229 lines
8.1 KiB
C
229 lines
8.1 KiB
C
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// Copyright 2017 The Abseil Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// https://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef ABSL_RANDOM_INTERNAL_RANDEN_ENGINE_H_
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#define ABSL_RANDOM_INTERNAL_RANDEN_ENGINE_H_
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#include <algorithm>
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#include <cinttypes>
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#include <cstdlib>
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#include <iostream>
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#include <iterator>
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#include <limits>
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#include <type_traits>
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#include "absl/meta/type_traits.h"
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#include "absl/random/internal/iostream_state_saver.h"
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#include "absl/random/internal/randen.h"
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namespace absl {
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namespace random_internal {
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// Deterministic pseudorandom byte generator with backtracking resistance
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// (leaking the state does not compromise prior outputs). Based on Reverie
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// (see "A Robust and Sponge-Like PRNG with Improved Efficiency") instantiated
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// with an improved Simpira-like permutation.
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// Returns values of type "T" (must be a built-in unsigned integer type).
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//
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// RANDen = RANDom generator or beetroots in Swiss High German.
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// 'Strong' (well-distributed, unpredictable, backtracking-resistant) random
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// generator, faster in some benchmarks than std::mt19937_64 and pcg64_c32.
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template <typename T>
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class alignas(16) randen_engine {
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public:
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// C++11 URBG interface:
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using result_type = T;
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static_assert(std::is_unsigned<result_type>::value,
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"randen_engine template argument must be a built-in unsigned "
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"integer type");
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static constexpr result_type(min)() {
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return (std::numeric_limits<result_type>::min)();
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}
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static constexpr result_type(max)() {
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return (std::numeric_limits<result_type>::max)();
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}
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explicit randen_engine(result_type seed_value = 0) { seed(seed_value); }
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template <class SeedSequence,
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typename = typename absl::enable_if_t<
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!std::is_same<SeedSequence, randen_engine>::value>>
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explicit randen_engine(SeedSequence&& seq) {
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seed(seq);
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}
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randen_engine(const randen_engine&) = default;
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// Returns random bits from the buffer in units of result_type.
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result_type operator()() {
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// Refill the buffer if needed (unlikely).
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if (next_ >= kStateSizeT) {
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next_ = kCapacityT;
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impl_.Generate(state_);
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}
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return state_[next_++];
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}
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template <class SeedSequence>
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typename absl::enable_if_t<
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!std::is_convertible<SeedSequence, result_type>::value>
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seed(SeedSequence&& seq) {
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// Zeroes the state.
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seed();
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reseed(seq);
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}
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void seed(result_type seed_value = 0) {
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next_ = kStateSizeT;
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// Zeroes the inner state and fills the outer state with seed_value to
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// mimics behaviour of reseed
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std::fill(std::begin(state_), std::begin(state_) + kCapacityT, 0);
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std::fill(std::begin(state_) + kCapacityT, std::end(state_), seed_value);
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}
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// Inserts entropy into (part of) the state. Calling this periodically with
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// sufficient entropy ensures prediction resistance (attackers cannot predict
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// future outputs even if state is compromised).
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template <class SeedSequence>
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void reseed(SeedSequence& seq) {
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using sequence_result_type = typename SeedSequence::result_type;
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static_assert(sizeof(sequence_result_type) == 4,
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"SeedSequence::result_type must be 32-bit");
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constexpr size_t kBufferSize =
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Randen::kSeedBytes / sizeof(sequence_result_type);
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alignas(16) sequence_result_type buffer[kBufferSize];
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// Randen::Absorb XORs the seed into state, which is then mixed by a call
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// to Randen::Generate. Seeding with only the provided entropy is preferred
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// to using an arbitrary generate() call, so use [rand.req.seed_seq]
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// size as a proxy for the number of entropy units that can be generated
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// without relying on seed sequence mixing...
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const size_t entropy_size = seq.size();
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if (entropy_size < kBufferSize) {
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// ... and only request that many values, or 256-bits, when unspecified.
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const size_t requested_entropy = (entropy_size == 0) ? 8u : entropy_size;
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std::fill(std::begin(buffer) + requested_entropy, std::end(buffer), 0);
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seq.generate(std::begin(buffer), std::begin(buffer) + requested_entropy);
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// The Randen paper suggests preferentially initializing even-numbered
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// 128-bit vectors of the randen state (there are 16 such vectors).
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// The seed data is merged into the state offset by 128-bits, which
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// implies prefering seed bytes [16..31, ..., 208..223]. Since the
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// buffer is 32-bit values, we swap the corresponding buffer positions in
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// 128-bit chunks.
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size_t dst = kBufferSize;
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while (dst > 7) {
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// leave the odd bucket as-is.
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dst -= 4;
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size_t src = dst >> 1;
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// swap 128-bits into the even bucket
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std::swap(buffer[--dst], buffer[--src]);
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std::swap(buffer[--dst], buffer[--src]);
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std::swap(buffer[--dst], buffer[--src]);
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std::swap(buffer[--dst], buffer[--src]);
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}
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} else {
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seq.generate(std::begin(buffer), std::end(buffer));
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}
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impl_.Absorb(buffer, state_);
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// Generate will be called when operator() is called
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next_ = kStateSizeT;
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}
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void discard(uint64_t count) {
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uint64_t step = std::min<uint64_t>(kStateSizeT - next_, count);
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count -= step;
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constexpr uint64_t kRateT = kStateSizeT - kCapacityT;
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while (count > 0) {
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next_ = kCapacityT;
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impl_.Generate(state_);
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step = std::min<uint64_t>(kRateT, count);
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count -= step;
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}
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next_ += step;
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}
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bool operator==(const randen_engine& other) const {
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return next_ == other.next_ &&
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std::equal(std::begin(state_), std::end(state_),
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std::begin(other.state_));
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}
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bool operator!=(const randen_engine& other) const {
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return !(*this == other);
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}
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template <class CharT, class Traits>
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friend std::basic_ostream<CharT, Traits>& operator<<(
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std::basic_ostream<CharT, Traits>& os, // NOLINT(runtime/references)
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const randen_engine<T>& engine) { // NOLINT(runtime/references)
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using numeric_type =
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typename random_internal::stream_format_type<result_type>::type;
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auto saver = random_internal::make_ostream_state_saver(os);
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for (const auto& elem : engine.state_) {
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// In the case that `elem` is `uint8_t`, it must be cast to something
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// larger so that it prints as an integer rather than a character. For
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// simplicity, apply the cast all circumstances.
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os << static_cast<numeric_type>(elem) << os.fill();
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}
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os << engine.next_;
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return os;
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}
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template <class CharT, class Traits>
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friend std::basic_istream<CharT, Traits>& operator>>(
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std::basic_istream<CharT, Traits>& is, // NOLINT(runtime/references)
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randen_engine<T>& engine) { // NOLINT(runtime/references)
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using numeric_type =
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typename random_internal::stream_format_type<result_type>::type;
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result_type state[kStateSizeT];
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size_t next;
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for (auto& elem : state) {
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// It is not possible to read uint8_t from wide streams, so it is
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// necessary to read a wider type and then cast it to uint8_t.
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numeric_type value;
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is >> value;
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elem = static_cast<result_type>(value);
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}
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is >> next;
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if (is.fail()) {
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return is;
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}
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std::memcpy(engine.state_, state, sizeof(engine.state_));
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engine.next_ = next;
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return is;
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}
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private:
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static constexpr size_t kStateSizeT =
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Randen::kStateBytes / sizeof(result_type);
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static constexpr size_t kCapacityT =
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Randen::kCapacityBytes / sizeof(result_type);
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// First kCapacityT are `inner', the others are accessible random bits.
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alignas(16) result_type state_[kStateSizeT];
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size_t next_; // index within state_
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Randen impl_;
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};
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} // namespace random_internal
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} // namespace absl
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#endif // ABSL_RANDOM_INTERNAL_RANDEN_ENGINE_H_
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