Mercurial > hg > truffle
annotate graal/com.oracle.graal.phases/src/com/oracle/graal/phases/graph/ComputeProbabilityClosure.java @ 9957:1b33ef6544b4
Fixed a warning.
author | Christian Haeubl <haeubl@ssw.jku.at> |
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date | Mon, 10 Jun 2013 09:30:32 +0200 |
parents | de73bbbde021 |
children | 053b837d0d7d |
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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.graal.phases.graph; |
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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.graal.graph.*; |
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28 import com.oracle.graal.nodes.*; |
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29 import com.oracle.graal.nodes.util.*; |
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30 |
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31 /** |
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32 * Computes probabilities for nodes in a graph. |
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33 * <p> |
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34 * The computation of absolute probabilities works in three steps: |
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35 * <ol> |
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36 * <li>{@link PropagateProbability} traverses the graph in post order (merges after their ends, ...) |
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37 * and keeps track of the "probability state". Whenever it encounters a {@link ControlSplitNode} it |
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38 * uses the split's probability information to divide the probability upon the successors. Whenever |
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39 * it encounters an {@link Invoke} it assumes that the exception edge is unlikely and propagates the |
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40 * whole probability to the normal successor. Whenever it encounters a {@link MergeNode} it sums up |
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41 * the probability of all predecessors. It also maintains a set of active loops (whose |
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42 * {@link LoopBeginNode} has been visited) and builds def/use information for step 2.</li> |
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43 * <li></li> |
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44 * <li>{@link PropagateLoopFrequency} propagates the loop frequencies and multiplies each |
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45 * {@link FixedNode}'s probability with its loop frequency.</li> |
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46 * </ol> |
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47 * TODO: add exception probability information to Invokes |
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48 */ |
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49 public class ComputeProbabilityClosure { |
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50 |
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51 private static final double EPSILON = 1d / Integer.MAX_VALUE; |
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52 |
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53 private final StructuredGraph graph; |
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54 private final NodesToDoubles nodeProbabilities; |
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55 private final Set<LoopInfo> loopInfos; |
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56 private final Map<MergeNode, Set<LoopInfo>> mergeLoops; |
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57 |
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58 public ComputeProbabilityClosure(StructuredGraph graph) { |
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59 this.graph = graph; |
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60 this.nodeProbabilities = new NodesToDoubles(graph.getNodeCount()); |
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61 this.loopInfos = new HashSet<>(); |
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62 this.mergeLoops = new IdentityHashMap<>(); |
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63 } |
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64 |
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65 public NodesToDoubles apply() { |
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66 new PropagateProbability(graph.start()).apply(); |
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67 computeLoopFactors(); |
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68 new PropagateLoopFrequency(graph.start()).apply(); |
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69 return nodeProbabilities; |
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70 } |
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71 |
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72 private void computeLoopFactors() { |
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73 for (LoopInfo info : loopInfos) { |
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74 double frequency = info.loopFrequency(nodeProbabilities); |
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75 assert frequency != -1; |
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76 } |
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77 } |
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78 |
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79 public static class LoopInfo { |
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80 |
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81 public final LoopBeginNode loopBegin; |
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82 |
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83 public final NodeMap<Set<LoopInfo>> requires; |
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84 |
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85 private double loopFrequency = -1; |
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86 public boolean ended = false; |
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87 |
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88 public LoopInfo(LoopBeginNode loopBegin) { |
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89 this.loopBegin = loopBegin; |
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90 this.requires = loopBegin.graph().createNodeMap(); |
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91 } |
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92 |
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93 public double loopFrequency(NodesToDoubles nodeProbabilities) { |
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94 if (loopFrequency == -1 && ended) { |
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95 double backEdgeProb = 0.0; |
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96 for (LoopEndNode le : loopBegin.loopEnds()) { |
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97 double factor = 1; |
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98 Set<LoopInfo> requireds = requires.get(le); |
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99 for (LoopInfo required : requireds) { |
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100 double t = required.loopFrequency(nodeProbabilities); |
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101 if (t == -1) { |
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102 return -1; |
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103 } |
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104 factor *= t; |
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105 } |
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106 backEdgeProb += nodeProbabilities.get(le) * factor; |
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107 } |
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108 double d = nodeProbabilities.get(loopBegin) - backEdgeProb; |
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109 if (d < EPSILON) { |
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110 d = EPSILON; |
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111 } |
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112 loopFrequency = nodeProbabilities.get(loopBegin) / d; |
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113 loopBegin.setLoopFrequency(loopFrequency); |
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114 } |
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115 return loopFrequency; |
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116 } |
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117 } |
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118 |
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119 private class Probability implements MergeableState<Probability> { |
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120 |
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121 public double probability; |
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122 public HashSet<LoopInfo> loops; |
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123 public LoopInfo loopInfo; |
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124 |
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125 public Probability(double probability, HashSet<LoopInfo> loops) { |
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126 assert probability >= 0.0; |
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127 this.probability = probability; |
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128 this.loops = new HashSet<>(4); |
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129 if (loops != null) { |
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130 this.loops.addAll(loops); |
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131 } |
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132 } |
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133 |
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134 @Override |
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135 public Probability clone() { |
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136 return new Probability(probability, loops); |
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137 } |
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138 |
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139 @Override |
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140 public boolean merge(MergeNode merge, List<Probability> withStates) { |
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141 if (merge.forwardEndCount() > 1) { |
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142 HashSet<LoopInfo> intersection = new HashSet<>(loops); |
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143 for (Probability other : withStates) { |
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144 intersection.retainAll(other.loops); |
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145 } |
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146 for (LoopInfo info : loops) { |
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147 if (!intersection.contains(info)) { |
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148 double loopFrequency = info.loopFrequency(nodeProbabilities); |
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149 if (loopFrequency == -1) { |
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150 return false; |
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151 } |
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152 probability *= loopFrequency; |
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153 } |
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154 } |
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155 for (Probability other : withStates) { |
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156 double prob = other.probability; |
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157 for (LoopInfo info : other.loops) { |
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158 if (!intersection.contains(info)) { |
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159 double loopFrequency = info.loopFrequency(nodeProbabilities); |
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160 if (loopFrequency == -1) { |
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161 return false; |
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162 } |
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163 prob *= loopFrequency; |
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164 } |
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165 } |
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166 probability += prob; |
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167 } |
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168 loops = intersection; |
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169 mergeLoops.put(merge, new HashSet<>(intersection)); |
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170 probability = Math.max(0.0, probability); |
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171 } |
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172 return true; |
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173 } |
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174 |
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175 @Override |
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176 public void loopBegin(LoopBeginNode loopBegin) { |
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177 loopInfo = new LoopInfo(loopBegin); |
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178 loopInfos.add(loopInfo); |
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179 loops.add(loopInfo); |
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180 } |
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181 |
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182 @Override |
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183 public void loopEnds(LoopBeginNode loopBegin, List<Probability> loopEndStates) { |
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184 assert loopInfo != null; |
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185 List<LoopEndNode> loopEnds = loopBegin.orderedLoopEnds(); |
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186 int i = 0; |
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187 for (Probability proba : loopEndStates) { |
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188 LoopEndNode loopEnd = loopEnds.get(i++); |
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189 Set<LoopInfo> requires = loopInfo.requires.get(loopEnd); |
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190 if (requires == null) { |
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191 requires = new HashSet<>(); |
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192 loopInfo.requires.set(loopEnd, requires); |
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193 } |
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194 for (LoopInfo innerLoop : proba.loops) { |
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195 if (innerLoop != loopInfo && !this.loops.contains(innerLoop)) { |
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196 requires.add(innerLoop); |
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197 } |
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198 } |
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199 } |
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200 loopInfo.ended = true; |
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201 } |
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202 |
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203 @Override |
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204 public void afterSplit(AbstractBeginNode node) { |
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205 assert node.predecessor() != null; |
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206 Node pred = node.predecessor(); |
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207 if (pred instanceof Invoke) { |
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208 Invoke x = (Invoke) pred; |
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209 if (x.next() != node) { |
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210 probability = 0; |
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211 } |
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212 } else { |
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213 assert pred instanceof ControlSplitNode; |
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214 ControlSplitNode x = (ControlSplitNode) pred; |
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215 double nodeProbability = x.probability(node); |
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216 assert nodeProbability >= 0.0 : "Node " + x + " provided negative probability for begin " + node + ": " + nodeProbability; |
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217 probability *= nodeProbability; |
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218 assert probability >= 0.0; |
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219 } |
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220 } |
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221 } |
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222 |
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223 private class PropagateProbability extends PostOrderNodeIterator<Probability> { |
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224 |
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225 public PropagateProbability(FixedNode start) { |
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226 super(start, new Probability(1d, null)); |
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227 } |
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228 |
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229 @Override |
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230 protected void node(FixedNode node) { |
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231 nodeProbabilities.put(node, state.probability); |
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232 } |
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233 } |
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234 |
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|
235 private class LoopCount implements MergeableState<LoopCount> { |
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236 |
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237 public double count; |
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238 |
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239 public LoopCount(double count) { |
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240 this.count = count; |
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241 } |
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242 |
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243 @Override |
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244 public LoopCount clone() { |
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245 return new LoopCount(count); |
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246 } |
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247 |
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248 @Override |
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249 public boolean merge(MergeNode merge, List<LoopCount> withStates) { |
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250 assert merge.forwardEndCount() == withStates.size() + 1; |
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251 if (merge.forwardEndCount() > 1) { |
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252 Set<LoopInfo> loops = mergeLoops.get(merge); |
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253 assert loops != null; |
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254 double countProd = 1; |
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255 for (LoopInfo loop : loops) { |
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256 countProd *= loop.loopFrequency(nodeProbabilities); |
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257 } |
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258 count = countProd; |
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259 } |
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260 return true; |
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261 } |
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262 |
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263 @Override |
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264 public void loopBegin(LoopBeginNode loopBegin) { |
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265 count *= loopBegin.loopFrequency(); |
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266 } |
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267 |
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268 @Override |
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269 public void loopEnds(LoopBeginNode loopBegin, List<LoopCount> loopEndStates) { |
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270 // nothing to do... |
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271 } |
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272 |
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273 @Override |
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274 public void afterSplit(AbstractBeginNode node) { |
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275 // nothing to do... |
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276 } |
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277 } |
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278 |
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279 private class PropagateLoopFrequency extends PostOrderNodeIterator<LoopCount> { |
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280 |
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281 public PropagateLoopFrequency(FixedNode start) { |
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282 super(start, new LoopCount(1d)); |
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283 } |
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284 |
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285 @Override |
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286 protected void node(FixedNode node) { |
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287 nodeProbabilities.put(node, nodeProbabilities.get(node) * state.count); |
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288 } |
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289 |
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290 } |
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291 } |