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diff --git a/third-party/benchmark/src/statistics.cc b/third-party/benchmark/src/statistics.cc
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+// Copyright 2016 Ismael Jimenez Martinez. All rights reserved.
+// Copyright 2017 Roman Lebedev. All rights reserved.
+//
+// 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
+//
+//     http://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 "benchmark/benchmark.h"
+
+#include <algorithm>
+#include <cmath>
+#include <numeric>
+#include <string>
+#include <vector>
+#include "check.h"
+#include "statistics.h"
+
+namespace benchmark {
+
+auto StatisticsSum = [](const std::vector<double>& v) {
+  return std::accumulate(v.begin(), v.end(), 0.0);
+};
+
+double StatisticsMean(const std::vector<double>& v) {
+  if (v.empty()) return 0.0;
+  return StatisticsSum(v) * (1.0 / v.size());
+}
+
+double StatisticsMedian(const std::vector<double>& v) {
+  if (v.size() < 3) return StatisticsMean(v);
+  std::vector<double> copy(v);
+
+  auto center = copy.begin() + v.size() / 2;
+  std::nth_element(copy.begin(), center, copy.end());
+
+  // did we have an odd number of samples?
+  // if yes, then center is the median
+  // it no, then we are looking for the average between center and the value
+  // before
+  if (v.size() % 2 == 1) return *center;
+  auto center2 = copy.begin() + v.size() / 2 - 1;
+  std::nth_element(copy.begin(), center2, copy.end());
+  return (*center + *center2) / 2.0;
+}
+
+// Return the sum of the squares of this sample set
+auto SumSquares = [](const std::vector<double>& v) {
+  return std::inner_product(v.begin(), v.end(), v.begin(), 0.0);
+};
+
+auto Sqr = [](const double dat) { return dat * dat; };
+auto Sqrt = [](const double dat) {
+  // Avoid NaN due to imprecision in the calculations
+  if (dat < 0.0) return 0.0;
+  return std::sqrt(dat);
+};
+
+double StatisticsStdDev(const std::vector<double>& v) {
+  const auto mean = StatisticsMean(v);
+  if (v.empty()) return mean;
+
+  // Sample standard deviation is undefined for n = 1
+  if (v.size() == 1) return 0.0;
+
+  const double avg_squares = SumSquares(v) * (1.0 / v.size());
+  return Sqrt(v.size() / (v.size() - 1.0) * (avg_squares - Sqr(mean)));
+}
+
+std::vector<BenchmarkReporter::Run> ComputeStats(
+    const std::vector<BenchmarkReporter::Run>& reports) {
+  typedef BenchmarkReporter::Run Run;
+  std::vector<Run> results;
+
+  auto error_count =
+      std::count_if(reports.begin(), reports.end(),
+                    [](Run const& run) { return run.error_occurred; });
+
+  if (reports.size() - error_count < 2) {
+    // We don't report aggregated data if there was a single run.
+    return results;
+  }
+
+  // Accumulators.
+  std::vector<double> real_accumulated_time_stat;
+  std::vector<double> cpu_accumulated_time_stat;
+
+  real_accumulated_time_stat.reserve(reports.size());
+  cpu_accumulated_time_stat.reserve(reports.size());
+
+  // All repetitions should be run with the same number of iterations so we
+  // can take this information from the first benchmark.
+  const IterationCount run_iterations = reports.front().iterations;
+  // create stats for user counters
+  struct CounterStat {
+    Counter c;
+    std::vector<double> s;
+  };
+  std::map<std::string, CounterStat> counter_stats;
+  for (Run const& r : reports) {
+    for (auto const& cnt : r.counters) {
+      auto it = counter_stats.find(cnt.first);
+      if (it == counter_stats.end()) {
+        counter_stats.insert({cnt.first, {cnt.second, std::vector<double>{}}});
+        it = counter_stats.find(cnt.first);
+        it->second.s.reserve(reports.size());
+      } else {
+        CHECK_EQ(counter_stats[cnt.first].c.flags, cnt.second.flags);
+      }
+    }
+  }
+
+  // Populate the accumulators.
+  for (Run const& run : reports) {
+    CHECK_EQ(reports[0].benchmark_name(), run.benchmark_name());
+    CHECK_EQ(run_iterations, run.iterations);
+    if (run.error_occurred) continue;
+    real_accumulated_time_stat.emplace_back(run.real_accumulated_time);
+    cpu_accumulated_time_stat.emplace_back(run.cpu_accumulated_time);
+    // user counters
+    for (auto const& cnt : run.counters) {
+      auto it = counter_stats.find(cnt.first);
+      CHECK_NE(it, counter_stats.end());
+      it->second.s.emplace_back(cnt.second);
+    }
+  }
+
+  // Only add label if it is same for all runs
+  std::string report_label = reports[0].report_label;
+  for (std::size_t i = 1; i < reports.size(); i++) {
+    if (reports[i].report_label != report_label) {
+      report_label = "";
+      break;
+    }
+  }
+
+  const double iteration_rescale_factor =
+      double(reports.size()) / double(run_iterations);
+
+  for (const auto& Stat : *reports[0].statistics) {
+    // Get the data from the accumulator to BenchmarkReporter::Run's.
+    Run data;
+    data.run_name = reports[0].run_name;
+    data.family_index = reports[0].family_index;
+    data.per_family_instance_index = reports[0].per_family_instance_index;
+    data.run_type = BenchmarkReporter::Run::RT_Aggregate;
+    data.threads = reports[0].threads;
+    data.repetitions = reports[0].repetitions;
+    data.repetition_index = Run::no_repetition_index;
+    data.aggregate_name = Stat.name_;
+    data.report_label = report_label;
+
+    // It is incorrect to say that an aggregate is computed over
+    // run's iterations, because those iterations already got averaged.
+    // Similarly, if there are N repetitions with 1 iterations each,
+    // an aggregate will be computed over N measurements, not 1.
+    // Thus it is best to simply use the count of separate reports.
+    data.iterations = reports.size();
+
+    data.real_accumulated_time = Stat.compute_(real_accumulated_time_stat);
+    data.cpu_accumulated_time = Stat.compute_(cpu_accumulated_time_stat);
+
+    // We will divide these times by data.iterations when reporting, but the
+    // data.iterations is not nessesairly the scale of these measurements,
+    // because in each repetition, these timers are sum over all the iterations.
+    // And if we want to say that the stats are over N repetitions and not
+    // M iterations, we need to multiply these by (N/M).
+    data.real_accumulated_time *= iteration_rescale_factor;
+    data.cpu_accumulated_time *= iteration_rescale_factor;
+
+    data.time_unit = reports[0].time_unit;
+
+    // user counters
+    for (auto const& kv : counter_stats) {
+      // Do *NOT* rescale the custom counters. They are already properly scaled.
+      const auto uc_stat = Stat.compute_(kv.second.s);
+      auto c = Counter(uc_stat, counter_stats[kv.first].c.flags,
+                       counter_stats[kv.first].c.oneK);
+      data.counters[kv.first] = c;
+    }
+
+    results.push_back(data);
+  }
+
+  return results;
+}
+
+}  // end namespace benchmark