From 5aa5d282eac56a21e74611c1cdbaa97bb5db2dca Mon Sep 17 00:00:00 2001 From: Vincent Ambo Date: Tue, 8 Feb 2022 02:05:36 +0300 Subject: chore(3p/abseil_cpp): unvendor abseil_cpp 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 Autosubmit: tazjin --- .../absl/random/bernoulli_distribution_test.cc | 217 --------------------- 1 file changed, 217 deletions(-) delete mode 100644 third_party/abseil_cpp/absl/random/bernoulli_distribution_test.cc (limited to 'third_party/abseil_cpp/absl/random/bernoulli_distribution_test.cc') diff --git a/third_party/abseil_cpp/absl/random/bernoulli_distribution_test.cc b/third_party/abseil_cpp/absl/random/bernoulli_distribution_test.cc deleted file mode 100644 index b250f8787c6e..000000000000 --- a/third_party/abseil_cpp/absl/random/bernoulli_distribution_test.cc +++ /dev/null @@ -1,217 +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/bernoulli_distribution.h" - -#include -#include -#include -#include -#include - -#include "gtest/gtest.h" -#include "absl/random/internal/pcg_engine.h" -#include "absl/random/internal/sequence_urbg.h" -#include "absl/random/random.h" - -namespace { - -class BernoulliTest : public testing::TestWithParam> { -}; - -TEST_P(BernoulliTest, Serialize) { - const double d = GetParam().first; - absl::bernoulli_distribution before(d); - - { - absl::bernoulli_distribution via_param{ - absl::bernoulli_distribution::param_type(d)}; - EXPECT_EQ(via_param, before); - } - - std::stringstream ss; - ss << before; - absl::bernoulli_distribution after(0.6789); - - EXPECT_NE(before.p(), after.p()); - EXPECT_NE(before.param(), after.param()); - EXPECT_NE(before, after); - - ss >> after; - - EXPECT_EQ(before.p(), after.p()); - EXPECT_EQ(before.param(), after.param()); - EXPECT_EQ(before, after); -} - -TEST_P(BernoulliTest, Accuracy) { - // Sadly, the claim to fame for this implementation is precise accuracy, which - // is very, very hard to measure, the improvements come as trials approach the - // limit of double accuracy; thus the outcome differs from the - // std::bernoulli_distribution with a probability of approximately 1 in 2^-53. - const std::pair para = GetParam(); - size_t trials = para.second; - double p = para.first; - - // 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); - - size_t yes = 0; - absl::bernoulli_distribution dist(p); - for (size_t i = 0; i < trials; ++i) { - if (dist(rng)) yes++; - } - - // Compute the distribution parameters for a binomial test, using a normal - // approximation for the confidence interval, as there are a sufficiently - // large number of trials that the central limit theorem applies. - const double stddev_p = std::sqrt((p * (1.0 - p)) / trials); - const double expected = trials * p; - const double stddev = trials * stddev_p; - - // 5 sigma, approved by Richard Feynman - EXPECT_NEAR(yes, expected, 5 * stddev) - << "@" << p << ", " - << std::abs(static_cast(yes) - expected) / stddev << " stddev"; -} - -// There must be many more trials to make the mean approximately normal for `p` -// closes to 0 or 1. -INSTANTIATE_TEST_SUITE_P( - All, BernoulliTest, - ::testing::Values( - // Typical values. - std::make_pair(0, 30000), std::make_pair(1e-3, 30000000), - std::make_pair(0.1, 3000000), std::make_pair(0.5, 3000000), - std::make_pair(0.9, 30000000), std::make_pair(0.999, 30000000), - std::make_pair(1, 30000), - // Boundary cases. - std::make_pair(std::nextafter(1.0, 0.0), 1), // ~1 - epsilon - std::make_pair(std::numeric_limits::epsilon(), 1), - std::make_pair(std::nextafter(std::numeric_limits::min(), - 1.0), // min + epsilon - 1), - std::make_pair(std::numeric_limits::min(), // smallest normal - 1), - std::make_pair( - std::numeric_limits::denorm_min(), // smallest denorm - 1), - std::make_pair(std::numeric_limits::min() / 2, 1), // denorm - std::make_pair(std::nextafter(std::numeric_limits::min(), - 0.0), // denorm_max - 1))); - -// NOTE: absl::bernoulli_distribution is not guaranteed to be stable. -TEST(BernoulliTest, StabilityTest) { - // absl::bernoulli_distribution stability relies on FastUniformBits and - // integer arithmetic. - absl::random_internal::sequence_urbg urbg({ - 0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull, - 0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull, - 0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull, - 0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull, - 0x4864f22c059bf29eull, 0x247856d8b862665cull, 0xe46e86e9a1337e10ull, - 0xd8c8541f3519b133ull, 0xe75b5162c567b9e4ull, 0xf732e5ded7009c5bull, - 0xb170b98353121eacull, 0x1ec2e8986d2362caull, 0x814c8e35fe9a961aull, - 0x0c3cd59c9b638a02ull, 0xcb3bb6478a07715cull, 0x1224e62c978bbc7full, - 0x671ef2cb04e81f6eull, 0x3c1cbd811eaf1808ull, 0x1bbc23cfa8fac721ull, - 0xa4c2cda65e596a51ull, 0xb77216fad37adf91ull, 0x836d794457c08849ull, - 0xe083df03475f49d7ull, 0xbc9feb512e6b0d6cull, 0xb12d74fdd718c8c5ull, - 0x12ff09653bfbe4caull, 0x8dd03a105bc4ee7eull, 0x5738341045ba0d85ull, - 0xe3fd722dc65ad09eull, 0x5a14fd21ea2a5705ull, 0x14e6ea4d6edb0c73ull, - 0x275b0dc7e0a18acfull, 0x36cebe0d2653682eull, 0x0361e9b23861596bull, - }); - - // Generate a string of '0' and '1' for the distribution output. - auto generate = [&urbg](absl::bernoulli_distribution& dist) { - std::string output; - output.reserve(36); - urbg.reset(); - for (int i = 0; i < 35; i++) { - output.append(dist(urbg) ? "1" : "0"); - } - return output; - }; - - const double kP = 0.0331289862362; - { - absl::bernoulli_distribution dist(kP); - auto v = generate(dist); - EXPECT_EQ(35, urbg.invocations()); - EXPECT_EQ(v, "00000000000010000000000010000000000") << dist; - } - { - absl::bernoulli_distribution dist(kP * 10.0); - auto v = generate(dist); - EXPECT_EQ(35, urbg.invocations()); - EXPECT_EQ(v, "00000100010010010010000011000011010") << dist; - } - { - absl::bernoulli_distribution dist(kP * 20.0); - auto v = generate(dist); - EXPECT_EQ(35, urbg.invocations()); - EXPECT_EQ(v, "00011110010110110011011111110111011") << dist; - } - { - absl::bernoulli_distribution dist(1.0 - kP); - auto v = generate(dist); - EXPECT_EQ(35, urbg.invocations()); - EXPECT_EQ(v, "11111111111111111111011111111111111") << dist; - } -} - -TEST(BernoulliTest, StabilityTest2) { - absl::random_internal::sequence_urbg urbg( - {0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull, - 0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull, - 0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull, - 0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull}); - - // Generate a string of '0' and '1' for the distribution output. - auto generate = [&urbg](absl::bernoulli_distribution& dist) { - std::string output; - output.reserve(13); - urbg.reset(); - for (int i = 0; i < 12; i++) { - output.append(dist(urbg) ? "1" : "0"); - } - return output; - }; - - constexpr double b0 = 1.0 / 13.0 / 0.2; - constexpr double b1 = 2.0 / 13.0 / 0.2; - constexpr double b3 = (5.0 / 13.0 / 0.2) - ((1 - b0) + (1 - b1) + (1 - b1)); - { - absl::bernoulli_distribution dist(b0); - auto v = generate(dist); - EXPECT_EQ(12, urbg.invocations()); - EXPECT_EQ(v, "000011100101") << dist; - } - { - absl::bernoulli_distribution dist(b1); - auto v = generate(dist); - EXPECT_EQ(12, urbg.invocations()); - EXPECT_EQ(v, "001111101101") << dist; - } - { - absl::bernoulli_distribution dist(b3); - auto v = generate(dist); - EXPECT_EQ(12, urbg.invocations()); - EXPECT_EQ(v, "001111101111") << dist; - } -} - -} // namespace -- cgit 1.4.1