Abseil Common Libraries (C++) (grcp 依赖)
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228 lines
8.1 KiB
228 lines
8.1 KiB
// 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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