Mercurial > hg > truffle
annotate graal/com.oracle.graal.phases/src/com/oracle/graal/phases/graph/ComputeProbabilityClosure.java @ 11399:c8a9914b36e8
Use an EPSILON where 1. / EPSILON is finite.
author | Roland Schatz <roland.schatz@oracle.com> |
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date | Fri, 23 Aug 2013 14:03:09 +0200 |
parents | 1a110b7c03e1 |
children | 93c63975217e |
rev | line source |
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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.debug.internal.*; |
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28 import com.oracle.graal.graph.*; |
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29 import com.oracle.graal.nodes.*; |
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30 import com.oracle.graal.nodes.util.*; |
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31 |
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32 /** |
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33 * Computes probabilities for nodes in a graph. |
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34 * <p> |
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35 * The computation of absolute probabilities works in three steps: |
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36 * <ol> |
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37 * <li>{@link PropagateProbability} traverses the graph in post order (merges after their ends, ...) |
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38 * and keeps track of the "probability state". Whenever it encounters a {@link ControlSplitNode} it |
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39 * uses the split's probability information to divide the probability upon the successors. Whenever |
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40 * it encounters an {@link Invoke} it assumes that the exception edge is unlikely and propagates the |
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41 * whole probability to the normal successor. Whenever it encounters a {@link MergeNode} it sums up |
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42 * the probability of all predecessors. It also maintains a set of active loops (whose |
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43 * {@link LoopBeginNode} has been visited) and builds def/use information for step 2.</li> |
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44 * <li></li> |
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45 * <li>{@link PropagateLoopFrequency} propagates the loop frequencies and multiplies each |
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46 * {@link FixedNode}'s probability with its loop frequency.</li> |
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47 * </ol> |
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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 = Double.MIN_NORMAL; |
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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 adjustControlSplitProbabilities(); |
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67 new PropagateProbability(graph.start()).apply(); |
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68 computeLoopFactors(); |
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69 new PropagateLoopFrequency(graph.start()).apply(); |
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70 assert verifyProbabilities(); |
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71 return nodeProbabilities; |
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72 } |
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73 |
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74 /** |
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75 * Assume that paths with a DeoptimizeNode at their end are taken infrequently. |
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76 */ |
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77 private void adjustControlSplitProbabilities() { |
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78 HashSet<ControlSplitNode> result = new HashSet<>(); |
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79 NodeBitMap visitedNodes = new NodeBitMap(graph); |
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80 for (DeoptimizeNode n : graph.getNodes(DeoptimizeNode.class)) { |
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81 if (n.action().doesInvalidateCompilation()) { |
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82 findParentControlSplitNodes(result, n, visitedNodes); |
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83 } |
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84 } |
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85 |
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86 for (ControlSplitNode n : result) { |
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87 if (!allSuxVisited(n, visitedNodes)) { |
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88 modifyProbabilities(n, visitedNodes); |
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89 } |
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90 } |
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91 } |
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92 |
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93 private static void findParentControlSplitNodes(HashSet<ControlSplitNode> result, DeoptimizeNode n, NodeBitMap visitedNodes) { |
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94 ArrayDeque<FixedNode> nodes = new ArrayDeque<>(); |
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95 nodes.push(n); |
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96 |
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97 Node currentNode; |
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98 do { |
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99 currentNode = nodes.pop(); |
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100 visitedNodes.mark(currentNode); |
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101 |
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102 for (Node pred : currentNode.cfgPredecessors()) { |
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103 FixedNode fixedPred = (FixedNode) pred; |
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104 if (visitedNodes.isMarked(fixedPred) && allPredsVisited(fixedPred, visitedNodes)) { |
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105 DebugScope.dump(n.graph(), "ComputeProbabilityClosure"); |
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106 GraalInternalError.shouldNotReachHere(String.format("Endless loop because %s was already visited", fixedPred)); |
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107 } else if (allSuxVisited(fixedPred, visitedNodes)) { |
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108 nodes.push(fixedPred); |
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109 } else { |
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110 assert fixedPred instanceof ControlSplitNode : "only control splits can have more than one sux"; |
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111 result.add((ControlSplitNode) fixedPred); |
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112 } |
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113 } |
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114 } while (!nodes.isEmpty()); |
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115 } |
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116 |
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117 private static void modifyProbabilities(ControlSplitNode controlSplit, NodeBitMap visitedNodes) { |
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118 assert !allSuxVisited(controlSplit, visitedNodes); |
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119 for (Node sux : controlSplit.successors()) { |
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120 if (visitedNodes.isMarked(sux)) { |
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121 controlSplit.setProbability((AbstractBeginNode) sux, 0); |
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122 } |
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123 } |
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124 } |
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125 |
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126 private static boolean allSuxVisited(FixedNode node, NodeBitMap visitedNodes) { |
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127 return allVisited(node.successors(), visitedNodes); |
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128 } |
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129 |
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130 private static boolean allPredsVisited(FixedNode node, NodeBitMap visitedNodes) { |
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131 return allVisited(node.cfgPredecessors(), visitedNodes); |
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132 } |
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133 |
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134 private static boolean allVisited(Iterable<? extends Node> nodes, NodeBitMap visitedNodes) { |
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135 for (Node sux : nodes) { |
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136 if (!visitedNodes.contains(sux)) { |
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137 return false; |
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138 } |
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139 } |
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140 return true; |
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141 } |
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142 |
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143 private boolean verifyProbabilities() { |
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144 if (doesNotAlwaysDeopt(graph)) { |
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145 for (DeoptimizeNode n : graph.getNodes(DeoptimizeNode.class)) { |
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146 if (n.action().doesInvalidateCompilation() && nodeProbabilities.get(n) > 0.01) { |
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147 throw new AssertionError(String.format("%s with reason %s and probability %f in graph %s", n, n.reason(), nodeProbabilities.get(n), graph)); |
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148 } |
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149 } |
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150 } |
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151 return true; |
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152 } |
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153 |
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154 private static boolean doesNotAlwaysDeopt(StructuredGraph graph) { |
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155 return graph.getNodes(ReturnNode.class).iterator().hasNext(); |
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156 } |
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157 |
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158 private void computeLoopFactors() { |
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159 for (LoopInfo info : loopInfos) { |
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160 double frequency = info.loopFrequency(nodeProbabilities); |
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161 assert frequency != -1; |
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162 } |
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163 } |
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164 |
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165 public static class LoopInfo { |
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166 |
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167 public final LoopBeginNode loopBegin; |
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168 |
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169 public final NodeMap<Set<LoopInfo>> requires; |
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170 |
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171 private double loopFrequency = -1; |
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172 public boolean ended = false; |
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173 |
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174 public LoopInfo(LoopBeginNode loopBegin) { |
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175 this.loopBegin = loopBegin; |
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176 this.requires = loopBegin.graph().createNodeMap(); |
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177 } |
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178 |
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179 public double loopFrequency(NodesToDoubles nodeProbabilities) { |
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180 if (loopFrequency == -1 && ended) { |
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181 double backEdgeProb = 0.0; |
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182 for (LoopEndNode le : loopBegin.loopEnds()) { |
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183 double factor = 1; |
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184 Set<LoopInfo> requireds = requires.get(le); |
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185 for (LoopInfo required : requireds) { |
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186 double t = required.loopFrequency(nodeProbabilities); |
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187 if (t == -1) { |
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188 return -1; |
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189 } |
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190 factor *= t; |
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191 } |
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192 backEdgeProb += nodeProbabilities.get(le) * factor; |
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193 } |
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194 double entryProb = nodeProbabilities.get(loopBegin); |
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195 double d = entryProb - backEdgeProb; |
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196 if (d <= EPSILON) { |
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197 d = EPSILON; |
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198 } |
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199 loopFrequency = entryProb / d; |
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200 loopBegin.setLoopFrequency(loopFrequency); |
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201 } |
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202 return loopFrequency; |
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203 } |
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204 } |
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205 |
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206 private class Probability extends MergeableState<Probability> { |
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207 |
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208 public double probability; |
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209 public HashSet<LoopInfo> loops; |
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210 public LoopInfo loopInfo; |
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211 |
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212 public Probability(double probability, HashSet<LoopInfo> loops) { |
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213 assert probability >= 0.0; |
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214 this.probability = probability; |
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215 this.loops = new HashSet<>(4); |
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216 if (loops != null) { |
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217 this.loops.addAll(loops); |
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218 } |
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219 } |
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220 |
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221 @Override |
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222 public Probability clone() { |
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223 return new Probability(probability, loops); |
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224 } |
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225 |
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226 @Override |
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227 public boolean merge(MergeNode merge, List<Probability> withStates) { |
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228 if (merge.forwardEndCount() > 1) { |
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229 HashSet<LoopInfo> intersection = new HashSet<>(loops); |
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230 for (Probability other : withStates) { |
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231 intersection.retainAll(other.loops); |
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232 } |
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233 for (LoopInfo info : loops) { |
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234 if (!intersection.contains(info)) { |
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235 double loopFrequency = info.loopFrequency(nodeProbabilities); |
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236 if (loopFrequency == -1) { |
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237 return false; |
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238 } |
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239 probability *= loopFrequency; |
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240 assert probability >= 0; |
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241 } |
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242 } |
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243 for (Probability other : withStates) { |
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244 double prob = other.probability; |
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245 for (LoopInfo info : other.loops) { |
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246 if (!intersection.contains(info)) { |
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247 double loopFrequency = info.loopFrequency(nodeProbabilities); |
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248 if (loopFrequency == -1) { |
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249 return false; |
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250 } |
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251 prob *= loopFrequency; |
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252 assert prob >= 0; |
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253 } |
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254 } |
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255 probability += prob; |
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256 assert probability >= 0; |
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257 } |
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258 loops = intersection; |
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259 mergeLoops.put(merge, new HashSet<>(intersection)); |
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260 probability = Math.max(0.0, probability); |
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261 } |
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262 return true; |
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263 } |
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264 |
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265 @Override |
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266 public void loopBegin(LoopBeginNode loopBegin) { |
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267 loopInfo = new LoopInfo(loopBegin); |
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268 loopInfos.add(loopInfo); |
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269 loops.add(loopInfo); |
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270 } |
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271 |
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272 @Override |
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273 public void loopEnds(LoopBeginNode loopBegin, List<Probability> loopEndStates) { |
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274 assert loopInfo != null; |
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275 List<LoopEndNode> loopEnds = loopBegin.orderedLoopEnds(); |
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276 int i = 0; |
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277 for (Probability proba : loopEndStates) { |
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278 LoopEndNode loopEnd = loopEnds.get(i++); |
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279 Set<LoopInfo> requires = loopInfo.requires.get(loopEnd); |
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280 if (requires == null) { |
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281 requires = new HashSet<>(); |
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282 loopInfo.requires.set(loopEnd, requires); |
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283 } |
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284 for (LoopInfo innerLoop : proba.loops) { |
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285 if (innerLoop != loopInfo && !this.loops.contains(innerLoop)) { |
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286 requires.add(innerLoop); |
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287 } |
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288 } |
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289 } |
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290 loopInfo.ended = true; |
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291 } |
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292 |
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293 @Override |
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294 public void afterSplit(AbstractBeginNode node) { |
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295 assert node.predecessor() != null; |
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296 Node pred = node.predecessor(); |
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297 ControlSplitNode x = (ControlSplitNode) pred; |
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298 double nodeProbability = x.probability(node); |
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299 assert nodeProbability >= 0.0 : "Node " + x + " provided negative probability for begin " + node + ": " + nodeProbability; |
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300 probability *= nodeProbability; |
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301 assert probability >= 0.0; |
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302 } |
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303 } |
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304 |
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305 private class PropagateProbability extends PostOrderNodeIterator<Probability> { |
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306 |
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307 public PropagateProbability(FixedNode start) { |
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308 super(start, new Probability(1d, null)); |
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309 } |
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310 |
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|
311 @Override |
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312 protected void node(FixedNode node) { |
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313 nodeProbabilities.put(node, state.probability); |
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314 } |
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315 } |
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316 |
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317 private class LoopCount extends MergeableState<LoopCount> { |
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318 |
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319 public double count; |
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320 |
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321 public LoopCount(double count) { |
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322 this.count = count; |
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323 } |
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324 |
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|
325 @Override |
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326 public LoopCount clone() { |
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327 return new LoopCount(count); |
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|
328 } |
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329 |
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330 @Override |
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331 public boolean merge(MergeNode merge, List<LoopCount> withStates) { |
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|
332 assert merge.forwardEndCount() == withStates.size() + 1; |
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|
333 if (merge.forwardEndCount() > 1) { |
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|
334 Set<LoopInfo> loops = mergeLoops.get(merge); |
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|
335 assert loops != null; |
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|
336 double countProd = 1; |
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|
337 for (LoopInfo loop : loops) { |
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|
338 countProd *= loop.loopFrequency(nodeProbabilities); |
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|
339 } |
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|
340 count = countProd; |
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|
341 } |
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|
342 return true; |
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|
343 } |
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344 |
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|
345 @Override |
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346 public void loopBegin(LoopBeginNode loopBegin) { |
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347 count *= loopBegin.loopFrequency(); |
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348 } |
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349 } |
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350 |
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351 private class PropagateLoopFrequency extends PostOrderNodeIterator<LoopCount> { |
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352 |
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353 public PropagateLoopFrequency(FixedNode start) { |
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354 super(start, new LoopCount(1d)); |
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355 } |
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356 |
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357 @Override |
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358 protected void node(FixedNode node) { |
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359 nodeProbabilities.put(node, nodeProbabilities.get(node) * state.count); |
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360 } |
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361 |
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362 } |
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363 } |