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14 | pmbaty | 1 | //===- llvm/ADT/SparseSet.h - Sparse set ------------------------*- C++ -*-===// |
2 | // |
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3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
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4 | // See https://llvm.org/LICENSE.txt for license information. |
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5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
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6 | // |
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7 | //===----------------------------------------------------------------------===// |
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8 | /// |
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9 | /// \file |
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10 | /// This file defines the SparseSet class derived from the version described in |
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11 | /// Briggs, Torczon, "An efficient representation for sparse sets", ACM Letters |
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12 | /// on Programming Languages and Systems, Volume 2 Issue 1-4, March-Dec. 1993. |
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13 | /// |
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14 | /// A sparse set holds a small number of objects identified by integer keys from |
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15 | /// a moderately sized universe. The sparse set uses more memory than other |
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16 | /// containers in order to provide faster operations. |
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17 | /// |
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18 | //===----------------------------------------------------------------------===// |
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19 | |||
20 | #ifndef LLVM_ADT_SPARSESET_H |
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21 | #define LLVM_ADT_SPARSESET_H |
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22 | |||
23 | #include "llvm/ADT/identity.h" |
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24 | #include "llvm/ADT/SmallVector.h" |
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25 | #include "llvm/Support/AllocatorBase.h" |
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26 | #include <cassert> |
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27 | #include <cstdint> |
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28 | #include <cstdlib> |
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29 | #include <limits> |
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30 | #include <utility> |
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31 | |||
32 | namespace llvm { |
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33 | |||
34 | /// SparseSetValTraits - Objects in a SparseSet are identified by keys that can |
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35 | /// be uniquely converted to a small integer less than the set's universe. This |
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36 | /// class allows the set to hold values that differ from the set's key type as |
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37 | /// long as an index can still be derived from the value. SparseSet never |
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38 | /// directly compares ValueT, only their indices, so it can map keys to |
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39 | /// arbitrary values. SparseSetValTraits computes the index from the value |
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40 | /// object. To compute the index from a key, SparseSet uses a separate |
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41 | /// KeyFunctorT template argument. |
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42 | /// |
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43 | /// A simple type declaration, SparseSet<Type>, handles these cases: |
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44 | /// - unsigned key, identity index, identity value |
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45 | /// - unsigned key, identity index, fat value providing getSparseSetIndex() |
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46 | /// |
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47 | /// The type declaration SparseSet<Type, UnaryFunction> handles: |
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48 | /// - unsigned key, remapped index, identity value (virtual registers) |
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49 | /// - pointer key, pointer-derived index, identity value (node+ID) |
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50 | /// - pointer key, pointer-derived index, fat value with getSparseSetIndex() |
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51 | /// |
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52 | /// Only other, unexpected cases require specializing SparseSetValTraits. |
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53 | /// |
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54 | /// For best results, ValueT should not require a destructor. |
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55 | /// |
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56 | template<typename ValueT> |
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57 | struct SparseSetValTraits { |
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58 | static unsigned getValIndex(const ValueT &Val) { |
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59 | return Val.getSparseSetIndex(); |
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60 | } |
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61 | }; |
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62 | |||
63 | /// SparseSetValFunctor - Helper class for selecting SparseSetValTraits. The |
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64 | /// generic implementation handles ValueT classes which either provide |
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65 | /// getSparseSetIndex() or specialize SparseSetValTraits<>. |
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66 | /// |
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67 | template<typename KeyT, typename ValueT, typename KeyFunctorT> |
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68 | struct SparseSetValFunctor { |
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69 | unsigned operator()(const ValueT &Val) const { |
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70 | return SparseSetValTraits<ValueT>::getValIndex(Val); |
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71 | } |
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72 | }; |
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73 | |||
74 | /// SparseSetValFunctor<KeyT, KeyT> - Helper class for the common case of |
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75 | /// identity key/value sets. |
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76 | template<typename KeyT, typename KeyFunctorT> |
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77 | struct SparseSetValFunctor<KeyT, KeyT, KeyFunctorT> { |
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78 | unsigned operator()(const KeyT &Key) const { |
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79 | return KeyFunctorT()(Key); |
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80 | } |
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81 | }; |
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82 | |||
83 | /// SparseSet - Fast set implementation for objects that can be identified by |
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84 | /// small unsigned keys. |
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85 | /// |
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86 | /// SparseSet allocates memory proportional to the size of the key universe, so |
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87 | /// it is not recommended for building composite data structures. It is useful |
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88 | /// for algorithms that require a single set with fast operations. |
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89 | /// |
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90 | /// Compared to DenseSet and DenseMap, SparseSet provides constant-time fast |
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91 | /// clear() and iteration as fast as a vector. The find(), insert(), and |
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92 | /// erase() operations are all constant time, and typically faster than a hash |
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93 | /// table. The iteration order doesn't depend on numerical key values, it only |
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94 | /// depends on the order of insert() and erase() operations. When no elements |
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95 | /// have been erased, the iteration order is the insertion order. |
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96 | /// |
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97 | /// Compared to BitVector, SparseSet<unsigned> uses 8x-40x more memory, but |
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98 | /// offers constant-time clear() and size() operations as well as fast |
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99 | /// iteration independent on the size of the universe. |
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100 | /// |
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101 | /// SparseSet contains a dense vector holding all the objects and a sparse |
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102 | /// array holding indexes into the dense vector. Most of the memory is used by |
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103 | /// the sparse array which is the size of the key universe. The SparseT |
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104 | /// template parameter provides a space/speed tradeoff for sets holding many |
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105 | /// elements. |
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106 | /// |
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107 | /// When SparseT is uint32_t, find() only touches 2 cache lines, but the sparse |
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108 | /// array uses 4 x Universe bytes. |
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109 | /// |
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110 | /// When SparseT is uint8_t (the default), find() touches up to 2+[N/256] cache |
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111 | /// lines, but the sparse array is 4x smaller. N is the number of elements in |
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112 | /// the set. |
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113 | /// |
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114 | /// For sets that may grow to thousands of elements, SparseT should be set to |
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115 | /// uint16_t or uint32_t. |
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116 | /// |
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117 | /// @tparam ValueT The type of objects in the set. |
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118 | /// @tparam KeyFunctorT A functor that computes an unsigned index from KeyT. |
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119 | /// @tparam SparseT An unsigned integer type. See above. |
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120 | /// |
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121 | template<typename ValueT, |
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122 | typename KeyFunctorT = identity<unsigned>, |
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123 | typename SparseT = uint8_t> |
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124 | class SparseSet { |
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125 | static_assert(std::is_unsigned_v<SparseT>, |
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126 | "SparseT must be an unsigned integer type"); |
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127 | |||
128 | using KeyT = typename KeyFunctorT::argument_type; |
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129 | using DenseT = SmallVector<ValueT, 8>; |
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130 | using size_type = unsigned; |
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131 | DenseT Dense; |
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132 | SparseT *Sparse = nullptr; |
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133 | unsigned Universe = 0; |
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134 | KeyFunctorT KeyIndexOf; |
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135 | SparseSetValFunctor<KeyT, ValueT, KeyFunctorT> ValIndexOf; |
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136 | |||
137 | public: |
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138 | using value_type = ValueT; |
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139 | using reference = ValueT &; |
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140 | using const_reference = const ValueT &; |
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141 | using pointer = ValueT *; |
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142 | using const_pointer = const ValueT *; |
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143 | |||
144 | SparseSet() = default; |
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145 | SparseSet(const SparseSet &) = delete; |
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146 | SparseSet &operator=(const SparseSet &) = delete; |
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147 | ~SparseSet() { free(Sparse); } |
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148 | |||
149 | /// setUniverse - Set the universe size which determines the largest key the |
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150 | /// set can hold. The universe must be sized before any elements can be |
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151 | /// added. |
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152 | /// |
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153 | /// @param U Universe size. All object keys must be less than U. |
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154 | /// |
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155 | void setUniverse(unsigned U) { |
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156 | // It's not hard to resize the universe on a non-empty set, but it doesn't |
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157 | // seem like a likely use case, so we can add that code when we need it. |
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158 | assert(empty() && "Can only resize universe on an empty map"); |
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159 | // Hysteresis prevents needless reallocations. |
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160 | if (U >= Universe/4 && U <= Universe) |
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161 | return; |
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162 | free(Sparse); |
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163 | // The Sparse array doesn't actually need to be initialized, so malloc |
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164 | // would be enough here, but that will cause tools like valgrind to |
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165 | // complain about branching on uninitialized data. |
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166 | Sparse = static_cast<SparseT*>(safe_calloc(U, sizeof(SparseT))); |
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167 | Universe = U; |
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168 | } |
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169 | |||
170 | // Import trivial vector stuff from DenseT. |
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171 | using iterator = typename DenseT::iterator; |
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172 | using const_iterator = typename DenseT::const_iterator; |
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173 | |||
174 | const_iterator begin() const { return Dense.begin(); } |
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175 | const_iterator end() const { return Dense.end(); } |
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176 | iterator begin() { return Dense.begin(); } |
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177 | iterator end() { return Dense.end(); } |
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178 | |||
179 | /// empty - Returns true if the set is empty. |
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180 | /// |
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181 | /// This is not the same as BitVector::empty(). |
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182 | /// |
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183 | bool empty() const { return Dense.empty(); } |
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184 | |||
185 | /// size - Returns the number of elements in the set. |
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186 | /// |
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187 | /// This is not the same as BitVector::size() which returns the size of the |
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188 | /// universe. |
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189 | /// |
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190 | size_type size() const { return Dense.size(); } |
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191 | |||
192 | /// clear - Clears the set. This is a very fast constant time operation. |
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193 | /// |
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194 | void clear() { |
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195 | // Sparse does not need to be cleared, see find(). |
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196 | Dense.clear(); |
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197 | } |
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198 | |||
199 | /// findIndex - Find an element by its index. |
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200 | /// |
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201 | /// @param Idx A valid index to find. |
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202 | /// @returns An iterator to the element identified by key, or end(). |
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203 | /// |
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204 | iterator findIndex(unsigned Idx) { |
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205 | assert(Idx < Universe && "Key out of range"); |
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206 | const unsigned Stride = std::numeric_limits<SparseT>::max() + 1u; |
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207 | for (unsigned i = Sparse[Idx], e = size(); i < e; i += Stride) { |
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208 | const unsigned FoundIdx = ValIndexOf(Dense[i]); |
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209 | assert(FoundIdx < Universe && "Invalid key in set. Did object mutate?"); |
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210 | if (Idx == FoundIdx) |
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211 | return begin() + i; |
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212 | // Stride is 0 when SparseT >= unsigned. We don't need to loop. |
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213 | if (!Stride) |
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214 | break; |
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215 | } |
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216 | return end(); |
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217 | } |
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218 | |||
219 | /// find - Find an element by its key. |
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220 | /// |
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221 | /// @param Key A valid key to find. |
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222 | /// @returns An iterator to the element identified by key, or end(). |
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223 | /// |
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224 | iterator find(const KeyT &Key) { |
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225 | return findIndex(KeyIndexOf(Key)); |
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226 | } |
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227 | |||
228 | const_iterator find(const KeyT &Key) const { |
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229 | return const_cast<SparseSet*>(this)->findIndex(KeyIndexOf(Key)); |
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230 | } |
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231 | |||
232 | /// Check if the set contains the given \c Key. |
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233 | /// |
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234 | /// @param Key A valid key to find. |
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235 | bool contains(const KeyT &Key) const { return find(Key) == end() ? 0 : 1; } |
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236 | |||
237 | /// count - Returns 1 if this set contains an element identified by Key, |
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238 | /// 0 otherwise. |
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239 | /// |
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240 | size_type count(const KeyT &Key) const { return contains(Key) ? 1 : 0; } |
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241 | |||
242 | /// insert - Attempts to insert a new element. |
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243 | /// |
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244 | /// If Val is successfully inserted, return (I, true), where I is an iterator |
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245 | /// pointing to the newly inserted element. |
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246 | /// |
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247 | /// If the set already contains an element with the same key as Val, return |
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248 | /// (I, false), where I is an iterator pointing to the existing element. |
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249 | /// |
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250 | /// Insertion invalidates all iterators. |
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251 | /// |
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252 | std::pair<iterator, bool> insert(const ValueT &Val) { |
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253 | unsigned Idx = ValIndexOf(Val); |
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254 | iterator I = findIndex(Idx); |
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255 | if (I != end()) |
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256 | return std::make_pair(I, false); |
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257 | Sparse[Idx] = size(); |
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258 | Dense.push_back(Val); |
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259 | return std::make_pair(end() - 1, true); |
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260 | } |
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261 | |||
262 | /// array subscript - If an element already exists with this key, return it. |
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263 | /// Otherwise, automatically construct a new value from Key, insert it, |
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264 | /// and return the newly inserted element. |
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265 | ValueT &operator[](const KeyT &Key) { |
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266 | return *insert(ValueT(Key)).first; |
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267 | } |
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268 | |||
269 | ValueT pop_back_val() { |
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270 | // Sparse does not need to be cleared, see find(). |
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271 | return Dense.pop_back_val(); |
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272 | } |
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273 | |||
274 | /// erase - Erases an existing element identified by a valid iterator. |
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275 | /// |
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276 | /// This invalidates all iterators, but erase() returns an iterator pointing |
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277 | /// to the next element. This makes it possible to erase selected elements |
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278 | /// while iterating over the set: |
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279 | /// |
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280 | /// for (SparseSet::iterator I = Set.begin(); I != Set.end();) |
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281 | /// if (test(*I)) |
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282 | /// I = Set.erase(I); |
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283 | /// else |
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284 | /// ++I; |
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285 | /// |
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286 | /// Note that end() changes when elements are erased, unlike std::list. |
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287 | /// |
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288 | iterator erase(iterator I) { |
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289 | assert(unsigned(I - begin()) < size() && "Invalid iterator"); |
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290 | if (I != end() - 1) { |
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291 | *I = Dense.back(); |
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292 | unsigned BackIdx = ValIndexOf(Dense.back()); |
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293 | assert(BackIdx < Universe && "Invalid key in set. Did object mutate?"); |
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294 | Sparse[BackIdx] = I - begin(); |
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295 | } |
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296 | // This depends on SmallVector::pop_back() not invalidating iterators. |
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297 | // std::vector::pop_back() doesn't give that guarantee. |
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298 | Dense.pop_back(); |
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299 | return I; |
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300 | } |
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301 | |||
302 | /// erase - Erases an element identified by Key, if it exists. |
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303 | /// |
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304 | /// @param Key The key identifying the element to erase. |
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305 | /// @returns True when an element was erased, false if no element was found. |
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306 | /// |
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307 | bool erase(const KeyT &Key) { |
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308 | iterator I = find(Key); |
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309 | if (I == end()) |
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310 | return false; |
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311 | erase(I); |
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312 | return true; |
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313 | } |
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314 | }; |
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315 | |||
316 | } // end namespace llvm |
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317 | |||
318 | #endif // LLVM_ADT_SPARSESET_H |