1 files changed, 0 insertions, 93 deletions
diff --git a/third_party/abseil_cpp/absl/base/internal/exponential_biased.cc b/third_party/abseil_cpp/absl/base/internal/exponential_biased.cc
deleted file mode 100644
index 1b30c061e3bd..000000000000
--- a/third_party/abseil_cpp/absl/base/internal/exponential_biased.cc
+++ /dev/null
@@ -1,93 +0,0 @@
-// Copyright 2019 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/base/internal/exponential_biased.h"
-
-#include <stdint.h>
-
-#include <algorithm>
-#include <atomic>
-#include <cmath>
-#include <limits>
-
-#include "absl/base/attributes.h"
-#include "absl/base/optimization.h"
-
-namespace absl {
-ABSL_NAMESPACE_BEGIN
-namespace base_internal {
-
-// The algorithm generates a random number between 0 and 1 and applies the
-// inverse cumulative distribution function for an exponential. Specifically:
-// Let m be the inverse of the sample period, then the probability
-// distribution function is m*exp(-mx) so the CDF is
-// p = 1 - exp(-mx), so
-// q = 1 - p = exp(-mx)
-// log_e(q) = -mx
-// -log_e(q)/m = x
-// log_2(q) * (-log_e(2) * 1/m) = x
-// In the code, q is actually in the range 1 to 2**26, hence the -26 below
-int64_t ExponentialBiased::GetSkipCount(int64_t mean) {
-  if (ABSL_PREDICT_FALSE(!initialized_)) {
-    Initialize();
-  }
-
-  uint64_t rng = NextRandom(rng_);
-  rng_ = rng;
-
-  // Take the top 26 bits as the random number
-  // (This plus the 1<<58 sampling bound give a max possible step of
-  // 5194297183973780480 bytes.)
-  // The uint32_t cast is to prevent a (hard-to-reproduce) NAN
-  // under piii debug for some binaries.
-  double q = static_cast<uint32_t>(rng >> (kPrngNumBits - 26)) + 1.0;
-  // Put the computed p-value through the CDF of a geometric.
-  double interval = bias_ + (std::log2(q) - 26) * (-std::log(2.0) * mean);
-  // Very large values of interval overflow int64_t. To avoid that, we will
-  // cheat and clamp any huge values to (int64_t max)/2. This is a potential
-  // source of bias, but the mean would need to be such a large value that it's
-  // not likely to come up. For example, with a mean of 1e18, the probability of
-  // hitting this condition is about 1/1000. For a mean of 1e17, standard
-  // calculators claim that this event won't happen.
-  if (interval > static_cast<double>(std::numeric_limits<int64_t>::max() / 2)) {
-    // Assume huge values are bias neutral, retain bias for next call.
-    return std::numeric_limits<int64_t>::max() / 2;
-  }
-  double value = std::round(interval);
-  bias_ = interval - value;
-  return value;
-}
-
-int64_t ExponentialBiased::GetStride(int64_t mean) {
-  return GetSkipCount(mean - 1) + 1;
-}
-
-void ExponentialBiased::Initialize() {
-  // We don't get well distributed numbers from `this` so we call NextRandom() a
-  // bunch to mush the bits around. We use a global_rand to handle the case
-  // where the same thread (by memory address) gets created and destroyed
-  // repeatedly.
-  ABSL_CONST_INIT static std::atomic<uint32_t> global_rand(0);
-  uint64_t r = reinterpret_cast<uint64_t>(this) +
-               global_rand.fetch_add(1, std::memory_order_relaxed);
-  for (int i = 0; i < 20; ++i) {
-    r = NextRandom(r);
-  }
-  rng_ = r;
-  initialized_ = true;
-}
-
-}  // namespace base_internal
-ABSL_NAMESPACE_END
-}  // namespace absl