diff options
author | Vincent Ambo <mail@tazj.in> | 2022-02-07T23·05+0300 |
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committer | clbot <clbot@tvl.fyi> | 2022-02-07T23·09+0000 |
commit | 5aa5d282eac56a21e74611c1cdbaa97bb5db2dca (patch) | |
tree | 8cc5dce8157a1470ff76719dd15d65f648a05522 /third_party/abseil_cpp/absl/random/uniform_int_distribution_test.cc | |
parent | a25675804c4f429fab5ee5201fe25e89865dfd13 (diff) |
chore(3p/abseil_cpp): unvendor abseil_cpp r/3786
we weren't actually using these sources anymore, okay? Change-Id: If701571d9716de308d3512e1eb22c35db0877a66 Reviewed-on: https://cl.tvl.fyi/c/depot/+/5248 Tested-by: BuildkiteCI Reviewed-by: grfn <grfn@gws.fyi> Autosubmit: tazjin <tazjin@tvl.su>
Diffstat (limited to 'third_party/abseil_cpp/absl/random/uniform_int_distribution_test.cc')
-rw-r--r-- | third_party/abseil_cpp/absl/random/uniform_int_distribution_test.cc | 259 |
1 files changed, 0 insertions, 259 deletions
diff --git a/third_party/abseil_cpp/absl/random/uniform_int_distribution_test.cc b/third_party/abseil_cpp/absl/random/uniform_int_distribution_test.cc deleted file mode 100644 index 276d72ad2045..000000000000 --- a/third_party/abseil_cpp/absl/random/uniform_int_distribution_test.cc +++ /dev/null @@ -1,259 +0,0 @@ -// Copyright 2017 The Abseil Authors. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// https://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include "absl/random/uniform_int_distribution.h" - -#include <cmath> -#include <cstdint> -#include <iterator> -#include <random> -#include <sstream> -#include <vector> - -#include "gmock/gmock.h" -#include "gtest/gtest.h" -#include "absl/base/internal/raw_logging.h" -#include "absl/random/internal/chi_square.h" -#include "absl/random/internal/distribution_test_util.h" -#include "absl/random/internal/pcg_engine.h" -#include "absl/random/internal/sequence_urbg.h" -#include "absl/random/random.h" -#include "absl/strings/str_cat.h" - -namespace { - -template <typename IntType> -class UniformIntDistributionTest : public ::testing::Test {}; - -using IntTypes = ::testing::Types<int8_t, uint8_t, int16_t, uint16_t, int32_t, - uint32_t, int64_t, uint64_t>; -TYPED_TEST_SUITE(UniformIntDistributionTest, IntTypes); - -TYPED_TEST(UniformIntDistributionTest, ParamSerializeTest) { - // This test essentially ensures that the parameters serialize, - // not that the values generated cover the full range. - using Limits = std::numeric_limits<TypeParam>; - using param_type = - typename absl::uniform_int_distribution<TypeParam>::param_type; - const TypeParam kMin = std::is_unsigned<TypeParam>::value ? 37 : -105; - const TypeParam kNegOneOrZero = std::is_unsigned<TypeParam>::value ? 0 : -1; - - constexpr int kCount = 1000; - absl::InsecureBitGen gen; - for (const auto& param : { - param_type(), - param_type(2, 2), // Same - param_type(9, 32), - param_type(kMin, 115), - param_type(kNegOneOrZero, Limits::max()), - param_type(Limits::min(), Limits::max()), - param_type(Limits::lowest(), Limits::max()), - param_type(Limits::min() + 1, Limits::max() - 1), - }) { - const auto a = param.a(); - const auto b = param.b(); - absl::uniform_int_distribution<TypeParam> before(a, b); - EXPECT_EQ(before.a(), param.a()); - EXPECT_EQ(before.b(), param.b()); - - { - // Initialize via param_type - absl::uniform_int_distribution<TypeParam> via_param(param); - EXPECT_EQ(via_param, before); - } - - // Initialize via iostreams - std::stringstream ss; - ss << before; - - absl::uniform_int_distribution<TypeParam> after(Limits::min() + 3, - Limits::max() - 5); - - EXPECT_NE(before.a(), after.a()); - EXPECT_NE(before.b(), after.b()); - EXPECT_NE(before.param(), after.param()); - EXPECT_NE(before, after); - - ss >> after; - - EXPECT_EQ(before.a(), after.a()); - EXPECT_EQ(before.b(), after.b()); - EXPECT_EQ(before.param(), after.param()); - EXPECT_EQ(before, after); - - // Smoke test. - auto sample_min = after.max(); - auto sample_max = after.min(); - for (int i = 0; i < kCount; i++) { - auto sample = after(gen); - EXPECT_GE(sample, after.min()); - EXPECT_LE(sample, after.max()); - if (sample > sample_max) { - sample_max = sample; - } - if (sample < sample_min) { - sample_min = sample; - } - } - std::string msg = absl::StrCat("Range: ", +sample_min, ", ", +sample_max); - ABSL_RAW_LOG(INFO, "%s", msg.c_str()); - } -} - -TYPED_TEST(UniformIntDistributionTest, ViolatesPreconditionsDeathTest) { -#if GTEST_HAS_DEATH_TEST - // Hi < Lo - EXPECT_DEBUG_DEATH({ absl::uniform_int_distribution<TypeParam> dist(10, 1); }, - ""); -#endif // GTEST_HAS_DEATH_TEST -#if defined(NDEBUG) - // opt-mode, for invalid parameters, will generate a garbage value, - // but should not enter an infinite loop. - absl::InsecureBitGen gen; - absl::uniform_int_distribution<TypeParam> dist(10, 1); - auto x = dist(gen); - - // Any value will generate a non-empty string. - EXPECT_FALSE(absl::StrCat(+x).empty()) << x; -#endif // NDEBUG -} - -TYPED_TEST(UniformIntDistributionTest, TestMoments) { - constexpr int kSize = 100000; - using Limits = std::numeric_limits<TypeParam>; - using param_type = - typename absl::uniform_int_distribution<TypeParam>::param_type; - - // We use a fixed bit generator for distribution accuracy tests. This allows - // these tests to be deterministic, while still testing the qualify of the - // implementation. - absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6}; - - std::vector<double> values(kSize); - for (const auto& param : - {param_type(0, Limits::max()), param_type(13, 127)}) { - absl::uniform_int_distribution<TypeParam> dist(param); - for (int i = 0; i < kSize; i++) { - const auto sample = dist(rng); - ASSERT_LE(dist.param().a(), sample); - ASSERT_GE(dist.param().b(), sample); - values[i] = sample; - } - - auto moments = absl::random_internal::ComputeDistributionMoments(values); - const double a = dist.param().a(); - const double b = dist.param().b(); - const double n = (b - a + 1); - const double mean = (a + b) / 2; - const double var = ((b - a + 1) * (b - a + 1) - 1) / 12; - const double kurtosis = 3 - 6 * (n * n + 1) / (5 * (n * n - 1)); - - // TODO(ahh): this is not the right bound - // empirically validated with --runs_per_test=10000. - EXPECT_NEAR(mean, moments.mean, 0.01 * var); - EXPECT_NEAR(var, moments.variance, 0.015 * var); - EXPECT_NEAR(0.0, moments.skewness, 0.025); - EXPECT_NEAR(kurtosis, moments.kurtosis, 0.02 * kurtosis); - } -} - -TYPED_TEST(UniformIntDistributionTest, ChiSquaredTest50) { - using absl::random_internal::kChiSquared; - - constexpr size_t kTrials = 1000; - constexpr int kBuckets = 50; // inclusive, so actally +1 - constexpr double kExpected = - static_cast<double>(kTrials) / static_cast<double>(kBuckets); - - // Empirically validated with --runs_per_test=10000. - const int kThreshold = - absl::random_internal::ChiSquareValue(kBuckets, 0.999999); - - const TypeParam min = std::is_unsigned<TypeParam>::value ? 37 : -37; - const TypeParam max = min + kBuckets; - - // We use a fixed bit generator for distribution accuracy tests. This allows - // these tests to be deterministic, while still testing the qualify of the - // implementation. - absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6}; - - absl::uniform_int_distribution<TypeParam> dist(min, max); - - std::vector<int32_t> counts(kBuckets + 1, 0); - for (size_t i = 0; i < kTrials; i++) { - auto x = dist(rng); - counts[x - min]++; - } - double chi_square = absl::random_internal::ChiSquareWithExpected( - std::begin(counts), std::end(counts), kExpected); - if (chi_square > kThreshold) { - double p_value = - absl::random_internal::ChiSquarePValue(chi_square, kBuckets); - - // Chi-squared test failed. Output does not appear to be uniform. - std::string msg; - for (const auto& a : counts) { - absl::StrAppend(&msg, a, "\n"); - } - absl::StrAppend(&msg, kChiSquared, " p-value ", p_value, "\n"); - absl::StrAppend(&msg, "High ", kChiSquared, " value: ", chi_square, " > ", - kThreshold); - ABSL_RAW_LOG(INFO, "%s", msg.c_str()); - FAIL() << msg; - } -} - -TEST(UniformIntDistributionTest, StabilityTest) { - // absl::uniform_int_distribution stability relies only on integer operations. - absl::random_internal::sequence_urbg urbg( - {0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull, - 0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull, - 0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull, - 0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull}); - - std::vector<int> output(12); - - { - absl::uniform_int_distribution<int32_t> dist(0, 4); - for (auto& v : output) { - v = dist(urbg); - } - } - EXPECT_EQ(12, urbg.invocations()); - EXPECT_THAT(output, testing::ElementsAre(4, 4, 3, 2, 1, 0, 1, 4, 3, 1, 3, 1)); - - { - urbg.reset(); - absl::uniform_int_distribution<int32_t> dist(0, 100); - for (auto& v : output) { - v = dist(urbg); - } - } - EXPECT_EQ(12, urbg.invocations()); - EXPECT_THAT(output, testing::ElementsAre(97, 86, 75, 41, 36, 16, 38, 92, 67, - 30, 80, 38)); - - { - urbg.reset(); - absl::uniform_int_distribution<int32_t> dist(0, 10000); - for (auto& v : output) { - v = dist(urbg); - } - } - EXPECT_EQ(12, urbg.invocations()); - EXPECT_THAT(output, testing::ElementsAre(9648, 8562, 7439, 4089, 3571, 1602, - 3813, 9195, 6641, 2986, 7956, 3765)); -} - -} // namespace |