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authorGravatar Abseil Team <absl-team@google.com>2019-06-21 13:11:42 -0700
committerGravatar Gennadiy Rozental <rogeeff@google.com>2019-06-21 16:18:10 -0400
commite9324d926a9189e222741fce6e676f0944661a72 (patch)
treea08568a709940c376454da34c9d8aac021378e5f /absl/random/uniform_int_distribution.h
parent43ef2148c0936ebf7cb4be6b19927a9d9d145b8f (diff)
Export of internal Abseil changes.
-- 7a6ff16a85beb730c172d5d25cf1b5e1be885c56 by Laramie Leavitt <lar@google.com>: Internal change. PiperOrigin-RevId: 254454546 -- ff8f9bafaefc26d451f576ea4a06d150aed63f6f by Andy Soffer <asoffer@google.com>: Internal changes PiperOrigin-RevId: 254451562 -- deefc5b651b479ce36f0b4ef203e119c0c8936f2 by CJ Johnson <johnsoncj@google.com>: Account for subtracting unsigned values from the size of InlinedVector PiperOrigin-RevId: 254450625 -- 3c677316a27bcadc17e41957c809ca472d5fef14 by Andy Soffer <asoffer@google.com>: Add C++17's std::make_from_tuple to absl/utility/utility.h PiperOrigin-RevId: 254411573 -- 4ee3536a918830eeec402a28fc31a62c7c90b940 by CJ Johnson <johnsoncj@google.com>: Adds benchmark for the rest of the InlinedVector public API PiperOrigin-RevId: 254408378 -- e5a21a00700ee83498ff1efbf649169756463ee4 by CJ Johnson <johnsoncj@google.com>: Updates the definition of InlinedVector::shrink_to_fit() to be exception safe and adds exception safety tests for it. PiperOrigin-RevId: 254401387 -- 2ea82e72b86d82d78b4e4712a63a55981b53c64b by Laramie Leavitt <lar@google.com>: Use absl::InsecureBitGen in place of std::mt19937 in tests absl/random/...distribution_test.cc PiperOrigin-RevId: 254289444 -- fa099e02c413a7ffda732415e8105cad26a90337 by Andy Soffer <asoffer@google.com>: Internal changes PiperOrigin-RevId: 254286334 -- ce34b7f36933b30cfa35b9c9a5697a792b5666e4 by Andy Soffer <asoffer@google.com>: Internal changes PiperOrigin-RevId: 254273059 -- 6f9c473da7c2090c2e85a37c5f00622e8a912a89 by Jorg Brown <jorg@google.com>: Change absl::container_internal::CompressedTuple to instantiate its internal Storage class with the name of the type it's holding, rather than the name of the Tuple. This is not an externally-visible change, other than less compiler memory is used and less debug information is generated. PiperOrigin-RevId: 254269285 -- 8bd3c186bf2fc0c55d8a2dd6f28a5327502c9fba by Andy Soffer <asoffer@google.com>: Adding short-hand IntervalClosed for IntervalClosedClosed and IntervalOpen for IntervalOpenOpen. PiperOrigin-RevId: 254252419 -- ea957f99b6a04fccd42aa05605605f3b44b1ecfd by Abseil Team <absl-team@google.com>: Do not directly use __SIZEOF_INT128__. In order to avoid linker errors when building with clang-cl (__fixunsdfti, __udivti3 and __fixunssfti are undefined), this CL uses ABSL_HAVE_INTRINSIC_INT128 which is not defined for clang-cl. PiperOrigin-RevId: 254250739 -- 89ab385cd26b34d64130bce856253aaba96d2345 by Andy Soffer <asoffer@google.com>: Internal changes PiperOrigin-RevId: 254242321 -- cffc793d93eca6d6bdf7de733847b6ab4a255ae9 by CJ Johnson <johnsoncj@google.com>: Adds benchmark for InlinedVector::reserve(size_type) PiperOrigin-RevId: 254199226 -- c90c7a9fa3c8f0c9d5114036979548b055ea2f2a by Gennadiy Rozental <rogeeff@google.com>: Import of CCTZ from GitHub. PiperOrigin-RevId: 254072387 -- c4c388beae016c9570ab54ffa1d52660e4a85b7b by Laramie Leavitt <lar@google.com>: Internal cleanup. PiperOrigin-RevId: 254062381 -- d3c992e221cc74e5372d0c8fa410170b6a43c062 by Tom Manshreck <shreck@google.com>: Update distributions.h to Abseil standards PiperOrigin-RevId: 254054946 -- d15ad0035c34ef11b14fadc5a4a2d3ec415f5518 by CJ Johnson <johnsoncj@google.com>: Removes functions with only one caller from the implementation details of InlinedVector by manually inlining the definitions PiperOrigin-RevId: 254005427 -- 2f37e807efc3a8ef1f4b539bdd379917d4151520 by Andy Soffer <asoffer@google.com>: Initial release of Abseil Random PiperOrigin-RevId: 253999861 -- 24ed1694b6430791d781ed533a8f8ccf6cac5856 by CJ Johnson <johnsoncj@google.com>: Updates the definition of InlinedVector::assign(...)/InlinedVector::operator=(...) to new, exception-safe implementations with exception safety tests to boot PiperOrigin-RevId: 253993691 -- 5613d95f5a7e34a535cfaeadce801441e990843e by CJ Johnson <johnsoncj@google.com>: Adds benchmarks for InlinedVector::shrink_to_fit() PiperOrigin-RevId: 253989647 -- 2a96ddfdac40bbb8cb6a7f1aeab90917067c6e63 by Abseil Team <absl-team@google.com>: Initial release of Abseil Random PiperOrigin-RevId: 253927497 -- bf1aff8fc9ffa921ad74643e9525ecf25b0d8dc1 by Andy Soffer <asoffer@google.com>: Initial release of Abseil Random PiperOrigin-RevId: 253920512 -- bfc03f4a3dcda3cf3a4b84bdb84cda24e3394f41 by Laramie Leavitt <lar@google.com>: Internal change. PiperOrigin-RevId: 253886486 -- 05036cfcc078ca7c5f581a00dfb0daed568cbb69 by Eric Fiselier <ericwf@google.com>: Don't include `winsock2.h` because it drags in `windows.h` and friends, and they define awful macros like OPAQUE, ERROR, and more. This has the potential to break abseil users. Instead we only forward declare `timeval` and require Windows users include `winsock2.h` themselves. This is both inconsistent and poor QoI, but so including 'windows.h' is bad too. PiperOrigin-RevId: 253852615 GitOrigin-RevId: 7a6ff16a85beb730c172d5d25cf1b5e1be885c56 Change-Id: Icd6aff87da26f29ec8915da856f051129987cef6
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+// 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.
+//
+// -----------------------------------------------------------------------------
+// File: uniform_int_distribution.h
+// -----------------------------------------------------------------------------
+//
+// This header defines a class for representing a uniform integer distribution
+// over the closed (inclusive) interval [a,b]. You use this distribution in
+// combination with an Abseil random bit generator to produce random values
+// according to the rules of the distribution.
+//
+// `absl::uniform_int_distribution` is a drop-in replacement for the C++11
+// `std::uniform_int_distribution` [rand.dist.uni.int] but is considerably
+// faster than the libstdc++ implementation.
+
+#ifndef ABSL_RANDOM_UNIFORM_INT_DISTRIBUTION_H_
+#define ABSL_RANDOM_UNIFORM_INT_DISTRIBUTION_H_
+
+#include <cassert>
+#include <istream>
+#include <limits>
+#include <type_traits>
+
+#include "absl/base/optimization.h"
+#include "absl/random/internal/distribution_impl.h"
+#include "absl/random/internal/fast_uniform_bits.h"
+#include "absl/random/internal/iostream_state_saver.h"
+#include "absl/random/internal/traits.h"
+
+namespace absl {
+
+// absl::uniform_int_distribution<T>
+//
+// This distribution produces random integer values uniformly distributed in the
+// closed (inclusive) interval [a, b].
+//
+// Example:
+//
+// absl::BitGen gen;
+//
+// // Use the distribution to produce a value between 1 and 6, inclusive.
+// int die_roll = absl::uniform_int_distribution<int>(1, 6)(gen);
+//
+template <typename IntType = int>
+class uniform_int_distribution {
+ private:
+ using unsigned_type =
+ typename random_internal::make_unsigned_bits<IntType>::type;
+
+ public:
+ using result_type = IntType;
+
+ class param_type {
+ public:
+ using distribution_type = uniform_int_distribution;
+
+ explicit param_type(
+ result_type lo = 0,
+ result_type hi = (std::numeric_limits<result_type>::max)())
+ : lo_(lo),
+ range_(static_cast<unsigned_type>(hi) -
+ static_cast<unsigned_type>(lo)) {
+ // [rand.dist.uni.int] precondition 2
+ assert(lo <= hi);
+ }
+
+ result_type a() const { return lo_; }
+ result_type b() const {
+ return static_cast<result_type>(static_cast<unsigned_type>(lo_) + range_);
+ }
+
+ friend bool operator==(const param_type& a, const param_type& b) {
+ return a.lo_ == b.lo_ && a.range_ == b.range_;
+ }
+
+ friend bool operator!=(const param_type& a, const param_type& b) {
+ return !(a == b);
+ }
+
+ private:
+ friend class uniform_int_distribution;
+ unsigned_type range() const { return range_; }
+
+ result_type lo_;
+ unsigned_type range_;
+
+ static_assert(std::is_integral<result_type>::value,
+ "Class-template absl::uniform_int_distribution<> must be "
+ "parameterized using an integral type.");
+ }; // param_type
+
+ uniform_int_distribution() : uniform_int_distribution(0) {}
+
+ explicit uniform_int_distribution(
+ result_type lo,
+ result_type hi = (std::numeric_limits<result_type>::max)())
+ : param_(lo, hi) {}
+
+ explicit uniform_int_distribution(const param_type& param) : param_(param) {}
+
+ // uniform_int_distribution<T>::reset()
+ //
+ // Resets the uniform int distribution. Note that this function has no effect
+ // because the distribution already produces independent values.
+ void reset() {}
+
+ template <typename URBG>
+ result_type operator()(URBG& gen) { // NOLINT(runtime/references)
+ return (*this)(gen, param());
+ }
+
+ template <typename URBG>
+ result_type operator()(
+ URBG& gen, const param_type& param) { // NOLINT(runtime/references)
+ return param.a() + Generate(gen, param.range());
+ }
+
+ result_type a() const { return param_.a(); }
+ result_type b() const { return param_.b(); }
+
+ param_type param() const { return param_; }
+ void param(const param_type& params) { param_ = params; }
+
+ result_type(min)() const { return a(); }
+ result_type(max)() const { return b(); }
+
+ friend bool operator==(const uniform_int_distribution& a,
+ const uniform_int_distribution& b) {
+ return a.param_ == b.param_;
+ }
+ friend bool operator!=(const uniform_int_distribution& a,
+ const uniform_int_distribution& b) {
+ return !(a == b);
+ }
+
+ private:
+ // Generates a value in the *closed* interval [0, R]
+ template <typename URBG>
+ unsigned_type Generate(URBG& g, // NOLINT(runtime/references)
+ unsigned_type R);
+ param_type param_;
+};
+
+// -----------------------------------------------------------------------------
+// Implementation details follow
+// -----------------------------------------------------------------------------
+template <typename CharT, typename Traits, typename IntType>
+std::basic_ostream<CharT, Traits>& operator<<(
+ std::basic_ostream<CharT, Traits>& os,
+ const uniform_int_distribution<IntType>& x) {
+ using stream_type =
+ typename random_internal::stream_format_type<IntType>::type;
+ auto saver = random_internal::make_ostream_state_saver(os);
+ os << static_cast<stream_type>(x.a()) << os.fill()
+ << static_cast<stream_type>(x.b());
+ return os;
+}
+
+template <typename CharT, typename Traits, typename IntType>
+std::basic_istream<CharT, Traits>& operator>>(
+ std::basic_istream<CharT, Traits>& is,
+ uniform_int_distribution<IntType>& x) {
+ using param_type = typename uniform_int_distribution<IntType>::param_type;
+ using result_type = typename uniform_int_distribution<IntType>::result_type;
+ using stream_type =
+ typename random_internal::stream_format_type<IntType>::type;
+
+ stream_type a;
+ stream_type b;
+
+ auto saver = random_internal::make_istream_state_saver(is);
+ is >> a >> b;
+ if (!is.fail()) {
+ x.param(
+ param_type(static_cast<result_type>(a), static_cast<result_type>(b)));
+ }
+ return is;
+}
+
+template <typename IntType>
+template <typename URBG>
+typename random_internal::make_unsigned_bits<IntType>::type
+uniform_int_distribution<IntType>::Generate(
+ URBG& g, // NOLINT(runtime/references)
+ typename random_internal::make_unsigned_bits<IntType>::type R) {
+ random_internal::FastUniformBits<unsigned_type> fast_bits;
+ unsigned_type bits = fast_bits(g);
+ const unsigned_type Lim = R + 1;
+ if ((R & Lim) == 0) {
+ // If the interval's length is a power of two range, just take the low bits.
+ return bits & R;
+ }
+
+ // Generates a uniform variate on [0, Lim) using fixed-point multiplication.
+ // The above fast-path guarantees that Lim is representable in unsigned_type.
+ //
+ // Algorithm adapted from
+ // http://lemire.me/blog/2016/06/30/fast-random-shuffling/, with added
+ // explanation.
+ //
+ // The algorithm creates a uniform variate `bits` in the interval [0, 2^N),
+ // and treats it as the fractional part of a fixed-point real value in [0, 1),
+ // multiplied by 2^N. For example, 0.25 would be represented as 2^(N - 2),
+ // because 2^N * 0.25 == 2^(N - 2).
+ //
+ // Next, `bits` and `Lim` are multiplied with a wide-multiply to bring the
+ // value into the range [0, Lim). The integral part (the high word of the
+ // multiplication result) is then very nearly the desired result. However,
+ // this is not quite accurate; viewing the multiplication result as one
+ // double-width integer, the resulting values for the sample are mapped as
+ // follows:
+ //
+ // If the result lies in this interval: Return this value:
+ // [0, 2^N) 0
+ // [2^N, 2 * 2^N) 1
+ // ... ...
+ // [K * 2^N, (K + 1) * 2^N) K
+ // ... ...
+ // [(Lim - 1) * 2^N, Lim * 2^N) Lim - 1
+ //
+ // While all of these intervals have the same size, the result of `bits * Lim`
+ // must be a multiple of `Lim`, and not all of these intervals contain the
+ // same number of multiples of `Lim`. In particular, some contain
+ // `F = floor(2^N / Lim)` and some contain `F + 1 = ceil(2^N / Lim)`. This
+ // difference produces a small nonuniformity, which is corrected by applying
+ // rejection sampling to one of the values in the "larger intervals" (i.e.,
+ // the intervals containing `F + 1` multiples of `Lim`.
+ //
+ // An interval contains `F + 1` multiples of `Lim` if and only if its smallest
+ // value modulo 2^N is less than `2^N % Lim`. The unique value satisfying
+ // this property is used as the one for rejection. That is, a value of
+ // `bits * Lim` is rejected if `(bit * Lim) % 2^N < (2^N % Lim)`.
+
+ using helper = random_internal::wide_multiply<unsigned_type>;
+ auto product = helper::multiply(bits, Lim);
+
+ // Two optimizations here:
+ // * Rejection occurs with some probability less than 1/2, and for reasonable
+ // ranges considerably less (in particular, less than 1/(F+1)), so
+ // ABSL_PREDICT_FALSE is apt.
+ // * `Lim` is an overestimate of `threshold`, and doesn't require a divide.
+ if (ABSL_PREDICT_FALSE(helper::lo(product) < Lim)) {
+ // This quantity is exactly equal to `2^N % Lim`, but does not require high
+ // precision calculations: `2^N % Lim` is congruent to `(2^N - Lim) % Lim`.
+ // Ideally this could be expressed simply as `-X` rather than `2^N - X`, but
+ // for types smaller than int, this calculation is incorrect due to integer
+ // promotion rules.
+ const unsigned_type threshold =
+ ((std::numeric_limits<unsigned_type>::max)() - Lim + 1) % Lim;
+ while (helper::lo(product) < threshold) {
+ bits = fast_bits(g);
+ product = helper::multiply(bits, Lim);
+ }
+ }
+
+ return helper::hi(product);
+}
+
+} // namespace absl
+
+#endif // ABSL_RANDOM_UNIFORM_INT_DISTRIBUTION_H_