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