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diff --git a/third_party/abseil_cpp/absl/random/uniform_int_distribution.h b/third_party/abseil_cpp/absl/random/uniform_int_distribution.h
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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.
-//
-// -----------------------------------------------------------------------------
-// File: uniform_int_distribution.h
-// -----------------------------------------------------------------------------
-//
-// This header defines a class for representing a uniform integer distribution
-// over the closed (inclusive) interval [a,b]. You use this distribution in
-// combination with an Abseil random bit generator to produce random values
-// according to the rules of the distribution.
-//
-// `absl::uniform_int_distribution` is a drop-in replacement for the C++11
-// `std::uniform_int_distribution` [rand.dist.uni.int] but is considerably
-// faster than the libstdc++ implementation.
-
-#ifndef ABSL_RANDOM_UNIFORM_INT_DISTRIBUTION_H_
-#define ABSL_RANDOM_UNIFORM_INT_DISTRIBUTION_H_
-
-#include <cassert>
-#include <istream>
-#include <limits>
-#include <type_traits>
-
-#include "absl/base/optimization.h"
-#include "absl/random/internal/fast_uniform_bits.h"
-#include "absl/random/internal/iostream_state_saver.h"
-#include "absl/random/internal/traits.h"
-#include "absl/random/internal/wide_multiply.h"
-
-namespace absl {
-ABSL_NAMESPACE_BEGIN
-
-// absl::uniform_int_distribution<T>
-//
-// This distribution produces random integer values uniformly distributed in the
-// closed (inclusive) interval [a, b].
-//
-// Example:
-//
-//   absl::BitGen gen;
-//
-//   // Use the distribution to produce a value between 1 and 6, inclusive.
-//   int die_roll = absl::uniform_int_distribution<int>(1, 6)(gen);
-//
-template <typename IntType = int>
-class uniform_int_distribution {
- private:
-  using unsigned_type =
-      typename random_internal::make_unsigned_bits<IntType>::type;
-
- public:
-  using result_type = IntType;
-
-  class param_type {
-   public:
-    using distribution_type = uniform_int_distribution;
-
-    explicit param_type(
-        result_type lo = 0,
-        result_type hi = (std::numeric_limits<result_type>::max)())
-        : lo_(lo),
-          range_(static_cast<unsigned_type>(hi) -
-                 static_cast<unsigned_type>(lo)) {
-      // [rand.dist.uni.int] precondition 2
-      assert(lo <= hi);
-    }
-
-    result_type a() const { return lo_; }
-    result_type b() const {
-      return static_cast<result_type>(static_cast<unsigned_type>(lo_) + range_);
-    }
-
-    friend bool operator==(const param_type& a, const param_type& b) {
-      return a.lo_ == b.lo_ && a.range_ == b.range_;
-    }
-
-    friend bool operator!=(const param_type& a, const param_type& b) {
-      return !(a == b);
-    }
-
-   private:
-    friend class uniform_int_distribution;
-    unsigned_type range() const { return range_; }
-
-    result_type lo_;
-    unsigned_type range_;
-
-    static_assert(std::is_integral<result_type>::value,
-                  "Class-template absl::uniform_int_distribution<> must be "
-                  "parameterized using an integral type.");
-  };  // param_type
-
-  uniform_int_distribution() : uniform_int_distribution(0) {}
-
-  explicit uniform_int_distribution(
-      result_type lo,
-      result_type hi = (std::numeric_limits<result_type>::max)())
-      : param_(lo, hi) {}
-
-  explicit uniform_int_distribution(const param_type& param) : param_(param) {}
-
-  // uniform_int_distribution<T>::reset()
-  //
-  // Resets the uniform int distribution. Note that this function has no effect
-  // because the distribution already produces independent values.
-  void reset() {}
-
-  template <typename URBG>
-  result_type operator()(URBG& gen) {  // NOLINT(runtime/references)
-    return (*this)(gen, param());
-  }
-
-  template <typename URBG>
-  result_type operator()(
-      URBG& gen, const param_type& param) {  // NOLINT(runtime/references)
-    return param.a() + Generate(gen, param.range());
-  }
-
-  result_type a() const { return param_.a(); }
-  result_type b() const { return param_.b(); }
-
-  param_type param() const { return param_; }
-  void param(const param_type& params) { param_ = params; }
-
-  result_type(min)() const { return a(); }
-  result_type(max)() const { return b(); }
-
-  friend bool operator==(const uniform_int_distribution& a,
-                         const uniform_int_distribution& b) {
-    return a.param_ == b.param_;
-  }
-  friend bool operator!=(const uniform_int_distribution& a,
-                         const uniform_int_distribution& b) {
-    return !(a == b);
-  }
-
- private:
-  // Generates a value in the *closed* interval [0, R]
-  template <typename URBG>
-  unsigned_type Generate(URBG& g,  // NOLINT(runtime/references)
-                         unsigned_type R);
-  param_type param_;
-};
-
-// -----------------------------------------------------------------------------
-// Implementation details follow
-// -----------------------------------------------------------------------------
-template <typename CharT, typename Traits, typename IntType>
-std::basic_ostream<CharT, Traits>& operator<<(
-    std::basic_ostream<CharT, Traits>& os,
-    const uniform_int_distribution<IntType>& x) {
-  using stream_type =
-      typename random_internal::stream_format_type<IntType>::type;
-  auto saver = random_internal::make_ostream_state_saver(os);
-  os << static_cast<stream_type>(x.a()) << os.fill()
-     << static_cast<stream_type>(x.b());
-  return os;
-}
-
-template <typename CharT, typename Traits, typename IntType>
-std::basic_istream<CharT, Traits>& operator>>(
-    std::basic_istream<CharT, Traits>& is,
-    uniform_int_distribution<IntType>& x) {
-  using param_type = typename uniform_int_distribution<IntType>::param_type;
-  using result_type = typename uniform_int_distribution<IntType>::result_type;
-  using stream_type =
-      typename random_internal::stream_format_type<IntType>::type;
-
-  stream_type a;
-  stream_type b;
-
-  auto saver = random_internal::make_istream_state_saver(is);
-  is >> a >> b;
-  if (!is.fail()) {
-    x.param(
-        param_type(static_cast<result_type>(a), static_cast<result_type>(b)));
-  }
-  return is;
-}
-
-template <typename IntType>
-template <typename URBG>
-typename random_internal::make_unsigned_bits<IntType>::type
-uniform_int_distribution<IntType>::Generate(
-    URBG& g,  // NOLINT(runtime/references)
-    typename random_internal::make_unsigned_bits<IntType>::type R) {
-    random_internal::FastUniformBits<unsigned_type> fast_bits;
-  unsigned_type bits = fast_bits(g);
-  const unsigned_type Lim = R + 1;
-  if ((R & Lim) == 0) {
-    // If the interval's length is a power of two range, just take the low bits.
-    return bits & R;
-  }
-
-  // Generates a uniform variate on [0, Lim) using fixed-point multiplication.
-  // The above fast-path guarantees that Lim is representable in unsigned_type.
-  //
-  // Algorithm adapted from
-  // http://lemire.me/blog/2016/06/30/fast-random-shuffling/, with added
-  // explanation.
-  //
-  // The algorithm creates a uniform variate `bits` in the interval [0, 2^N),
-  // and treats it as the fractional part of a fixed-point real value in [0, 1),
-  // multiplied by 2^N.  For example, 0.25 would be represented as 2^(N - 2),
-  // because 2^N * 0.25 == 2^(N - 2).
-  //
-  // Next, `bits` and `Lim` are multiplied with a wide-multiply to bring the
-  // value into the range [0, Lim).  The integral part (the high word of the
-  // multiplication result) is then very nearly the desired result.  However,
-  // this is not quite accurate; viewing the multiplication result as one
-  // double-width integer, the resulting values for the sample are mapped as
-  // follows:
-  //
-  // If the result lies in this interval:       Return this value:
-  //        [0, 2^N)                                    0
-  //        [2^N, 2 * 2^N)                              1
-  //        ...                                         ...
-  //        [K * 2^N, (K + 1) * 2^N)                    K
-  //        ...                                         ...
-  //        [(Lim - 1) * 2^N, Lim * 2^N)                Lim - 1
-  //
-  // While all of these intervals have the same size, the result of `bits * Lim`
-  // must be a multiple of `Lim`, and not all of these intervals contain the
-  // same number of multiples of `Lim`.  In particular, some contain
-  // `F = floor(2^N / Lim)` and some contain `F + 1 = ceil(2^N / Lim)`.  This
-  // difference produces a small nonuniformity, which is corrected by applying
-  // rejection sampling to one of the values in the "larger intervals" (i.e.,
-  // the intervals containing `F + 1` multiples of `Lim`.
-  //
-  // An interval contains `F + 1` multiples of `Lim` if and only if its smallest
-  // value modulo 2^N is less than `2^N % Lim`.  The unique value satisfying
-  // this property is used as the one for rejection.  That is, a value of
-  // `bits * Lim` is rejected if `(bit * Lim) % 2^N < (2^N % Lim)`.
-
-  using helper = random_internal::wide_multiply<unsigned_type>;
-  auto product = helper::multiply(bits, Lim);
-
-  // Two optimizations here:
-  // * Rejection occurs with some probability less than 1/2, and for reasonable
-  //   ranges considerably less (in particular, less than 1/(F+1)), so
-  //   ABSL_PREDICT_FALSE is apt.
-  // * `Lim` is an overestimate of `threshold`, and doesn't require a divide.
-  if (ABSL_PREDICT_FALSE(helper::lo(product) < Lim)) {
-    // This quantity is exactly equal to `2^N % Lim`, but does not require high
-    // precision calculations: `2^N % Lim` is congruent to `(2^N - Lim) % Lim`.
-    // Ideally this could be expressed simply as `-X` rather than `2^N - X`, but
-    // for types smaller than int, this calculation is incorrect due to integer
-    // promotion rules.
-    const unsigned_type threshold =
-        ((std::numeric_limits<unsigned_type>::max)() - Lim + 1) % Lim;
-    while (helper::lo(product) < threshold) {
-      bits = fast_bits(g);
-      product = helper::multiply(bits, Lim);
-    }
-  }
-
-  return helper::hi(product);
-}
-
-ABSL_NAMESPACE_END
-}  // namespace absl
-
-#endif  // ABSL_RANDOM_UNIFORM_INT_DISTRIBUTION_H_