1 //===- unittest/Support/BranchProbabilityTest.cpp - BranchProbability tests -=// 2 // 3 // The LLVM Compiler Infrastructure 4 // 5 // This file is distributed under the University of Illinois Open Source 6 // License. See LICENSE.TXT for details. 7 // 8 //===----------------------------------------------------------------------===// 9 10 #include "llvm/Support/BranchProbability.h" 11 #include "llvm/Support/raw_ostream.h" 12 #include "gtest/gtest.h" 13 14 using namespace llvm; 15 16 namespace llvm { 17 void PrintTo(BranchProbability P, ::std::ostream *os) { 18 *os << P.getNumerator() << "/" << P.getDenominator(); 19 } 20 } 21 namespace { 22 23 typedef BranchProbability BP; 24 TEST(BranchProbabilityTest, Accessors) { 25 EXPECT_EQ(306783378u, BP(1, 7).getNumerator()); 26 EXPECT_EQ(1u << 31, BP(1, 7).getDenominator()); 27 EXPECT_EQ(0u, BP::getZero().getNumerator()); 28 EXPECT_EQ(1u << 31, BP::getZero().getDenominator()); 29 EXPECT_EQ(1u << 31, BP::getOne().getNumerator()); 30 EXPECT_EQ(1u << 31, BP::getOne().getDenominator()); 31 } 32 33 TEST(BranchProbabilityTest, Operators) { 34 EXPECT_TRUE(BP(1, 7) < BP(2, 7)); 35 EXPECT_TRUE(BP(1, 7) < BP(1, 4)); 36 EXPECT_TRUE(BP(5, 7) < BP(3, 4)); 37 EXPECT_FALSE(BP(1, 7) < BP(1, 7)); 38 EXPECT_FALSE(BP(1, 7) < BP(2, 14)); 39 EXPECT_FALSE(BP(4, 7) < BP(1, 2)); 40 EXPECT_FALSE(BP(4, 7) < BP(3, 7)); 41 42 EXPECT_FALSE(BP(1, 7) > BP(2, 7)); 43 EXPECT_FALSE(BP(1, 7) > BP(1, 4)); 44 EXPECT_FALSE(BP(5, 7) > BP(3, 4)); 45 EXPECT_FALSE(BP(1, 7) > BP(1, 7)); 46 EXPECT_FALSE(BP(1, 7) > BP(2, 14)); 47 EXPECT_TRUE(BP(4, 7) > BP(1, 2)); 48 EXPECT_TRUE(BP(4, 7) > BP(3, 7)); 49 50 EXPECT_TRUE(BP(1, 7) <= BP(2, 7)); 51 EXPECT_TRUE(BP(1, 7) <= BP(1, 4)); 52 EXPECT_TRUE(BP(5, 7) <= BP(3, 4)); 53 EXPECT_TRUE(BP(1, 7) <= BP(1, 7)); 54 EXPECT_TRUE(BP(1, 7) <= BP(2, 14)); 55 EXPECT_FALSE(BP(4, 7) <= BP(1, 2)); 56 EXPECT_FALSE(BP(4, 7) <= BP(3, 7)); 57 58 EXPECT_FALSE(BP(1, 7) >= BP(2, 7)); 59 EXPECT_FALSE(BP(1, 7) >= BP(1, 4)); 60 EXPECT_FALSE(BP(5, 7) >= BP(3, 4)); 61 EXPECT_TRUE(BP(1, 7) >= BP(1, 7)); 62 EXPECT_TRUE(BP(1, 7) >= BP(2, 14)); 63 EXPECT_TRUE(BP(4, 7) >= BP(1, 2)); 64 EXPECT_TRUE(BP(4, 7) >= BP(3, 7)); 65 66 EXPECT_FALSE(BP(1, 7) == BP(2, 7)); 67 EXPECT_FALSE(BP(1, 7) == BP(1, 4)); 68 EXPECT_FALSE(BP(5, 7) == BP(3, 4)); 69 EXPECT_TRUE(BP(1, 7) == BP(1, 7)); 70 EXPECT_TRUE(BP(1, 7) == BP(2, 14)); 71 EXPECT_FALSE(BP(4, 7) == BP(1, 2)); 72 EXPECT_FALSE(BP(4, 7) == BP(3, 7)); 73 74 EXPECT_TRUE(BP(1, 7) != BP(2, 7)); 75 EXPECT_TRUE(BP(1, 7) != BP(1, 4)); 76 EXPECT_TRUE(BP(5, 7) != BP(3, 4)); 77 EXPECT_FALSE(BP(1, 7) != BP(1, 7)); 78 EXPECT_FALSE(BP(1, 7) != BP(2, 14)); 79 EXPECT_TRUE(BP(4, 7) != BP(1, 2)); 80 EXPECT_TRUE(BP(4, 7) != BP(3, 7)); 81 82 EXPECT_TRUE(BP(1, 7) == BP(2, 14)); 83 EXPECT_TRUE(BP(1, 7) == BP(3, 21)); 84 EXPECT_TRUE(BP(5, 7) == BP(25, 35)); 85 EXPECT_TRUE(BP(99999998, 100000000) < BP(99999999, 100000000)); 86 EXPECT_TRUE(BP(4, 8) == BP(400000000, 800000000)); 87 } 88 89 TEST(BranchProbabilityTest, MoreOperators) { 90 BP A(4, 5); 91 BP B(4U << 29, 5U << 29); 92 BP C(3, 4); 93 94 EXPECT_TRUE(A == B); 95 EXPECT_FALSE(A != B); 96 EXPECT_FALSE(A < B); 97 EXPECT_FALSE(A > B); 98 EXPECT_TRUE(A <= B); 99 EXPECT_TRUE(A >= B); 100 101 EXPECT_FALSE(B == C); 102 EXPECT_TRUE(B != C); 103 EXPECT_FALSE(B < C); 104 EXPECT_TRUE(B > C); 105 EXPECT_FALSE(B <= C); 106 EXPECT_TRUE(B >= C); 107 108 BP BigZero(0, UINT32_MAX); 109 BP BigOne(UINT32_MAX, UINT32_MAX); 110 EXPECT_FALSE(BigZero == BigOne); 111 EXPECT_TRUE(BigZero != BigOne); 112 EXPECT_TRUE(BigZero < BigOne); 113 EXPECT_FALSE(BigZero > BigOne); 114 EXPECT_TRUE(BigZero <= BigOne); 115 EXPECT_FALSE(BigZero >= BigOne); 116 } 117 118 TEST(BranchProbabilityTest, getCompl) { 119 EXPECT_EQ(BP(5, 7), BP(2, 7).getCompl()); 120 EXPECT_EQ(BP(2, 7), BP(5, 7).getCompl()); 121 EXPECT_EQ(BP::getZero(), BP(7, 7).getCompl()); 122 EXPECT_EQ(BP::getOne(), BP(0, 7).getCompl()); 123 } 124 125 TEST(BranchProbabilityTest, scale) { 126 // Multiply by 1.0. 127 EXPECT_EQ(UINT64_MAX, BP(1, 1).scale(UINT64_MAX)); 128 EXPECT_EQ(UINT64_MAX, BP(7, 7).scale(UINT64_MAX)); 129 EXPECT_EQ(UINT32_MAX, BP(1, 1).scale(UINT32_MAX)); 130 EXPECT_EQ(UINT32_MAX, BP(7, 7).scale(UINT32_MAX)); 131 EXPECT_EQ(0u, BP(1, 1).scale(0)); 132 EXPECT_EQ(0u, BP(7, 7).scale(0)); 133 134 // Multiply by 0.0. 135 EXPECT_EQ(0u, BP(0, 1).scale(UINT64_MAX)); 136 EXPECT_EQ(0u, BP(0, 1).scale(UINT64_MAX)); 137 EXPECT_EQ(0u, BP(0, 1).scale(0)); 138 139 auto Two63 = UINT64_C(1) << 63; 140 auto Two31 = UINT64_C(1) << 31; 141 142 // Multiply by 0.5. 143 EXPECT_EQ(Two63 - 1, BP(1, 2).scale(UINT64_MAX)); 144 145 // Big fractions. 146 EXPECT_EQ(1u, BP(Two31, UINT32_MAX).scale(2)); 147 EXPECT_EQ(Two31, BP(Two31, UINT32_MAX).scale(Two31 * 2)); 148 EXPECT_EQ(9223372036854775807ULL, BP(Two31, UINT32_MAX).scale(UINT64_MAX)); 149 150 // High precision. 151 EXPECT_EQ(UINT64_C(9223372045444710399), 152 BP(Two31 + 1, UINT32_MAX - 2).scale(UINT64_MAX)); 153 } 154 155 TEST(BranchProbabilityTest, scaleByInverse) { 156 // Divide by 1.0. 157 EXPECT_EQ(UINT64_MAX, BP(1, 1).scaleByInverse(UINT64_MAX)); 158 EXPECT_EQ(UINT64_MAX, BP(7, 7).scaleByInverse(UINT64_MAX)); 159 EXPECT_EQ(UINT32_MAX, BP(1, 1).scaleByInverse(UINT32_MAX)); 160 EXPECT_EQ(UINT32_MAX, BP(7, 7).scaleByInverse(UINT32_MAX)); 161 EXPECT_EQ(0u, BP(1, 1).scaleByInverse(0)); 162 EXPECT_EQ(0u, BP(7, 7).scaleByInverse(0)); 163 164 auto MAX_DENOMINATOR = BP::getDenominator(); 165 166 // Divide by something very small. 167 EXPECT_EQ(UINT64_MAX, BP(1, UINT32_MAX).scaleByInverse(UINT64_MAX)); 168 EXPECT_EQ(uint64_t(UINT32_MAX) * MAX_DENOMINATOR, 169 BP(1, MAX_DENOMINATOR).scaleByInverse(UINT32_MAX)); 170 EXPECT_EQ(MAX_DENOMINATOR, BP(1, MAX_DENOMINATOR).scaleByInverse(1)); 171 172 auto Two63 = UINT64_C(1) << 63; 173 auto Two31 = UINT64_C(1) << 31; 174 175 // Divide by 0.5. 176 EXPECT_EQ(UINT64_MAX - 1, BP(1, 2).scaleByInverse(Two63 - 1)); 177 EXPECT_EQ(UINT64_MAX, BP(1, 2).scaleByInverse(Two63)); 178 179 // Big fractions. 180 EXPECT_EQ(2u, BP(Two31, UINT32_MAX).scaleByInverse(1)); 181 EXPECT_EQ(2u, BP(Two31 - 1, UINT32_MAX).scaleByInverse(1)); 182 EXPECT_EQ(Two31 * 2, BP(Two31, UINT32_MAX).scaleByInverse(Two31)); 183 EXPECT_EQ(Two31 * 2, BP(Two31 - 1, UINT32_MAX).scaleByInverse(Two31)); 184 EXPECT_EQ(UINT64_MAX, BP(Two31, UINT32_MAX).scaleByInverse(Two63 + Two31)); 185 186 // High precision. The exact answers to these are close to the successors of 187 // the floor. If we were rounding, these would round up. 188 EXPECT_EQ(UINT64_C(18446744060824649767), 189 BP(Two31 + 2, UINT32_MAX - 2) 190 .scaleByInverse(UINT64_C(9223372047592194056))); 191 EXPECT_EQ(UINT64_C(18446744060824649739), 192 BP(Two31 + 1, UINT32_MAX).scaleByInverse(Two63 + Two31)); 193 } 194 195 TEST(BranchProbabilityTest, scaleBruteForce) { 196 struct { 197 uint64_t Num; 198 uint32_t Prob[2]; 199 uint64_t Result; 200 } Tests[] = { 201 // Data for scaling that results in <= 64 bit division. 202 { 0x1423e2a50ULL, { 0x64819521, 0x7765dd13 }, 0x10f418888ULL }, 203 { 0x35ef14ceULL, { 0x28ade3c7, 0x304532ae }, 0x2d73c33bULL }, 204 { 0xd03dbfbe24ULL, { 0x790079, 0xe419f3 }, 0x6e776fc2c4ULL }, 205 { 0x21d67410bULL, { 0x302a9dc2, 0x3ddb4442 }, 0x1a5948fd4ULL }, 206 { 0x8664aeadULL, { 0x3d523513, 0x403523b1 }, 0x805a04cfULL }, 207 { 0x201db0cf4ULL, { 0x35112a7b, 0x79fc0c74 }, 0xdf8b07f8ULL }, 208 { 0x13f1e4430aULL, { 0x21c92bf, 0x21e63aae }, 0x13e0cba26ULL }, 209 { 0x16c83229ULL, { 0x3793f66f, 0x53180dea }, 0xf3ce7b6ULL }, 210 { 0xc62415be8ULL, { 0x9cc4a63, 0x4327ae9b }, 0x1ce8b71c1ULL }, 211 { 0x6fac5e434ULL, { 0xe5f9170, 0x1115e10b }, 0x5df23dd4cULL }, 212 { 0x1929375f2ULL, { 0x3a851375, 0x76c08456 }, 0xc662b083ULL }, 213 { 0x243c89db6ULL, { 0x354ebfc0, 0x450ef197 }, 0x1bf8c1663ULL }, 214 { 0x310e9b31aULL, { 0x1b1b8acf, 0x2d3629f0 }, 0x1d69c93f9ULL }, 215 { 0xa1fae921dULL, { 0xa7a098c, 0x10469f44 }, 0x684413d6eULL }, 216 { 0xc1582d957ULL, { 0x498e061, 0x59856bc }, 0x9edc5f4ecULL }, 217 { 0x57cfee75ULL, { 0x1d061dc3, 0x7c8bfc17 }, 0x1476a220ULL }, 218 { 0x139220080ULL, { 0x294a6c71, 0x2a2b07c9 }, 0x1329e1c75ULL }, 219 { 0x1665d353cULL, { 0x7080db5, 0xde0d75c }, 0xb590d9faULL }, 220 { 0xe8f14541ULL, { 0x5188e8b2, 0x736527ef }, 0xa4971be5ULL }, 221 { 0x2f4775f29ULL, { 0x254ef0fe, 0x435fcf50 }, 0x1a2e449c1ULL }, 222 { 0x27b85d8d7ULL, { 0x304c8220, 0x5de678f2 }, 0x146e3befbULL }, 223 { 0x1d362e36bULL, { 0x36c85b12, 0x37a66f55 }, 0x1cc19b8e7ULL }, 224 { 0x155fd48c7ULL, { 0xf5894d, 0x1256108 }, 0x11e383604ULL }, 225 { 0xb5db2d15ULL, { 0x39bb26c5, 0x5bdcda3e }, 0x72499259ULL }, 226 { 0x153990298ULL, { 0x48921c09, 0x706eb817 }, 0xdb3268e7ULL }, 227 { 0x28a7c3ed7ULL, { 0x1f776fd7, 0x349f7a70 }, 0x184f73ae2ULL }, 228 { 0x724dbeabULL, { 0x1bd149f5, 0x253a085e }, 0x5569c0b3ULL }, 229 { 0xd8f0c513ULL, { 0x18c8cc4c, 0x1b72bad0 }, 0xc3e30642ULL }, 230 { 0x17ce3dcbULL, { 0x1e4c6260, 0x233b359e }, 0x1478f4afULL }, 231 { 0x1ce036ce0ULL, { 0x29e3c8af, 0x5318dd4a }, 0xe8e76195ULL }, 232 { 0x1473ae2aULL, { 0x29b897ba, 0x2be29378 }, 0x13718185ULL }, 233 { 0x1dd41aa68ULL, { 0x3d0a4441, 0x5a0e8f12 }, 0x1437b6bbfULL }, 234 { 0x1b49e4a53ULL, { 0x3430c1fe, 0x5a204aed }, 0xfcd6852fULL }, 235 { 0x217941b19ULL, { 0x12ced2bd, 0x21b68310 }, 0x12aca65b1ULL }, 236 { 0xac6a4dc8ULL, { 0x3ed68da8, 0x6fdca34c }, 0x60da926dULL }, 237 { 0x1c503a4e7ULL, { 0xfcbbd32, 0x11e48d17 }, 0x18fec7d37ULL }, 238 { 0x1c885855ULL, { 0x213e919d, 0x25941897 }, 0x193de742ULL }, 239 { 0x29b9c168eULL, { 0x2b644aea, 0x45725ee7 }, 0x1a122e5d4ULL }, 240 { 0x806a33f2ULL, { 0x30a80a23, 0x5063733a }, 0x4db9a264ULL }, 241 { 0x282afc96bULL, { 0x143ae554, 0x1a9863ff }, 0x1e8de5204ULL }, 242 // Data for scaling that results in > 64 bit division. 243 { 0x23ca5f2f672ca41cULL, { 0xecbc641, 0x111373f7 }, 0x1f0301e5c76869c6ULL }, 244 { 0x5e4f2468142265e3ULL, { 0x1ddf5837, 0x32189233 }, 0x383ca7bad6053ac9ULL }, 245 { 0x277a1a6f6b266bf6ULL, { 0x415d81a8, 0x61eb5e1e }, 0x1a5a3e1d1c9e8540ULL }, 246 { 0x1bdbb49a237035cbULL, { 0xea5bf17, 0x1d25ffb3 }, 0xdffc51c5cb51cf1ULL }, 247 { 0x2bce6d29b64fb8ULL, { 0x3bfd5631, 0x7525c9bb }, 0x166ebedd9581fdULL }, 248 { 0x3a02116103df5013ULL, { 0x2ee18a83, 0x3299aea8 }, 0x35be89227276f105ULL }, 249 { 0x7b5762390799b18cULL, { 0x12f8e5b9, 0x2563bcd4 }, 0x3e960077695655a3ULL }, 250 { 0x69cfd72537021579ULL, { 0x4c35f468, 0x6a40feee }, 0x4be4cb38695a4f30ULL }, 251 { 0x49dfdf835120f1c1ULL, { 0x8cb3759, 0x559eb891 }, 0x79663f6e3c8d8f6ULL }, 252 { 0x74b5be5c27676381ULL, { 0x47e4c5e0, 0x7c7b19ff }, 0x4367d2dfb22b3265ULL }, 253 { 0x4f50f97075e7f431ULL, { 0x9a50a17, 0x11cd1185 }, 0x2af952b30374f382ULL }, 254 { 0x2f8b0d712e393be4ULL, { 0x1487e386, 0x15aa356e }, 0x2d0df3649b2b19fcULL }, 255 { 0x224c1c75999d3deULL, { 0x3b2df0ea, 0x4523b100 }, 0x1d5b481d160dd8bULL }, 256 { 0x2bcbcea22a399a76ULL, { 0x28b58212, 0x48dd013e }, 0x187814d0610c8a56ULL }, 257 { 0x1dbfca91257cb2d1ULL, { 0x1a8c04d9, 0x5e92502c }, 0x859cf7d19e83ad0ULL }, 258 { 0x7f20039b57cda935ULL, { 0xeccf651, 0x323f476e }, 0x25720cd9054634bdULL }, 259 { 0x40512c6a586aa087ULL, { 0x113b0423, 0x398c9eab }, 0x1341c03dbb662054ULL }, 260 { 0x63d802693f050a11ULL, { 0xf50cdd6, 0xfce2a44 }, 0x60c0177b667a4feaULL }, 261 { 0x2d956b422838de77ULL, { 0xb2d345b, 0x1321e557 }, 0x1aa0ed16b094575cULL }, 262 { 0x5a1cdf0c1657bc91ULL, { 0x1d77bb0c, 0x1f991ff1 }, 0x54097ee9907290eaULL }, 263 { 0x3801b26d7e00176bULL, { 0xeed25da, 0x1a819d8b }, 0x1f89e96a616b9abeULL }, 264 { 0x37655e74338e1e45ULL, { 0x300e170a, 0x5a1595fe }, 0x1d8cfb55ff6a6dbcULL }, 265 { 0x7b38703f2a84e6ULL, { 0x66d9053, 0xc79b6b9 }, 0x3f7d4c91b9afb9ULL }, 266 { 0x2245063c0acb3215ULL, { 0x30ce2f5b, 0x610e7271 }, 0x113b916455fe2560ULL }, 267 { 0x6bc195877b7b8a7eULL, { 0x392004aa, 0x4a24e60c }, 0x530594fabfc81cc3ULL }, 268 { 0x40a3fde23c7b43dbULL, { 0x4e712195, 0x6553e56e }, 0x320a799bc205c78dULL }, 269 { 0x1d3dfc2866fbccbaULL, { 0x5075b517, 0x5fc42245 }, 0x18917f00745cb781ULL }, 270 { 0x19aeb14045a61121ULL, { 0x1bf6edec, 0x707e2f4b }, 0x6626672aa2ba10aULL }, 271 { 0x44ff90486c531e9fULL, { 0x66598a, 0x8a90dc }, 0x32f6f2b097001598ULL }, 272 { 0x3f3e7121092c5bcbULL, { 0x1c754df7, 0x5951a1b9 }, 0x14267f50d4971583ULL }, 273 { 0x60e2dafb7e50a67eULL, { 0x4d96c66e, 0x65bd878d }, 0x49e317155d75e883ULL }, 274 { 0x656286667e0e6e29ULL, { 0x9d971a2, 0xacda23b }, 0x5c6ee3159e1deac3ULL }, 275 { 0x1114e0974255d507ULL, { 0x1c693, 0x2d6ff }, 0xaae42e4be5f9f8dULL }, 276 { 0x508c8baf3a70ff5aULL, { 0x3b26b779, 0x6ad78745 }, 0x2c983876178ed5b1ULL }, 277 { 0x5b47bc666bf1f9cfULL, { 0x10a87ed6, 0x187d358a }, 0x3e1767153bea720aULL }, 278 { 0x50954e3744460395ULL, { 0x7a42263, 0xcdaa048 }, 0x2fe739f0944a023cULL }, 279 { 0x20020b406550dd8fULL, { 0x3318539, 0x42eead0 }, 0x186f326307c0d985ULL }, 280 { 0x5bcb0b872439ffd5ULL, { 0x6f61fb2, 0x9af7344 }, 0x41fa1e3c47f0f80dULL }, 281 { 0x7a670f365db87a53ULL, { 0x417e102, 0x3bb54c67 }, 0x8642a551d0f41b0ULL }, 282 { 0x1ef0db1e7bab1cd0ULL, { 0x2b60cf38, 0x4188f78f }, 0x147ae0d63fc0575aULL } 283 }; 284 285 for (const auto &T : Tests) { 286 EXPECT_EQ(T.Result, BP(T.Prob[0], T.Prob[1]).scale(T.Num)); 287 } 288 } 289 290 TEST(BranchProbabilityTest, NormalizeProbabilities) { 291 const auto UnknownProb = BranchProbability::getUnknown(); 292 { 293 SmallVector<BranchProbability, 2> Probs{{0, 1}, {0, 1}}; 294 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 295 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[0].getNumerator()); 296 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[1].getNumerator()); 297 } 298 { 299 SmallVector<BranchProbability, 2> Probs{{0, 1}, {1, 1}}; 300 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 301 EXPECT_EQ(0u, Probs[0].getNumerator()); 302 EXPECT_EQ(BranchProbability::getDenominator(), Probs[1].getNumerator()); 303 } 304 { 305 SmallVector<BranchProbability, 2> Probs{{1, 100}, {1, 100}}; 306 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 307 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[0].getNumerator()); 308 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[1].getNumerator()); 309 } 310 { 311 SmallVector<BranchProbability, 2> Probs{{1, 1}, {1, 1}}; 312 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 313 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[0].getNumerator()); 314 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[1].getNumerator()); 315 } 316 { 317 SmallVector<BranchProbability, 3> Probs{{1, 1}, {1, 1}, {1, 1}}; 318 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 319 EXPECT_EQ(BranchProbability::getDenominator() / 3 + 1, 320 Probs[0].getNumerator()); 321 EXPECT_EQ(BranchProbability::getDenominator() / 3 + 1, 322 Probs[1].getNumerator()); 323 EXPECT_EQ(BranchProbability::getDenominator() / 3 + 1, 324 Probs[2].getNumerator()); 325 } 326 { 327 SmallVector<BranchProbability, 2> Probs{{0, 1}, UnknownProb}; 328 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 329 EXPECT_EQ(0U, Probs[0].getNumerator()); 330 EXPECT_EQ(BranchProbability::getDenominator(), Probs[1].getNumerator()); 331 } 332 { 333 SmallVector<BranchProbability, 2> Probs{{1, 1}, UnknownProb}; 334 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 335 EXPECT_EQ(BranchProbability::getDenominator(), Probs[0].getNumerator()); 336 EXPECT_EQ(0U, Probs[1].getNumerator()); 337 } 338 { 339 SmallVector<BranchProbability, 2> Probs{{1, 2}, UnknownProb}; 340 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 341 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[0].getNumerator()); 342 EXPECT_EQ(BranchProbability::getDenominator() / 2, Probs[1].getNumerator()); 343 } 344 { 345 SmallVector<BranchProbability, 4> Probs{ 346 {1, 2}, {1, 2}, {1, 2}, UnknownProb}; 347 BranchProbability::normalizeProbabilities(Probs.begin(), Probs.end()); 348 EXPECT_EQ(BranchProbability::getDenominator() / 3 + 1, 349 Probs[0].getNumerator()); 350 EXPECT_EQ(BranchProbability::getDenominator() / 3 + 1, 351 Probs[1].getNumerator()); 352 EXPECT_EQ(BranchProbability::getDenominator() / 3 + 1, 353 Probs[2].getNumerator()); 354 EXPECT_EQ(0U, Probs[3].getNumerator()); 355 } 356 } 357 358 } 359
