrequencyPropagationPolicy policy; |
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318 |
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|
319 public PropagateLoopFrequency(FixedNode start) { |
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|
320 super(start, new LoopCount(1d)); |
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|
321 this.policy = createFrequencyPropagationPolicy(); |
3733
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|
322 } |
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|
323 |
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diff
changeset
|
324 @Override |
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changeset
|
325 protected void node(FixedNode node) { |
4638
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|
326 node.setProbability(policy.compute(node.probability(), state.count)); |
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|
327 } |
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|
328 |
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|
329 } |
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|
330 |
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|
331 private static FrequencyPropagationPolicy createFrequencyPropagationPolicy() { |
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|
332 switch (GraalOptions.LoopFrequencyPropagationPolicy) { |
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|
333 case -1: |
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|
334 case -2: |
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|
335 case 0: |
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|
336 return new FullFrequencyPropagation(); |
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|
337 case 1: |
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|
338 return new NoFrequencyPropagation(); |
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|
339 case 2: |
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|
340 return new LogarithmicFrequencyPropagation(); |
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|
341 default: |
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|
342 throw GraalInternalError.shouldNotReachHere(); |
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|
343 } |
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|
344 } |
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|
345 |
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|
346 private interface FrequencyPropagationPolicy { |
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|
347 |
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|
348 double compute(double probability, double frequency); |
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|
349 } |
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|
350 |
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|
351 private static class FullFrequencyPropagation implements FrequencyPropagationPolicy { |
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|
352 |
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|
353 @Override |
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|
354 public double compute(double probability, double frequency) { |
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|
355 return probability * frequency; |
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|
356 } |
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|
357 } |
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|
358 |
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|
359 private static class NoFrequencyPropagation implements FrequencyPropagationPolicy { |
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|
360 |
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|
361 @Override |
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|
362 public double compute(double probability, double frequency) { |
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|
363 return probability; |
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changeset
|
364 } |
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parents:
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changeset
|
365 } |
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parents:
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changeset
|
366 |
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parents:
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diff
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367 private static class LogarithmicFrequencyPropagation implements FrequencyPropagationPolicy { |
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368 |
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369 @Override |
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370 public double compute(double probability, double frequency) { |
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371 double result = Math.pow(probability, 1.5) * Math.log(frequency); |
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372 return Math.max(probability, result); |
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373 } |
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374 } |
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375 } |