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rocrand.hpp
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rocrand.hpp
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// Copyright (c) 2017-2024 Advanced Micro Devices, Inc. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
// THE SOFTWARE.
#ifndef ROCRAND_HPP_
#define ROCRAND_HPP_
// At least C++11 required
#if defined(__cplusplus) && __cplusplus >= 201103L
#include "rocrand/rocrand.h"
#include "rocrand/rocrand_kernel.h"
#include <exception>
#include <limits>
#include <random>
#include <sstream>
#include <string>
#include <type_traits>
#include <cassert>
namespace rocrand_cpp {
/// \rocrand_internal \addtogroup rocrandhostcpp
/// @{
/// \class error
/// \brief A run-time rocRAND error.
///
/// The error class represents an error returned
/// by a rocRAND function.
class error : public std::exception
{
public:
/// rocRAND error code type
typedef rocrand_status error_type;
/// Constructs new error object from error code \p error.
///
/// \param error - error code
explicit error(error_type error) noexcept
: m_error(error),
m_error_string(to_string(error))
{
}
/// Returns the numeric error code.
error_type error_code() const noexcept
{
return m_error;
}
/// Returns a string description of the error.
std::string error_string() const noexcept
{
return m_error_string;
}
/// Returns a C-string description of the error.
const char* what() const noexcept override
{
return m_error_string.c_str();
}
/// Static function which converts the numeric rocRAND
/// error code \p error to a human-readable string.
///
/// If the error code is unknown, a string containing
/// "Unknown rocRAND error" along with the error code
/// \p error will be returned.
static std::string to_string(error_type error)
{
switch(error)
{
case ROCRAND_STATUS_SUCCESS:
return "Success";
case ROCRAND_STATUS_VERSION_MISMATCH:
return "Header file and linked library version do not match";
case ROCRAND_STATUS_NOT_CREATED:
return "Generator was not created using rocrand_create_generator";
case ROCRAND_STATUS_ALLOCATION_FAILED:
return "Memory allocation failed during execution";
case ROCRAND_STATUS_TYPE_ERROR:
return "Generator type is wrong";
case ROCRAND_STATUS_OUT_OF_RANGE:
return "Argument out of range";
case ROCRAND_STATUS_LENGTH_NOT_MULTIPLE:
return "Length requested is not a multiple of dimension";
case ROCRAND_STATUS_DOUBLE_PRECISION_REQUIRED:
return "GPU does not have double precision";
case ROCRAND_STATUS_LAUNCH_FAILURE:
return "Kernel launch failure";
case ROCRAND_STATUS_INTERNAL_ERROR:
return "Internal library error";
default: {
std::stringstream s;
s << "Unknown rocRAND error (" << error << ")";
return s.str();
}
}
}
/// Compares two error objects for equality.
friend
bool operator==(const error& l, const error& r)
{
return l.error_code() == r.error_code();
}
/// Compares two error objects for inequality.
friend
bool operator!=(const error& l, const error& r)
{
return !(l == r);
}
private:
error_type m_error;
std::string m_error_string;
};
/// \class uniform_int_distribution
///
/// \brief Produces random integer values uniformly distributed on the interval [0, 2^(sizeof(IntType)*8) - 1].
///
/// \tparam IntType - type of generated values. Only \p unsigned \p char, \p unsigned \p short and \p unsigned \p int and \p unsigned \p long \p long \p int type is supported.
template<class IntType = unsigned int>
class uniform_int_distribution
{
static_assert(std::is_same<unsigned char, IntType>::value
|| std::is_same<unsigned short, IntType>::value
|| std::is_same<unsigned long long int, IntType>::value
|| std::is_same<unsigned int, IntType>::value,
"Only unsigned char, unsigned short, unsigned int and unsigned long long int "
"types are supported in uniform_int_distribution");
public:
/// See description for IntType template parameter.
typedef IntType result_type;
/// Default constructor
uniform_int_distribution()
{
}
/// Resets distribution's internal state if there is any.
static void reset()
{
}
/// Returns the smallest possible value that can be generated.
static constexpr IntType min()
{
return 0;
}
/// Returns the largest possible value that can be generated.
static constexpr IntType max()
{
return std::numeric_limits<IntType>::max();
}
/// \brief Fills \p output with uniformly distributed random integer values.
///
/// Generates \p size random integer values uniformly distributed
/// on the interval [0, 2^(sizeof(IntType)*8) - 1], and stores them into the device memory
/// referenced by \p output pointer.
///
/// \param g - An uniform random number generator object
/// \param output - Pointer to device memory to store results
/// \param size - Number of values to generate
///
/// Requirements:
/// * The device memory pointed by \p output must have been previously allocated
/// and be large enough to store at least \p size values of \p IntType type.
/// * If generator \p g is a quasi-random number generator (`rocrand_cpp::sobol32_engine`),
/// then \p size must be a multiple of that generator's dimension.
///
/// See also: rocrand_generate(), rocrand_generate_char(), rocrand_generate_short()
template<class Generator>
void operator()(Generator& g, IntType * output, size_t size)
{
rocrand_status status;
status = this->generate(g, output, size);
if(status != ROCRAND_STATUS_SUCCESS) throw rocrand_cpp::error(status);
}
/// Returns \c true if the distribution is the same as \p other.
bool operator==(const uniform_int_distribution<IntType>& other) const
{
(void) other;
return true;
}
/// Returns \c true if the distribution is different from \p other.
bool operator!=(const uniform_int_distribution<IntType>& other) const
{
return !(*this == other);
}
private:
template<class Generator>
static rocrand_status generate(Generator& g, unsigned char * output, size_t size)
{
return rocrand_generate_char(g.m_generator, output, size);
}
template<class Generator>
static rocrand_status generate(Generator& g, unsigned short * output, size_t size)
{
return rocrand_generate_short(g.m_generator, output, size);
}
template<class Generator>
static rocrand_status generate(Generator& g, unsigned int * output, size_t size)
{
return rocrand_generate(g.m_generator, output, size);
}
template<class Generator>
static rocrand_status generate(Generator& g, unsigned long long int* output, size_t size)
{
return rocrand_generate_long_long(g.m_generator, output, size);
}
};
/// \class uniform_real_distribution
///
/// \brief Produces random floating-point values uniformly distributed on the interval (0, 1].
///
/// \tparam RealType - type of generated values. Only \p float, \p double and \p half types are supported.
template<class RealType = float>
class uniform_real_distribution
{
static_assert(
std::is_same<float, RealType>::value
|| std::is_same<double, RealType>::value
|| std::is_same<half, RealType>::value,
"Only float, double, and half types are supported in uniform_real_distribution"
);
public:
/// See description for RealType template parameter.
typedef RealType result_type;
/// Default constructor
uniform_real_distribution()
{
}
/// Resets distribution's internal state if there is any.
static void reset()
{
}
/// Returns the smallest possible value that can be generated.
static constexpr RealType min()
{
return static_cast<RealType>(ROCRAND_2POW32_INV_DOUBLE);
}
/// Returns the largest possible value that can be generated.
static constexpr RealType max()
{
return 1.0;
}
/// \brief Fills \p output with uniformly distributed random floating-point values.
///
/// Generates \p size random floating-point values uniformly distributed
/// on the interval (0, 1], and stores them into the device memory referenced
/// by \p output pointer.
///
/// \param g - An uniform random number generator object
/// \param output - Pointer to device memory to store results
/// \param size - Number of values to generate
///
/// Requirements:
/// * The device memory pointed by \p output must have been previously allocated
/// and be large enough to store at least \p size values of \p RealType type.
/// * If generator \p g is a quasi-random number generator (`rocrand_cpp::sobol32_engine`),
/// then \p size must be a multiple of that generator's dimension.
///
/// See also: rocrand_generate_uniform(), rocrand_generate_uniform_double(), rocrand_generate_uniform_half()
template<class Generator>
void operator()(Generator& g, RealType * output, size_t size)
{
rocrand_status status;
status = this->generate(g, output, size);
if(status != ROCRAND_STATUS_SUCCESS) throw rocrand_cpp::error(status);
}
/// Returns \c true if the distribution is the same as \p other.
bool operator==(const uniform_real_distribution<RealType>& other) const
{
(void) other;
return true;
}
/// Returns \c true if the distribution is different from \p other.
bool operator!=(const uniform_real_distribution<RealType>& other) const
{
return !(*this == other);
}
private:
template<class Generator>
static rocrand_status generate(Generator& g, float * output, size_t size)
{
return rocrand_generate_uniform(g.m_generator, output, size);
}
template<class Generator>
static rocrand_status generate(Generator& g, double * output, size_t size)
{
return rocrand_generate_uniform_double(g.m_generator, output, size);
}
template<class Generator>
static rocrand_status generate(Generator& g, half * output, size_t size)
{
return rocrand_generate_uniform_half(g.m_generator, output, size);
}
};
/// \class normal_distribution
///
/// \brief Produces random numbers according to a normal distribution.
///
/// \tparam RealType - type of generated values. Only \p float, \p double and \p half types are supported.
template<class RealType = float>
class normal_distribution
{
static_assert(
std::is_same<float, RealType>::value
|| std::is_same<double, RealType>::value
|| std::is_same<half, RealType>::value,
"Only float, double and half types are supported in normal_distribution"
);
public:
/// See description for RealType template parameter.
typedef RealType result_type;
/// \class param_type
/// \brief The type of the distribution parameter set.
class param_type
{
public:
/// Alias for convenience
using distribution_type = normal_distribution<RealType>;
/// \brief Constructs a \p param_type object with the
/// given distribution parameters.
/// \param mean - mean
/// \param stddev - standard deviation
param_type(RealType mean = 0.0, RealType stddev = 1.0)
: m_mean(mean), m_stddev(stddev)
{
}
/// Copy constructor
param_type(const param_type& params) = default;
/// Copy assignment operator
param_type& operator=(const param_type& params) = default;
/// \brief Returns the deviation distribution parameter.
///
/// The default value is 0.0.
RealType mean() const
{
return m_mean;
}
/// \brief Returns the standard deviation distribution parameter.
///
/// The default value is 1.0.
RealType stddev() const
{
return m_stddev;
}
/// Returns \c true if the param_type is the same as \p other.
bool operator==(const param_type& other) const
{
return m_mean == other.m_mean && m_stddev == other.m_stddev;
}
/// Returns \c true if the param_type is different from \p other.
bool operator!=(const param_type& other) const
{
return !(*this == other);
}
private:
RealType m_mean;
RealType m_stddev;
};
/// \brief Constructs a new distribution object.
/// \param mean - A mean distribution parameter
/// \param stddev - A standard deviation distribution parameter
normal_distribution(RealType mean = 0.0, RealType stddev = 1.0)
: m_params(mean, stddev)
{
}
/// \brief Constructs a new distribution object.
/// \param params - Distribution parameters
explicit normal_distribution(const param_type& params)
: m_params(params)
{
}
/// Resets distribution's internal state if there is any.
static void reset()
{
}
/// \brief Returns the mean distribution parameter.
///
/// The mean specifies the location of the peak. The default value is 0.0.
RealType mean() const
{
return m_params.mean();
}
/// \brief Returns the standard deviation distribution parameter.
///
/// The default value is 1.0.
RealType stddev() const
{
return m_params.stddev();
}
/// Returns the smallest possible value that can be generated.
static constexpr RealType min()
{
return std::numeric_limits<RealType>::lowest();
}
/// Returns the largest possible value that can be generated.
static constexpr RealType max()
{
return std::numeric_limits<RealType>::max();
}
/// Returns the distribution parameter object
param_type param() const
{
return m_params;
}
/// Sets the distribution parameter object
void param(const param_type& params)
{
m_params = params;
}
/// \brief Fills \p output with normally distributed random floating-point values.
///
/// Generates \p size random floating-point values distributed according to a normal distribution,
/// and stores them into the device memory referenced by \p output pointer.
///
/// \param g - An uniform random number generator object
/// \param output - Pointer to device memory to store results
/// \param size - Number of values to generate
///
/// Requirements:
/// * The device memory pointed by \p output must have been previously allocated
/// and be large enough to store at least \p size values of \p RealType type.
/// * Pointer \p output must be aligned to <tt>2 * sizeof(RealType)</tt> bytes.
/// * \p size must be even.
/// * If generator \p g is a quasi-random number generator (`rocrand_cpp::sobol32_engine`),
/// then \p size must be a multiple of that generator's dimension.
///
/// See also: rocrand_generate_normal(), rocrand_generate_normal_double(), rocrand_generate_normal_half()
template<class Generator>
void operator()(Generator& g, RealType * output, size_t size)
{
rocrand_status status;
status = this->generate(g, output, size);
if(status != ROCRAND_STATUS_SUCCESS) throw rocrand_cpp::error(status);
}
/// \brief Returns \c true if the distribution is the same as \p other.
///
/// Two distribution are equal, if their parameters are equal.
bool operator==(const normal_distribution<RealType>& other) const
{
return this->m_params == other.m_params;
}
/// \brief Returns \c true if the distribution is different from \p other.
///
/// Two distribution are equal, if their parameters are equal.
bool operator!=(const normal_distribution<RealType>& other) const
{
return !(*this == other);
}
private:
template<class Generator>
rocrand_status generate(Generator& g, float * output, size_t size)
{
return rocrand_generate_normal(
g.m_generator, output, size, this->mean(), this->stddev()
);
}
template<class Generator>
rocrand_status generate(Generator& g, double * output, size_t size)
{
return rocrand_generate_normal_double(
g.m_generator, output, size, this->mean(), this->stddev()
);
}
template<class Generator>
rocrand_status generate(Generator& g, half * output, size_t size)
{
return rocrand_generate_normal_half(
g.m_generator, output, size, this->mean(), this->stddev()
);
}
param_type m_params;
};
/// \class lognormal_distribution
///
/// \brief Produces positive random numbers according to a log-normal distribution.
///
/// \tparam RealType - type of generated values. Only \p float, \p double and \p half types are supported.
template<class RealType = float>
class lognormal_distribution
{
static_assert(
std::is_same<float, RealType>::value
|| std::is_same<double, RealType>::value
|| std::is_same<half, RealType>::value,
"Only float, double and half types are supported in lognormal_distribution"
);
public:
/// See description for RealType template parameter.
typedef RealType result_type;
/// \class param_type
/// \brief The type of the distribution parameter set.
class param_type
{
public:
/// Alias for convenience
using distribution_type = lognormal_distribution<RealType>;
/// \brief Constructs a \p param_type object with the
/// given distribution parameters.
/// \param m - mean
/// \param s - standard deviation
param_type(RealType m = 0.0, RealType s = 1.0)
: m_mean(m), m_stddev(s)
{
}
/// Copy constructor
param_type(const param_type& params) = default;
/// Copy assignment operator
param_type& operator=(const param_type& params) = default;
/// \brief Returns the deviation distribution parameter.
///
/// The default value is 1.0.
RealType m() const
{
return m_mean;
}
/// \brief Returns the deviation distribution parameter.
///
/// The default value is 1.0.
RealType s() const
{
return m_stddev;
}
/// Returns \c true if the param_type is the same as \p other.
bool operator==(const param_type& other) const
{
return m_mean == other.m_mean && m_stddev == other.m_stddev;
}
/// Returns \c true if the param_type is different from \p other.
bool operator!=(const param_type& other) const
{
return !(*this == other);
}
private:
RealType m_mean;
RealType m_stddev;
};
/// \brief Constructs a new distribution object.
/// \param m - A mean distribution parameter
/// \param s - A standard deviation distribution parameter
lognormal_distribution(RealType m = 0.0, RealType s = 1.0)
: m_params(m, s)
{
}
/// \brief Constructs a new distribution object.
/// \param params - Distribution parameters
explicit lognormal_distribution(const param_type& params)
: m_params(params)
{
}
/// Resets distribution's internal state if there is any.
static void reset()
{
}
/// \brief Returns the mean distribution parameter.
///
/// The mean specifies the location of the peak. The default value is 0.0.
RealType m() const
{
return m_params.m();
}
/// \brief Returns the standard deviation distribution parameter.
///
/// The default value is 1.0.
RealType s() const
{
return m_params.s();
}
/// Returns the distribution parameter object
param_type param() const
{
return m_params;
}
/// Sets the distribution parameter object
void param(const param_type& params)
{
m_params = params;
}
/// Returns the smallest possible value that can be generated.
static constexpr RealType min()
{
return 0;
}
/// Returns the largest possible value that can be generated.
static RealType max()
{
return std::numeric_limits<RealType>::max();
}
/// \brief Fills \p output with log-normally distributed random floating-point values.
///
/// Generates \p size random floating-point values (greater than zero) distributed according
/// to a log-normal distribution, and stores them into the device memory referenced
/// by \p output pointer.
///
/// \param g - An uniform random number generator object
/// \param output - Pointer to device memory to store results
/// \param size - Number of values to generate
///
/// Requirements:
/// * The device memory pointed by \p output must have been previously allocated
/// and be large enough to store at least \p size values of \p RealType type.
/// * Pointer \p output must be aligned to <tt>2 * sizeof(RealType)</tt> bytes.
/// * \p size must be even.
/// * If generator \p g is a quasi-random number generator (`rocrand_cpp::sobol32_engine`),
/// then \p size must be a multiple of that generator's dimension.
///
/// See also: rocrand_generate_log_normal(), rocrand_generate_log_normal_double()
template<class Generator>
void operator()(Generator& g, RealType * output, size_t size)
{
rocrand_status status;
status = this->generate(g, output, size);
if(status != ROCRAND_STATUS_SUCCESS) throw rocrand_cpp::error(status);
}
/// \brief Returns \c true if the distribution is the same as \p other.
///
/// Two distribution are equal, if their parameters are equal.
bool operator==(const lognormal_distribution<RealType>& other) const
{
return this->m_params == other.m_params;
}
/// \brief Returns \c true if the distribution is different from \p other.
///
/// Two distribution are equal, if their parameters are equal.
bool operator!=(const lognormal_distribution<RealType>& other) const
{
return !(*this == other);
}
private:
template<class Generator>
rocrand_status generate(Generator& g, float * output, size_t size)
{
return rocrand_generate_log_normal(
g.m_generator, output, size, this->m(), this->s()
);
}
template<class Generator>
rocrand_status generate(Generator& g, double * output, size_t size)
{
return rocrand_generate_log_normal_double(
g.m_generator, output, size, this->m(), this->s()
);
}
template<class Generator>
rocrand_status generate(Generator& g, half * output, size_t size)
{
return rocrand_generate_log_normal_half(
g.m_generator, output, size, this->m(), this->s()
);
}
param_type m_params;
};
/// \class poisson_distribution
///
/// \brief Produces random non-negative integer values distributed according to Poisson distribution.
///
/// \tparam IntType - type of generated values. Only \p unsinged \p int type is supported.
template<class IntType = unsigned int>
class poisson_distribution
{
static_assert(
std::is_same<unsigned int, IntType>::value,
"Only unsigned int type is supported in poisson_distribution"
);
public:
/// See description for IntType template parameter.
typedef IntType result_type;
/// \class param_type
/// \brief The type of the distribution parameter set.
class param_type
{
public:
/// Alias for convenience.
using distribution_type = poisson_distribution<IntType>;
/// \brief Constructs a \p param_type object with the
/// given mean.
/// \param mean - mean to use for the distribution
param_type(double mean = 1.0)
: m_mean(mean)
{
}
/// Copy constructor
param_type(const param_type& params) = default;
/// Copy assignment operator
param_type& operator=(const param_type& params) = default;
/// \brief Returns the mean distribution parameter.
///
/// The mean (also known as lambda) is the average number
/// of events per interval. The default value is 1.0.
double mean() const
{
return m_mean;
}
/// Returns \c true if the param_type is the same as \p other.
bool operator==(const param_type& other) const
{
return m_mean == other.m_mean;
}
/// Returns \c true if the param_type is different from \p other.
bool operator!=(const param_type& other) const
{
return !(*this == other);
}
private:
double m_mean;
};
/// \brief Constructs a new distribution object.
/// \param mean - A mean distribution parameter.
poisson_distribution(double mean = 1.0)
: m_params(mean)
{
}
/// \brief Constructs a new distribution object.
/// \param params - Distribution parameters
explicit poisson_distribution(const param_type& params)
: m_params(params)
{
}
/// Resets distribution's internal state if there is any.
static void reset()
{
}
/// \brief Returns the mean distribution parameter.
///
/// The mean (also known as lambda) is the average number
/// of events per interval. The default value is 1.0.
double mean() const
{
return m_params.mean();
}
/// Returns the smallest possible value that can be generated.
static constexpr IntType min()
{
return 0;
}
/// Returns the largest possible value that can be generated.
static constexpr IntType max()
{
return std::numeric_limits<IntType>::max();
}
/// Returns the distribution parameter object
param_type param()
{
return m_params;
}
/// Sets the distribution parameter object
void param(const param_type& params)
{
m_params = params;
}
/// \brief Fills \p output with random non-negative integer values
/// distributed according to Poisson distribution.
///
/// Generates \p size random non-negative integer values distributed according
/// to Poisson distribution, and stores them into the device memory referenced
/// by \p output pointer.
///
/// \param g - An uniform random number generator object
/// \param output - Pointer to device memory to store results
/// \param size - Number of values to generate
///
/// Requirements:
/// * The device memory pointed by \p output must have been previously allocated
/// and be large enough to store at least \p size values of \p IntType type.
/// * If generator \p g is a quasi-random number generator (`rocrand_cpp::sobol32_engine`),
/// then \p size must be a multiple of that generator's dimension.
///
/// See also: rocrand_generate_poisson()
template<class Generator>
void operator()(Generator& g, IntType * output, size_t size)
{
rocrand_status status;
status = rocrand_generate_poisson(g.m_generator, output, size, this->mean());
if(status != ROCRAND_STATUS_SUCCESS) throw rocrand_cpp::error(status);
}
/// \brief Returns \c true if the distribution is the same as \p other.
///
/// Two distribution are equal, if their parameters are equal.
bool operator==(const poisson_distribution<IntType>& other) const
{
return this->m_params == other.m_params;
}
/// \brief Returns \c true if the distribution is different from \p other.
///
/// Two distribution are equal, if their parameters are equal.
bool operator!=(const poisson_distribution<IntType>& other) const
{
return !(*this == other);
}
private:
param_type m_params;
};
/// \brief Pseudorandom number engine based Philox algorithm.
///
/// It generates random numbers of type \p unsigned \p int on the interval [0; 2^32 - 1].
/// Random numbers are generated in sets of four.
template<unsigned long long DefaultSeed = ROCRAND_PHILOX4x32_DEFAULT_SEED>
class philox4x32_10_engine
{
public:
/// \typedef result_type
/// Type of values generated by the random number engine.
typedef unsigned int result_type;
// \typedef order_type
/// Pseudo-random number engine ordering type.
/// Represents the ordering of the results of a random number engine.
///
/// See also: order()
typedef rocrand_ordering order_type;
/// \typedef offset_type
/// Pseudo-random number engine offset type.
/// Offset represents a number of the random number engine's states
/// that should be skipped before first value is generated.
///
/// See also: offset()
typedef unsigned long long offset_type;
/// \typedef seed_type
/// Pseudo-random number engine seed type definition.
///
/// See also: seed()
typedef unsigned long long seed_type;
/// \brief The default seed equal to \p DefaultSeed.
static constexpr seed_type default_seed = DefaultSeed;
/// \brief Constructs the pseudo-random number engine.
///
/// \param seed_value - seed value to use in the initialization of the internal state, see also seed()
/// \param offset_value - number of internal states that should be skipped, see also offset()
/// \param order_value - ordering of the sequences generated by the engine, see also order()
///
/// See also: rocrand_create_generator()
philox4x32_10_engine(seed_type seed_value = DefaultSeed,
offset_type offset_value = 0,
order_type order_value = ROCRAND_ORDERING_PSEUDO_DEFAULT)
{
rocrand_status status;
status = rocrand_create_generator(&m_generator, this->type());
if(status != ROCRAND_STATUS_SUCCESS) throw rocrand_cpp::error(status);
try
{
if(offset_value > 0)
{
this->offset(offset_value);
}
this->order(order_value);
this->seed(seed_value);
}
catch(...)
{
(void)rocrand_destroy_generator(m_generator);
throw;
}
}
/// \brief Constructs the pseudo-random number engine.
///
/// The pseudo-random number engine will be created using \p generator.
/// The constructed engine take ownership over \p generator, and sets
/// passed reference to \p NULL. The lifetime of \p generator is now
/// bound to the lifetime of the engine.
///
/// \param generator - rocRAND generator
explicit philox4x32_10_engine(rocrand_generator& generator)
: m_generator(generator)
{
if(generator == NULL)
{
throw rocrand_cpp::error(ROCRAND_STATUS_NOT_CREATED);
}
generator = NULL;
}
philox4x32_10_engine(const philox4x32_10_engine&) = delete;
philox4x32_10_engine& operator=(const philox4x32_10_engine&) = delete;
/// \brief Move construct from an other engine, moving the state over.
///