Creation of LTS branch "lts_2019_08_08"20190808

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GitOrigin-RevId: 9ee91d3e430fb33a4590486573792eb0fa146c2d
Change-Id: Ia06e548bc106cc9d136f6c65714be6645317aced

1 files changed, 494 insertions, 0 deletions

diff --git a/absl/random/distributions_test.cc b/absl/random/distributions_test.cc
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+// 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/distributions.h"
+
+#include <cmath>
+#include <cstdint>
+#include <random>
+#include <vector>
+
+#include "gtest/gtest.h"
+#include "absl/random/internal/distribution_test_util.h"
+#include "absl/random/random.h"
+
+namespace {
+
+constexpr int kSize = 400000;
+
+class RandomDistributionsTest : public testing::Test {};
+
+TEST_F(RandomDistributionsTest, UniformBoundFunctions) {
+  using absl::IntervalClosedClosed;
+  using absl::IntervalClosedOpen;
+  using absl::IntervalOpenClosed;
+  using absl::IntervalOpenOpen;
+  using absl::random_internal::uniform_lower_bound;
+  using absl::random_internal::uniform_upper_bound;
+
+  // absl::uniform_int_distribution natively assumes IntervalClosedClosed
+  // absl::uniform_real_distribution natively assumes IntervalClosedOpen
+
+  EXPECT_EQ(uniform_lower_bound(IntervalOpenClosed, 0, 100), 1);
+  EXPECT_EQ(uniform_lower_bound(IntervalOpenOpen, 0, 100), 1);
+  EXPECT_GT(uniform_lower_bound<float>(IntervalOpenClosed, 0, 1.0), 0);
+  EXPECT_GT(uniform_lower_bound<float>(IntervalOpenOpen, 0, 1.0), 0);
+  EXPECT_GT(uniform_lower_bound<double>(IntervalOpenClosed, 0, 1.0), 0);
+  EXPECT_GT(uniform_lower_bound<double>(IntervalOpenOpen, 0, 1.0), 0);
+
+  EXPECT_EQ(uniform_lower_bound(IntervalClosedClosed, 0, 100), 0);
+  EXPECT_EQ(uniform_lower_bound(IntervalClosedOpen, 0, 100), 0);
+  EXPECT_EQ(uniform_lower_bound<float>(IntervalClosedClosed, 0, 1.0), 0);
+  EXPECT_EQ(uniform_lower_bound<float>(IntervalClosedOpen, 0, 1.0), 0);
+  EXPECT_EQ(uniform_lower_bound<double>(IntervalClosedClosed, 0, 1.0), 0);
+  EXPECT_EQ(uniform_lower_bound<double>(IntervalClosedOpen, 0, 1.0), 0);
+
+  EXPECT_EQ(uniform_upper_bound(IntervalOpenOpen, 0, 100), 99);
+  EXPECT_EQ(uniform_upper_bound(IntervalClosedOpen, 0, 100), 99);
+  EXPECT_EQ(uniform_upper_bound<float>(IntervalOpenOpen, 0, 1.0), 1.0);
+  EXPECT_EQ(uniform_upper_bound<float>(IntervalClosedOpen, 0, 1.0), 1.0);
+  EXPECT_EQ(uniform_upper_bound<double>(IntervalOpenOpen, 0, 1.0), 1.0);
+  EXPECT_EQ(uniform_upper_bound<double>(IntervalClosedOpen, 0, 1.0), 1.0);
+
+  EXPECT_EQ(uniform_upper_bound(IntervalOpenClosed, 0, 100), 100);
+  EXPECT_EQ(uniform_upper_bound(IntervalClosedClosed, 0, 100), 100);
+  EXPECT_GT(uniform_upper_bound<float>(IntervalOpenClosed, 0, 1.0), 1.0);
+  EXPECT_GT(uniform_upper_bound<float>(IntervalClosedClosed, 0, 1.0), 1.0);
+  EXPECT_GT(uniform_upper_bound<double>(IntervalOpenClosed, 0, 1.0), 1.0);
+  EXPECT_GT(uniform_upper_bound<double>(IntervalClosedClosed, 0, 1.0), 1.0);
+
+  // Negative value tests
+  EXPECT_EQ(uniform_lower_bound(IntervalOpenClosed, -100, -1), -99);
+  EXPECT_EQ(uniform_lower_bound(IntervalOpenOpen, -100, -1), -99);
+  EXPECT_GT(uniform_lower_bound<float>(IntervalOpenClosed, -2.0, -1.0), -2.0);
+  EXPECT_GT(uniform_lower_bound<float>(IntervalOpenOpen, -2.0, -1.0), -2.0);
+  EXPECT_GT(uniform_lower_bound<double>(IntervalOpenClosed, -2.0, -1.0), -2.0);
+  EXPECT_GT(uniform_lower_bound<double>(IntervalOpenOpen, -2.0, -1.0), -2.0);
+
+  EXPECT_EQ(uniform_lower_bound(IntervalClosedClosed, -100, -1), -100);
+  EXPECT_EQ(uniform_lower_bound(IntervalClosedOpen, -100, -1), -100);
+  EXPECT_EQ(uniform_lower_bound<float>(IntervalClosedClosed, -2.0, -1.0), -2.0);
+  EXPECT_EQ(uniform_lower_bound<float>(IntervalClosedOpen, -2.0, -1.0), -2.0);
+  EXPECT_EQ(uniform_lower_bound<double>(IntervalClosedClosed, -2.0, -1.0),
+            -2.0);
+  EXPECT_EQ(uniform_lower_bound<double>(IntervalClosedOpen, -2.0, -1.0), -2.0);
+
+  EXPECT_EQ(uniform_upper_bound(IntervalOpenOpen, -100, -1), -2);
+  EXPECT_EQ(uniform_upper_bound(IntervalClosedOpen, -100, -1), -2);
+  EXPECT_EQ(uniform_upper_bound<float>(IntervalOpenOpen, -2.0, -1.0), -1.0);
+  EXPECT_EQ(uniform_upper_bound<float>(IntervalClosedOpen, -2.0, -1.0), -1.0);
+  EXPECT_EQ(uniform_upper_bound<double>(IntervalOpenOpen, -2.0, -1.0), -1.0);
+  EXPECT_EQ(uniform_upper_bound<double>(IntervalClosedOpen, -2.0, -1.0), -1.0);
+
+  EXPECT_EQ(uniform_upper_bound(IntervalOpenClosed, -100, -1), -1);
+  EXPECT_EQ(uniform_upper_bound(IntervalClosedClosed, -100, -1), -1);
+  EXPECT_GT(uniform_upper_bound<float>(IntervalOpenClosed, -2.0, -1.0), -1.0);
+  EXPECT_GT(uniform_upper_bound<float>(IntervalClosedClosed, -2.0, -1.0), -1.0);
+  EXPECT_GT(uniform_upper_bound<double>(IntervalOpenClosed, -2.0, -1.0), -1.0);
+  EXPECT_GT(uniform_upper_bound<double>(IntervalClosedClosed, -2.0, -1.0),
+            -1.0);
+
+  // Edge cases: the next value toward itself is itself.
+  const double d = 1.0;
+  const float f = 1.0;
+  EXPECT_EQ(uniform_lower_bound(IntervalOpenClosed, d, d), d);
+  EXPECT_EQ(uniform_lower_bound(IntervalOpenClosed, f, f), f);
+
+  EXPECT_GT(uniform_lower_bound(IntervalOpenClosed, 1.0, 2.0), 1.0);
+  EXPECT_LT(uniform_lower_bound(IntervalOpenClosed, 1.0, +0.0), 1.0);
+  EXPECT_LT(uniform_lower_bound(IntervalOpenClosed, 1.0, -0.0), 1.0);
+  EXPECT_LT(uniform_lower_bound(IntervalOpenClosed, 1.0, -1.0), 1.0);
+
+  EXPECT_EQ(uniform_upper_bound(IntervalClosedClosed, 0.0f,
+                                std::numeric_limits<float>::max()),
+            std::numeric_limits<float>::max());
+  EXPECT_EQ(uniform_upper_bound(IntervalClosedClosed, 0.0,
+                                std::numeric_limits<double>::max()),
+            std::numeric_limits<double>::max());
+}
+
+struct Invalid {};
+
+template <typename A, typename B>
+auto InferredUniformReturnT(int)
+    -> decltype(absl::Uniform(std::declval<absl::InsecureBitGen&>(),
+                              std::declval<A>(), std::declval<B>()));
+
+template <typename, typename>
+Invalid InferredUniformReturnT(...);
+
+template <typename TagType, typename A, typename B>
+auto InferredTaggedUniformReturnT(int)
+    -> decltype(absl::Uniform(std::declval<TagType>(),
+                              std::declval<absl::InsecureBitGen&>(),
+                              std::declval<A>(), std::declval<B>()));
+
+template <typename, typename, typename>
+Invalid InferredTaggedUniformReturnT(...);
+
+// Given types <A, B, Expect>, CheckArgsInferType() verifies that
+//
+//   absl::Uniform(gen, A{}, B{})
+//
+// returns the type "Expect".
+//
+// This interface can also be used to assert that a given absl::Uniform()
+// overload does not exist / will not compile. Given types <A, B>, the
+// expression
+//
+//   decltype(absl::Uniform(..., std::declval<A>(), std::declval<B>()))
+//
+// will not compile, leaving the definition of InferredUniformReturnT<A, B> to
+// resolve (via SFINAE) to the overload which returns type "Invalid". This
+// allows tests to assert that an invocation such as
+//
+//   absl::Uniform(gen, 1.23f, std::numeric_limits<int>::max() - 1)
+//
+// should not compile, since neither type, float nor int, can precisely
+// represent both endpoint-values. Writing:
+//
+//   CheckArgsInferType<float, int, Invalid>()
+//
+// will assert that this overload does not exist.
+template <typename A, typename B, typename Expect>
+void CheckArgsInferType() {
+  static_assert(
+      absl::conjunction<
+          std::is_same<Expect, decltype(InferredUniformReturnT<A, B>(0))>,
+          std::is_same<Expect,
+                       decltype(InferredUniformReturnT<B, A>(0))>>::value,
+      "");
+  static_assert(
+      absl::conjunction<
+          std::is_same<Expect,
+                       decltype(InferredTaggedUniformReturnT<
+                                absl::random_internal::IntervalOpenOpenT, A, B>(
+                           0))>,
+          std::is_same<Expect,
+                       decltype(InferredTaggedUniformReturnT<
+                                absl::random_internal::IntervalOpenOpenT, B, A>(
+                           0))>>::value,
+      "");
+}
+
+template <typename A, typename B, typename ExplicitRet>
+auto ExplicitUniformReturnT(int) -> decltype(
+    absl::Uniform<ExplicitRet>(*std::declval<absl::InsecureBitGen*>(),
+                               std::declval<A>(), std::declval<B>()));
+
+template <typename, typename, typename ExplicitRet>
+Invalid ExplicitUniformReturnT(...);
+
+template <typename TagType, typename A, typename B, typename ExplicitRet>
+auto ExplicitTaggedUniformReturnT(int) -> decltype(absl::Uniform<ExplicitRet>(
+    std::declval<TagType>(), *std::declval<absl::InsecureBitGen*>(),
+    std::declval<A>(), std::declval<B>()));
+
+template <typename, typename, typename, typename ExplicitRet>
+Invalid ExplicitTaggedUniformReturnT(...);
+
+// Given types <A, B, Expect>, CheckArgsReturnExpectedType() verifies that
+//
+//   absl::Uniform<Expect>(gen, A{}, B{})
+//
+// returns the type "Expect", and that the function-overload has the signature
+//
+//   Expect(URBG&, Expect, Expect)
+template <typename A, typename B, typename Expect>
+void CheckArgsReturnExpectedType() {
+  static_assert(
+      absl::conjunction<
+          std::is_same<Expect,
+                       decltype(ExplicitUniformReturnT<A, B, Expect>(0))>,
+          std::is_same<Expect, decltype(ExplicitUniformReturnT<B, A, Expect>(
+                                   0))>>::value,
+      "");
+  static_assert(
+      absl::conjunction<
+          std::is_same<Expect,
+                       decltype(ExplicitTaggedUniformReturnT<
+                                absl::random_internal::IntervalOpenOpenT, A, B,
+                                Expect>(0))>,
+          std::is_same<Expect,
+                       decltype(ExplicitTaggedUniformReturnT<
+                                absl::random_internal::IntervalOpenOpenT, B, A,
+                                Expect>(0))>>::value,
+      "");
+}
+
+TEST_F(RandomDistributionsTest, UniformTypeInference) {
+  // Infers common types.
+  CheckArgsInferType<uint16_t, uint16_t, uint16_t>();
+  CheckArgsInferType<uint32_t, uint32_t, uint32_t>();
+  CheckArgsInferType<uint64_t, uint64_t, uint64_t>();
+  CheckArgsInferType<int16_t, int16_t, int16_t>();
+  CheckArgsInferType<int32_t, int32_t, int32_t>();
+  CheckArgsInferType<int64_t, int64_t, int64_t>();
+  CheckArgsInferType<float, float, float>();
+  CheckArgsInferType<double, double, double>();
+
+  // Explicitly-specified return-values override inferences.
+  CheckArgsReturnExpectedType<int16_t, int16_t, int32_t>();
+  CheckArgsReturnExpectedType<uint16_t, uint16_t, int32_t>();
+  CheckArgsReturnExpectedType<int16_t, int16_t, int64_t>();
+  CheckArgsReturnExpectedType<int16_t, int32_t, int64_t>();
+  CheckArgsReturnExpectedType<int16_t, int32_t, double>();
+  CheckArgsReturnExpectedType<float, float, double>();
+  CheckArgsReturnExpectedType<int, int, int16_t>();
+
+  // Properly promotes uint16_t.
+  CheckArgsInferType<uint16_t, uint32_t, uint32_t>();
+  CheckArgsInferType<uint16_t, uint64_t, uint64_t>();
+  CheckArgsInferType<uint16_t, int32_t, int32_t>();
+  CheckArgsInferType<uint16_t, int64_t, int64_t>();
+  CheckArgsInferType<uint16_t, float, float>();
+  CheckArgsInferType<uint16_t, double, double>();
+
+  // Properly promotes int16_t.
+  CheckArgsInferType<int16_t, int32_t, int32_t>();
+  CheckArgsInferType<int16_t, int64_t, int64_t>();
+  CheckArgsInferType<int16_t, float, float>();
+  CheckArgsInferType<int16_t, double, double>();
+
+  // Invalid (u)int16_t-pairings do not compile.
+  // See "CheckArgsInferType" comments above, for how this is achieved.
+  CheckArgsInferType<uint16_t, int16_t, Invalid>();
+  CheckArgsInferType<int16_t, uint32_t, Invalid>();
+  CheckArgsInferType<int16_t, uint64_t, Invalid>();
+
+  // Properly promotes uint32_t.
+  CheckArgsInferType<uint32_t, uint64_t, uint64_t>();
+  CheckArgsInferType<uint32_t, int64_t, int64_t>();
+  CheckArgsInferType<uint32_t, double, double>();
+
+  // Properly promotes int32_t.
+  CheckArgsInferType<int32_t, int64_t, int64_t>();
+  CheckArgsInferType<int32_t, double, double>();
+
+  // Invalid (u)int32_t-pairings do not compile.
+  CheckArgsInferType<uint32_t, int32_t, Invalid>();
+  CheckArgsInferType<int32_t, uint64_t, Invalid>();
+  CheckArgsInferType<int32_t, float, Invalid>();
+  CheckArgsInferType<uint32_t, float, Invalid>();
+
+  // Invalid (u)int64_t-pairings do not compile.
+  CheckArgsInferType<uint64_t, int64_t, Invalid>();
+  CheckArgsInferType<int64_t, float, Invalid>();
+  CheckArgsInferType<int64_t, double, Invalid>();
+
+  // Properly promotes float.
+  CheckArgsInferType<float, double, double>();
+
+  // Examples.
+  absl::InsecureBitGen gen;
+  EXPECT_NE(1, absl::Uniform(gen, static_cast<uint16_t>(0), 1.0f));
+  EXPECT_NE(1, absl::Uniform(gen, 0, 1.0));
+  EXPECT_NE(1, absl::Uniform(absl::IntervalOpenOpen, gen,
+                             static_cast<uint16_t>(0), 1.0f));
+  EXPECT_NE(1, absl::Uniform(absl::IntervalOpenOpen, gen, 0, 1.0));
+  EXPECT_NE(1, absl::Uniform(absl::IntervalOpenOpen, gen, -1, 1.0));
+  EXPECT_NE(1, absl::Uniform<double>(absl::IntervalOpenOpen, gen, -1, 1));
+  EXPECT_NE(1, absl::Uniform<float>(absl::IntervalOpenOpen, gen, 0, 1));
+  EXPECT_NE(1, absl::Uniform<float>(gen, 0, 1));
+}
+
+TEST_F(RandomDistributionsTest, UniformNoBounds) {
+  absl::InsecureBitGen gen;
+
+  absl::Uniform<uint8_t>(gen);
+  absl::Uniform<uint16_t>(gen);
+  absl::Uniform<uint32_t>(gen);
+  absl::Uniform<uint64_t>(gen);
+}
+
+// TODO(lar): Validate properties of non-default interval-semantics.
+TEST_F(RandomDistributionsTest, UniformReal) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Uniform(gen, 0, 1.0);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(0.5, moments.mean, 0.02);
+  EXPECT_NEAR(1 / 12.0, moments.variance, 0.02);
+  EXPECT_NEAR(0.0, moments.skewness, 0.02);
+  EXPECT_NEAR(9 / 5.0, moments.kurtosis, 0.02);
+}
+
+TEST_F(RandomDistributionsTest, UniformInt) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    const int64_t kMax = 1000000000000ll;
+    int64_t j = absl::Uniform(absl::IntervalClosedClosed, gen, 0, kMax);
+    // convert to double.
+    values[i] = static_cast<double>(j) / static_cast<double>(kMax);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(0.5, moments.mean, 0.02);
+  EXPECT_NEAR(1 / 12.0, moments.variance, 0.02);
+  EXPECT_NEAR(0.0, moments.skewness, 0.02);
+  EXPECT_NEAR(9 / 5.0, moments.kurtosis, 0.02);
+
+  /*
+  // NOTE: These are not supported by absl::Uniform, which is specialized
+  // on integer and real valued types.
+
+  enum E { E0, E1 };    // enum
+  enum S : int { S0, S1 };    // signed enum
+  enum U : unsigned int { U0, U1 };  // unsigned enum
+
+  absl::Uniform(gen, E0, E1);
+  absl::Uniform(gen, S0, S1);
+  absl::Uniform(gen, U0, U1);
+  */
+}
+
+TEST_F(RandomDistributionsTest, Exponential) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Exponential<double>(gen);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(1.0, moments.mean, 0.02);
+  EXPECT_NEAR(1.0, moments.variance, 0.025);
+  EXPECT_NEAR(2.0, moments.skewness, 0.1);
+  EXPECT_LT(5.0, moments.kurtosis);
+}
+
+TEST_F(RandomDistributionsTest, PoissonDefault) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Poisson<int64_t>(gen);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(1.0, moments.mean, 0.02);
+  EXPECT_NEAR(1.0, moments.variance, 0.02);
+  EXPECT_NEAR(1.0, moments.skewness, 0.025);
+  EXPECT_LT(2.0, moments.kurtosis);
+}
+
+TEST_F(RandomDistributionsTest, PoissonLarge) {
+  constexpr double kMean = 100000000.0;
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Poisson<int64_t>(gen, kMean);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(kMean, moments.mean, kMean * 0.015);
+  EXPECT_NEAR(kMean, moments.variance, kMean * 0.015);
+  EXPECT_NEAR(std::sqrt(kMean), moments.skewness, kMean * 0.02);
+  EXPECT_LT(2.0, moments.kurtosis);
+}
+
+TEST_F(RandomDistributionsTest, Bernoulli) {
+  constexpr double kP = 0.5151515151;
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Bernoulli(gen, kP);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(kP, moments.mean, 0.01);
+}
+
+TEST_F(RandomDistributionsTest, Beta) {
+  constexpr double kAlpha = 2.0;
+  constexpr double kBeta = 3.0;
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Beta(gen, kAlpha, kBeta);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(0.4, moments.mean, 0.01);
+}
+
+TEST_F(RandomDistributionsTest, Zipf) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Zipf<int64_t>(gen, 100);
+  }
+
+  // The mean of a zipf distribution is: H(N, s-1) / H(N,s).
+  // Given the parameter v = 1, this gives the following function:
+  // (Hn(100, 1) - Hn(1,1)) / (Hn(100,2) - Hn(1,2)) = 6.5944
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(6.5944, moments.mean, 2000) << moments;
+}
+
+TEST_F(RandomDistributionsTest, Gaussian) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::Gaussian<double>(gen);
+  }
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(0.0, moments.mean, 0.02);
+  EXPECT_NEAR(1.0, moments.variance, 0.04);
+  EXPECT_NEAR(0, moments.skewness, 0.2);
+  EXPECT_NEAR(3.0, moments.kurtosis, 0.5);
+}
+
+TEST_F(RandomDistributionsTest, LogUniform) {
+  std::vector<double> values(kSize);
+
+  absl::InsecureBitGen gen;
+  for (int i = 0; i < kSize; i++) {
+    values[i] = absl::LogUniform<int64_t>(gen, 0, (1 << 10) - 1);
+  }
+
+  // The mean is the sum of the fractional means of the uniform distributions:
+  // [0..0][1..1][2..3][4..7][8..15][16..31][32..63]
+  // [64..127][128..255][256..511][512..1023]
+  const double mean = (0 + 1 + 1 + 2 + 3 + 4 + 7 + 8 + 15 + 16 + 31 + 32 + 63 +
+                       64 + 127 + 128 + 255 + 256 + 511 + 512 + 1023) /
+                      (2.0 * 11.0);
+
+  const auto moments =
+      absl::random_internal::ComputeDistributionMoments(values);
+  EXPECT_NEAR(mean, moments.mean, 2) << moments;
+}
+
+}  // namespace