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>

1 files changed, 0 insertions, 200 deletions

diff --git a/third_party/abseil_cpp/absl/random/bernoulli_distribution.h b/third_party/abseil_cpp/absl/random/bernoulli_distribution.h
deleted file mode 100644
index 25bd0d5ca420..000000000000
--- a/third_party/abseil_cpp/absl/random/bernoulli_distribution.h
+++ /dev/null
@@ -1,200 +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.
-
-#ifndef ABSL_RANDOM_BERNOULLI_DISTRIBUTION_H_
-#define ABSL_RANDOM_BERNOULLI_DISTRIBUTION_H_
-
-#include <cstdint>
-#include <istream>
-#include <limits>
-
-#include "absl/base/optimization.h"
-#include "absl/random/internal/fast_uniform_bits.h"
-#include "absl/random/internal/iostream_state_saver.h"
-
-namespace absl {
-ABSL_NAMESPACE_BEGIN
-
-// absl::bernoulli_distribution is a drop in replacement for
-// std::bernoulli_distribution. It guarantees that (given a perfect
-// UniformRandomBitGenerator) the acceptance probability is *exactly* equal to
-// the given double.
-//
-// The implementation assumes that double is IEEE754
-class bernoulli_distribution {
- public:
-  using result_type = bool;
-
-  class param_type {
-   public:
-    using distribution_type = bernoulli_distribution;
-
-    explicit param_type(double p = 0.5) : prob_(p) {
-      assert(p >= 0.0 && p <= 1.0);
-    }
-
-    double p() const { return prob_; }
-
-    friend bool operator==(const param_type& p1, const param_type& p2) {
-      return p1.p() == p2.p();
-    }
-    friend bool operator!=(const param_type& p1, const param_type& p2) {
-      return p1.p() != p2.p();
-    }
-
-   private:
-    double prob_;
-  };
-
-  bernoulli_distribution() : bernoulli_distribution(0.5) {}
-
-  explicit bernoulli_distribution(double p) : param_(p) {}
-
-  explicit bernoulli_distribution(param_type p) : param_(p) {}
-
-  // no-op
-  void reset() {}
-
-  template <typename URBG>
-  bool operator()(URBG& g) {  // NOLINT(runtime/references)
-    return Generate(param_.p(), g);
-  }
-
-  template <typename URBG>
-  bool operator()(URBG& g,  // NOLINT(runtime/references)
-                  const param_type& param) {
-    return Generate(param.p(), g);
-  }
-
-  param_type param() const { return param_; }
-  void param(const param_type& param) { param_ = param; }
-
-  double p() const { return param_.p(); }
-
-  result_type(min)() const { return false; }
-  result_type(max)() const { return true; }
-
-  friend bool operator==(const bernoulli_distribution& d1,
-                         const bernoulli_distribution& d2) {
-    return d1.param_ == d2.param_;
-  }
-
-  friend bool operator!=(const bernoulli_distribution& d1,
-                         const bernoulli_distribution& d2) {
-    return d1.param_ != d2.param_;
-  }
-
- private:
-  static constexpr uint64_t kP32 = static_cast<uint64_t>(1) << 32;
-
-  template <typename URBG>
-  static bool Generate(double p, URBG& g);  // NOLINT(runtime/references)
-
-  param_type param_;
-};
-
-template <typename CharT, typename Traits>
-std::basic_ostream<CharT, Traits>& operator<<(
-    std::basic_ostream<CharT, Traits>& os,  // NOLINT(runtime/references)
-    const bernoulli_distribution& x) {
-  auto saver = random_internal::make_ostream_state_saver(os);
-  os.precision(random_internal::stream_precision_helper<double>::kPrecision);
-  os << x.p();
-  return os;
-}
-
-template <typename CharT, typename Traits>
-std::basic_istream<CharT, Traits>& operator>>(
-    std::basic_istream<CharT, Traits>& is,  // NOLINT(runtime/references)
-    bernoulli_distribution& x) {            // NOLINT(runtime/references)
-  auto saver = random_internal::make_istream_state_saver(is);
-  auto p = random_internal::read_floating_point<double>(is);
-  if (!is.fail()) {
-    x.param(bernoulli_distribution::param_type(p));
-  }
-  return is;
-}
-
-template <typename URBG>
-bool bernoulli_distribution::Generate(double p,
-                                      URBG& g) {  // NOLINT(runtime/references)
-  random_internal::FastUniformBits<uint32_t> fast_u32;
-
-  while (true) {
-    // There are two aspects of the definition of `c` below that are worth
-    // commenting on.  First, because `p` is in the range [0, 1], `c` is in the
-    // range [0, 2^32] which does not fit in a uint32_t and therefore requires
-    // 64 bits.
-    //
-    // Second, `c` is constructed by first casting explicitly to a signed
-    // integer and then converting implicitly to an unsigned integer of the same
-    // size.  This is done because the hardware conversion instructions produce
-    // signed integers from double; if taken as a uint64_t the conversion would
-    // be wrong for doubles greater than 2^63 (not relevant in this use-case).
-    // If converted directly to an unsigned integer, the compiler would end up
-    // emitting code to handle such large values that are not relevant due to
-    // the known bounds on `c`.  To avoid these extra instructions this
-    // implementation converts first to the signed type and then use the
-    // implicit conversion to unsigned (which is a no-op).
-    const uint64_t c = static_cast<int64_t>(p * kP32);
-    const uint32_t v = fast_u32(g);
-    // FAST PATH: this path fails with probability 1/2^32.  Note that simply
-    // returning v <= c would approximate P very well (up to an absolute error
-    // of 1/2^32); the slow path (taken in that range of possible error, in the
-    // case of equality) eliminates the remaining error.
-    if (ABSL_PREDICT_TRUE(v != c)) return v < c;
-
-    // It is guaranteed that `q` is strictly less than 1, because if `q` were
-    // greater than or equal to 1, the same would be true for `p`. Certainly `p`
-    // cannot be greater than 1, and if `p == 1`, then the fast path would
-    // necessary have been taken already.
-    const double q = static_cast<double>(c) / kP32;
-
-    // The probability of acceptance on the fast path is `q` and so the
-    // probability of acceptance here should be `p - q`.
-    //
-    // Note that `q` is obtained from `p` via some shifts and conversions, the
-    // upshot of which is that `q` is simply `p` with some of the
-    // least-significant bits of its mantissa set to zero. This means that the
-    // difference `p - q` will not have any rounding errors. To see why, pretend
-    // that double has 10 bits of resolution and q is obtained from `p` in such
-    // a way that the 4 least-significant bits of its mantissa are set to zero.
-    // For example:
-    //   p   = 1.1100111011 * 2^-1
-    //   q   = 1.1100110000 * 2^-1
-    // p - q = 1.011        * 2^-8
-    // The difference `p - q` has exactly the nonzero mantissa bits that were
-    // "lost" in `q` producing a number which is certainly representable in a
-    // double.
-    const double left = p - q;
-
-    // By construction, the probability of being on this slow path is 1/2^32, so
-    // P(accept in slow path) = P(accept| in slow path) * P(slow path),
-    // which means the probability of acceptance here is `1 / (left * kP32)`:
-    const double here = left * kP32;
-
-    // The simplest way to compute the result of this trial is to repeat the
-    // whole algorithm with the new probability. This terminates because even
-    // given  arbitrarily unfriendly "random" bits, each iteration either
-    // multiplies a tiny probability by 2^32 (if c == 0) or strips off some
-    // number of nonzero mantissa bits. That process is bounded.
-    if (here == 0) return false;
-    p = here;
-  }
-}
-
-ABSL_NAMESPACE_END
-}  // namespace absl
-
-#endif  // ABSL_RANDOM_BERNOULLI_DISTRIBUTION_H_