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View Code? Open in Web Editor NEWFastest Random Distribution Generator for Eigen
Home Page: https://bab2min.github.io/eigenrand/
License: MIT License
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kilasuelika rmalouf perara-libs seasony-org hxhc arkrde johnpekl m-henning-toptal feelpp manifoldfr gerhobbelteigenrand's Issues
uniformReal : Access violation reading location 0xFFFFFFFFFFFFFFFF with a specific congifuration
Hi so the error occurs in GenericPacketMath.h here (line 452) (In Eigen)
/** \internal copy the packet \a from to \a *to, (un-aligned store) */
template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
{ (*to) = from; }
The code I ran is this, and the error occurs when debugging the line where i define my X variable
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor> CMatrix;
using Eigen::Rand::Vmt19937_64;
using Eigen::Rand::uniformReal;
Vmt19937_64 gen_eigen;
CMatrix X = uniformReal<CMatrix>(5, 3, gen_eigen);
Any ideas?
Edit:
These work.
CMatrix X1 = uniformReal<CMatrix>(2, 3, gen_eigen);
CMatrix X1 = uniformReal<CMatrix>(5, 2, gen_eigen);
CMatrix X2 = uniformReal<CMatrix>(100, 2, gen_eigen);
CMatrix X3 = uniformReal<CMatrix>(100, 3, gen_eigen);
CMatrix X4 = uniformReal<CMatrix>(100, 10, gen_eigen);
Is there something wrong with the specific configuration of 5 rows and 3 columns?
Im using:
Eigen 3.3.9 specifically (https://gitlab.com/libeigen/eigen/-/tree/5f25bcf7d6918f5c6091fb4e961e5607e13b7324)
Unrealistic result of StdNormalGen.
My code:
#include <iostream>
#include <functional>
#include <Eigen/Dense>
#include <EigenRand/EigenRand>
using namespace std;
using namespace Eigen;
int main()
{
Rand::Vmt19937_64 urng{4212};
Rand::StdNormalGen<float> stdnorm;
for (int i = 0; i < 10; ++i)
{
cout << stdnorm.generate<Matrix<float, 4, -1>>(4, 1, urng) << endl;
};
};
``
Returning result:
-0
-6.42001
8.3635
-6.50135
1.90169
2.42386e-38
2.94601e-38
2.49921e-38
-0
0
-0
0
0.783801
0.534232
1.48888
0.844737
4.74061
7.18897
-0
-5.66121
1.59769e-38
2.74603e-38
0.594965
2.17096e-38
-1.74388
-0
-0
3.80259
6.58371e-39
0.81791
0.762132
1.40474e-38
-0
-2.30039
-0
-12.4106
1.05125
8.62637e-39
0.706428
4.00838e-38
One can see that there are many values very close to 0. It's unlikely that these values obey normal distribution.
I'm using EigenRand in 64bit Ubuntu and my CPU has AVX and SSE flags.
Is there any specific reason for the version constraint?
I tried to compile my code against Eigen 3.3.4 (bundled in Ubuntu 18.04) and manually relieved the version constraint. The compilation is successful, although I haven't tested the output. So I'm curious is there any specific reason for constraint Eigen > 3.3.7? It will be convenient if I don't need to override system Eigen.
Compilation error with Apple Silicon
I am trying to compile EigenRand on a Homebrewed macbook Pro with a M1 processor. Using the "Simple Random Generator Matrix Example" from https://bab2min.github.io/eigenrand/v0.3.3/en/getting_started.html, I have:
> g++ -I/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/ -I./EigenRand/ -std=c++11 test.cpp
In file included from test.cpp:3:
In file included from ./EigenRand/EigenRand/EigenRand:17:
In file included from ./EigenRand/EigenRand/Core.h:16:
In file included from ./EigenRand/EigenRand/RandUtils.h:17:
./EigenRand/EigenRand/PacketRandomEngine.h:321:15: error: no member named 'split_two' in namespace 'Eigen::internal'
internal::split_two(operator()(), a, cache);
~~~~~~~~~~^
In file included from test.cpp:3:
In file included from ./EigenRand/EigenRand/EigenRand:17:
In file included from ./EigenRand/EigenRand/Core.h:16:
./EigenRand/EigenRand/RandUtils.h:34:29: error: implicit instantiation of undefined template
'Eigen::internal::UniformRealUtils<__attribute__((neon_vector_type(4))) float, std::__1::mersenne_twister_engine<unsigned long long, 64,
312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>
&>'
struct RandUtils : public UniformRealUtils<PacketType, Rng>
^
./EigenRand/EigenRand/Dists/Basic.h:295:12: note: in instantiation of template class
'Eigen::internal::RandUtils<__attribute__((neon_vector_type(4))) float, std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156,
31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &>'
requested here
return RUtils{}.balanced(std::forward<Rng>(rng));
^
./EigenRand/EigenRand/RandUtils.h:455:25: note: in instantiation of function template specialization
'Eigen::Rand::BalancedGen<float>::packetOp<__attribute__((neon_vector_type(4))) float, std::__1::mersenne_twister_engine<unsigned long
long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43,
6364136223846793005> &>' requested here
return gen.template packetOp<Packet>(rng);
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/CoreEvaluators.h:360:168: note: in instantiation of function template
specialization 'Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float, std::__1::mersenne_twister_engine<unsigned long
long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43,
6364136223846793005> &, true>::packetOp<__attribute__((neon_vector_type(4))) float>' requested here
...EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType=0, IndexType=0) const { return op.template packetOp<T>(); }
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/CoreEvaluators.h:505:31: note: in instantiation of function template
specialization 'Eigen::internal::nullary_wrapper<float, Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float,
std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, true, false,
false>::packetOp<__attribute__((neon_vector_type(4))) float, long>' requested here
return m_wrapper.template packetOp<PacketType>(m_functor, index);
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/AssignEvaluator.h:658:87: note: in instantiation of function template
specialization 'Eigen::internal::evaluator<Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>,
float, std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, const Eigen::Matrix<float, -1, -1, 0, -1, -1> >
>::packet<16, __attribute__((neon_vector_type(4))) float, long>' requested here
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode,PacketType>(index));
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/AssignEvaluator.h:416:23: note: (skipping 4 contexts in backtrace; use
-ftemplate-backtrace-limit=0 to see all)
kernel.template assignPacket<dstAlignment, srcAlignment, PacketType>(index);
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/AssignEvaluator.h:804:3: note: in instantiation of function template
specialization 'Eigen::internal::call_assignment_no_alias<Eigen::Matrix<float, -1, -1, 0, -1, -1>,
Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float,
std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, const Eigen::Matrix<float, -1, -1, 0, -1, -1> >,
Eigen::internal::assign_op<float, float> >' requested here
call_assignment_no_alias(dst, src, func);
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/AssignEvaluator.h:782:3: note: in instantiation of function template
specialization 'Eigen::internal::call_assignment<Eigen::Matrix<float, -1, -1, 0, -1, -1>,
Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float,
std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, const Eigen::Matrix<float, -1, -1, 0, -1, -1> >,
Eigen::internal::assign_op<float, float> >' requested here
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/PlainObjectBase.h:714:17: note: in instantiation of function template
specialization 'Eigen::internal::call_assignment<Eigen::Matrix<float, -1, -1, 0, -1, -1>,
Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float,
std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, const Eigen::Matrix<float, -1, -1, 0, -1, -1> > >'
requested here
internal::call_assignment(this->derived(), other.derived());
^
/opt/homebrew/Cellar/eigen/3.3.9/include/eigen3/Eigen/src/Core/Matrix.h:225:20: note: in instantiation of function template specialization
'Eigen::PlainObjectBase<Eigen::Matrix<float, -1, -1, 0, -1, -1>
>::_set<Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float,
std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, const Eigen::Matrix<float, -1, -1, 0, -1, -1> > >'
requested here
return Base::_set(other);
^
test.cpp:17:7: note: in instantiation of function template specialization 'Eigen::Matrix<float, -1, -1, 0, -1,
-1>::operator=<Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BalancedGen<float>, float,
std::__1::mersenne_twister_engine<unsigned long long, 64, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17,
8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005> &, true>, const Eigen::Matrix<float, -1, -1, 0, -1, -1> > >'
requested here
mat = Rand::balancedLike(mat, urng);
^
./EigenRand/EigenRand/RandUtils.h:31:10: note: template is declared here
struct UniformRealUtils;
^
2 errors generated.This is what cpuinfo reports:
§ cpuinfo
Python Version: 3.9.2.final.0 (64 bit)
Cpuinfo Version: 8.0.0
Vendor ID Raw:
Hardware Raw:
Brand Raw: Apple M1
Hz Advertised Friendly:
Hz Actual Friendly:
Hz Advertised:
Hz Actual:
Arch: ARM_8
Bits: 64
Count: 8
Arch String Raw: arm64
L1 Data Cache Size:
L1 Instruction Cache Size:
L2 Cache Size:
L2 Cache Line Size:
L2 Cache Associativity:
L3 Cache Size:
Stepping:
Model:
Family:
Processor Type:
Flags:
§ g++ --version
Configured with: --prefix=/Library/Developer/CommandLineTools/usr --with-gxx-include-dir=/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include/c++/4.2.1
Apple clang version 12.0.0 (clang-1200.0.32.29)
Target: arm64-apple-darwin20.3.0
Thread model: posix
InstalledDir: /Library/Developer/CommandLineTools/usr/bin
How to generate different randomized matrices with min and max values?
I use the library to generate randomized arrays. I had 2 questions:
Why when I do
MatrixXd m{rows,cols}; Rand::Vmt19937_64 urng{ 42 }; Rand::balancedLike(m, urng); m = Rand::balancedLike(m, urng);
it always returns the same matrix with the same values.
And my other question: is it possible to choose min and max values to generate random numbers?
Adding PDFs/CDFs to the main library
Hi @bab2min ! Thanks for the great work you've done on this library. I'm using it for a purpose (importance sampling) where I need to compute the probability density or cumulative distribution functions of what I'm sampling.
I noticed some benchmarks implement some 1D pdfs and cdfs. Would you be interested in having those be part of the main library, as well as multivariate densities e.g. the multivariate normal density? For now what I've implemented is in my own client library, but I could make a PR if there's interest.
generates real vectors on a LOG multivariate normal distribution
It seems your package does not support generating a vector log norm, Isn't it? I have checked, it can only generate a number following log-normal distribution Eigen::Rand::LognormalGen.
How to include the library
Hello,
I may sound like a nooby but I'm going for it. How to include your library? I did not understand in your documentation you just say to download it and that's all but I guess there is not that to do. I already have Eigen. I am on Linux.
Thanks!
Cannot compile with `-march=native`
Hi,
I am trying to compile using -march=native to activate avx-stuff. However, I get some issue that I am not sure how to work around.
Example application
#include <iostream>
#include <random>
#include "EigenRand/EigenRand"
#include "Eigen/Dense"
template<typename Scalar, int Rows, int Cols>
inline void resample(Eigen::Matrix<Scalar, Rows, Cols> &mat, int i)
{
static Eigen::Rand::BinomialGen<int> bin_gen{1, 0.5};
static std::random_device seeder{};
static Eigen::Rand::P8_mt19937_64 uurg{seeder()};
Eigen::Matrix<int, Rows, 1> r = bin_gen.template generate<Eigen::Matrix<int, Rows, 1>>(mat.rows(), 1, uurg);
Eigen::Matrix<Scalar, Rows, 1> r_float = r.template cast<Scalar>();
mat.col(i) = 2.0 / mat.rows() * (r_float.array() - 0.5);
}
int main()
{
Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> mat{10, 2};
mat.setOnes();
resample(mat, 1);
std::cout << mat << "\n";
}
Compile command
g++ test.cc -I libs/EigenRand/ -I ~/.local/include/eigen3 -march=native
Compilation error
In file included from /home/jakkes/.local/include/eigen3/Eigen/Core:372,
from /home/jakkes/.local/include/eigen3/Eigen/Dense:1,
from libs/EigenRand/EigenRand/EigenRand:15,
from test.cc:4:
/home/jakkes/.local/include/eigen3/Eigen/src/Core/GenericPacketMath.h: In instantiation of ‘TgtPacket Eigen::internal::pcast(const SrcPacket&) [with SrcPacket = __vector(4) float; TgtPacket = __vector(2) long long int]’:
libs/EigenRand/EigenRand/Dists/Discrete.h:991:39: required from ‘const Packet Eigen::Rand::BinomialGen< <template-parameter-1-1> >::packetOp(Rng&&) [with Packet = __vector(2) long long int; Rng = Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&; _Scalar = int]’
libs/EigenRand/EigenRand/RandUtils.h:90:45: required from ‘const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, _mutable>::packetOp() const [with Packet = __vector(2) long long int; Gen = Eigen::Rand::BinomialGen<int>&; _Scalar = int; Rng = Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&; bool _mutable = false]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/CoreEvaluators.h:388:180: required from ‘T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(2) long long int; IndexType = long int; Scalar = int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/CoreEvaluators.h:533:68: required from ‘PacketType Eigen::internal::evaluator<Eigen::CwiseNullaryOp<NullaryOp, PlainObjectType> >::packet(IndexType) const [with int LoadMode = 32; PacketType = __vector(2) long long int; IndexType = long int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>; PlainObjectType = const Eigen::Matrix<int, -1, 1>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/AssignEvaluator.h:658:5: required from ‘void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignPacket(Eigen::Index) [with int StoreMode = 16; int LoadMode = 32; PacketType = __vector(2) long long int; DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Matrix<int, -1, 1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> > >; Functor = Eigen::internal::assign_op<int, int>; int Version = 0; Eigen::Index = long int]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/AssignEvaluator.h:416:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
/home/jakkes/.local/include/eigen3/Eigen/src/Core/AssignEvaluator.h:836:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<int, -1, 1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; Func = Eigen::internal::assign_op<int, int>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/PlainObjectBase.h:728:41: required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; Derived = Eigen::Matrix<int, -1, 1>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/PlainObjectBase.h:537:7: required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; Derived = Eigen::Matrix<int, -1, 1>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/Matrix.h:379:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; _Scalar = int; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’
test.cc:14:33: required from ‘void resample(Eigen::Matrix<Scalar, Rows, Cols>&, int) [with Scalar = double; int Rows = -1; int Cols = -1]’
test.cc:24:20: required from here
/home/jakkes/.local/include/eigen3/Eigen/src/Core/GenericPacketMath.h:136:10: error: invalid static_cast from type ‘const __vector(4) float’ to type ‘__vector(2) long long int’
136 | return static_cast<TgtPacket>(a);
| ^~~~~~~~~~~~~~~~~~~~~~~~~
/home/jakkes/.local/include/eigen3/Eigen/src/Core/GenericPacketMath.h: In instantiation of ‘TgtPacket Eigen::internal::pcast(const SrcPacket&) [with SrcPacket = __vector(2) long long int; TgtPacket = __vector(4) float]’:
libs/EigenRand/EigenRand/MorePacketMath.h:294:32: required from ‘typename std::enable_if<Eigen::internal::IsFloatPacket<Ty>::value>::type Eigen::internal::psincos(Packet, Packet&, Packet&) [with Packet = __vector(4) float; typename std::enable_if<Eigen::internal::IsFloatPacket<Ty>::value>::type = void]’
libs/EigenRand/EigenRand/Dists/Discrete.h:970:14: required from ‘const Packet Eigen::Rand::BinomialGen< <template-parameter-1-1> >::packetOp(Rng&&) [with Packet = __vector(2) long long int; Rng = Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&; _Scalar = int]’
libs/EigenRand/EigenRand/RandUtils.h:90:45: required from ‘const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, _mutable>::packetOp() const [with Packet = __vector(2) long long int; Gen = Eigen::Rand::BinomialGen<int>&; _Scalar = int; Rng = Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&; bool _mutable = false]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/CoreEvaluators.h:388:180: required from ‘T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(2) long long int; IndexType = long int; Scalar = int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/CoreEvaluators.h:533:68: required from ‘PacketType Eigen::internal::evaluator<Eigen::CwiseNullaryOp<NullaryOp, PlainObjectType> >::packet(IndexType) const [with int LoadMode = 32; PacketType = __vector(2) long long int; IndexType = long int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>; PlainObjectType = const Eigen::Matrix<int, -1, 1>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/AssignEvaluator.h:658:5: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
/home/jakkes/.local/include/eigen3/Eigen/src/Core/AssignEvaluator.h:836:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Matrix<int, -1, 1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; Func = Eigen::internal::assign_op<int, int>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/PlainObjectBase.h:728:41: required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; Derived = Eigen::Matrix<int, -1, 1>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/PlainObjectBase.h:537:7: required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; Derived = Eigen::Matrix<int, -1, 1>]’
/home/jakkes/.local/include/eigen3/Eigen/src/Core/Matrix.h:379:29: required from ‘Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::BinomialGen<int>&, int, Eigen::Rand::ParallelRandomEngineAdaptor<long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, false>, const Eigen::Matrix<int, -1, 1> >; _Scalar = int; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]’
test.cc:14:33: required from ‘void resample(Eigen::Matrix<Scalar, Rows, Cols>&, int) [with Scalar = double; int Rows = -1; int Cols = -1]’
test.cc:24:20: required from here
/home/jakkes/.local/include/eigen3/Eigen/src/Core/GenericPacketMath.h:136:10: error: invalid static_cast from type ‘const __vector(2) long long int’ to type ‘__vector(4) float'
I have had no issue compiling Eigen with -march=native previously, before adding EigenRand to my application.
Thankful for any insight into how I could resolve this.
I am running AMD Ryzen 7 5800X, and g++-9 version 9.3.0
Conflict with other Eigen Dependents Template Libraries
I noticed conflict happens when RandEigen is used alongside another library which also uses eigen.
The conflict only happens with the definition of plgamma
<command-line>: note: this is the location of the previous definition
In file included from /usr/include/eigen3/unsupported/Eigen/SpecialFunctions:47,
from /usr/include/eigen3/unsupported/Eigen/CXX11/Tensor:30,
from /opt/ros/noetic/include/pinocchio/fwd.hpp:31,
[...]
/usr/include/eigen3/unsupported/Eigen/src/SpecialFunctions/SpecialFunctionsPacketMath.h:19:8: error: redefinition of ‘template<class Packet> Packet Eigen::internal::plgamma(const Packet&)’
19 | Packet plgamma(const Packet& a) { using numext::lgamma; return lgamma(a); }
| ^~~~~~~
In file included from /usr/local/include/EigenRand/RandUtils.h:15,
from /usr/local/include/EigenRand/Core.h:16,
from /usr/local/include/EigenRand/EigenRand:17,
[...]
/usr/local/include/EigenRand/MorePacketMath.h:181:30: note: ‘template<class Packet> Packet Eigen::internal::plgamma(const Packet&)’ previously declared here
181 | EIGEN_STRONG_INLINE Packet plgamma(const Packet& x)
| ^~~~~~~
Once plgamma is commented, it compiles just fine. (Also removing the comments and compiling a second time does not
raise any error. The error comes for the first build or after a make clean).
I tried to avoid circular declaration in my own code, it might be an error from my side but I reported it just in case.
CXX compiler: GNU 9.3.0
cmake version 3.16.3
Eigen 3.3.7
RandEigen version 0.3.2
uniformIntLike creates values outside [min,max]
EigenRand Version: 0.4.0
When trying to create uniform random values between -1 and 1 with Eigen::Rand::uniformIntLike I get also values equal 2.
I used the following code to create this bug:
#include <iostream>
#include <eigen3/Eigen/Dense>
#include <EigenRand/EigenRand>
int main(){
uint64_t seed = std::random_device{}();
Eigen::Rand::P8_mt19937_64 generator{seed};
Eigen::VectorXi p;
p.resize(2);
for (uint i = 0; i<100; i++){
auto x = Eigen::Rand::uniformIntLike(p, generator,-1,1);
std::cout << "x :" << x << std::endl;
}
}
In the output I one should see that there are values equal 2 though the range of the distribution is defined to be [-1,1].
For the range [0,1] the function works as described in the documentation.
error C2466: cannot allocate an array of constant size 0
I want to random matrix using C++11 RNG such as std::mt19937 with std::random_device. Every time it randoms different numbers. Your example using Rand::P8_mt19937_64 urng{ 42 }; produces the same number if I run in a loop.
The following code is working fine (building without any errors) with matrix, vector size is 4. It can also run and return a random matrix.
Eigen::Vector<double, 4> mu1;
Eigen::Matrix<double, 4, 4> cov1;
Eigen::Matrix<double, 4, -1> samples;
Eigen::Rand::MvNormalGen<double, 4> gen_init{ mu1, cov1 };
std::random_device rd;
std::mt19937 genn(rd());
samples = gen_init.generate(genn, 10);
But if I change the size to 2, 3, or 9 it has an error.
eigenrand\Dists/Basic.h(260): error C2466: cannot allocate an array of constant size 0
Eigen::Vector<double, 3> mu1;
Eigen::Matrix<double, 3, 3> cov1;
Eigen::Matrix<double, 3, -1> samples;
Eigen::Rand::MvNormalGen<double, 3> gen_init{ mu1, cov1 };
std::random_device rd;
std::mt19937 genn(rd());
samples = gen_init.generate(genn, 10);
NOTE: It happens on Windows, Ubuntu has no problem
Please Report Performance in ARM64 NEON architectures
From version 0.4.0 alpha onwards, EigenRand begins to support ARM64 experimentally.
If anyone report an issue or its performance on various real ARM machines here, it will be helpful for optimization.
Reporting Performance
Please report outputs from these 3 binaries below along with the details of the machine that runs them.
$ git clone https://github.com/bab2min/EigenRand
$ cd EigenRand
$ git clone https://github.com/google/googletest
$ pushd googletest && git checkout v1.8.x && popd
$ mkdir build && cd build
$ cmake -DCMAKE_BUILD_TYPE=Release -DEIGENRAND_CXX_FLAGS="-march=native" ..
$ make
$ ./EigenRand-accuracy # Binary for accuracy test of univariate random distributions
$ ./EigenRand-benchmark # Binary for performance test of univariate random distributions
$ ./EigenRand-benchmark-mv # Binary for performance test of multivariate random distributionsAdding General & Specialized Truncated Distribution
Getting template errors when including EigenRand
I am using MinGW64/GCC 10.2.0. When trying to include EigenRand like following:
#include <Eigen/Dense>
#include <EigenRand/EigenRand>
I get lots of template errors(have not tried to initialize anything with EigenRand yet):
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:15,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:709:32: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
[build] 709 | struct reinterpreter<Packet4f>
[build] | ^
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:728:32: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
[build] 728 | struct reinterpreter<Packet2d>
[build] | ^
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h: In function 'Packet Eigen::internal::pgather(const int*, const Packet&) [with Packet = Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>]':
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:872:21: error: cannot convert 'Eigen::internal::Packet4i*' {aka 'Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>*'} to '__m128i_u*'
[build] 872 | _mm_storeu_si128((Packet4i*)u, index);
[build] | ^~~~~~~~~~~~
[build] | |
[build] | Eigen::internal::Packet4i* {aka Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>*}
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/src/Core/util/ConfigureVectorization.h:345,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Core:22,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Dense:1,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:3:
[build] C:/msys64/mingw64/lib/gcc/x86_64-w64-mingw32/10.2.0/include/emmintrin.h:725:30: note: initializing argument 1 of 'void _mm_storeu_si128(__m128i_u*, __m128i)'
[build] 725 | _mm_storeu_si128 (__m128i_u *__P, __m128i __B)
[build] | ~~~~~~~~~~~^~~
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:15,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h: In function 'decltype (Eigen::internal::reinterpret_to_float(declval<Packet>())) Eigen::internal::pgather(const float*, const Packet&) [with Packet = Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>; decltype (Eigen::internal::reinterpret_to_float(declval<Packet>())) = __vector(4) float]':
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:884:21: error: cannot convert 'Eigen::internal::Packet4i*' {aka 'Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>*'} to '__m128i_u*'
[build] 884 | _mm_storeu_si128((Packet4i*)u, index);
[build] | ^~~~~~~~~~~~
[build] | |
[build] | Eigen::internal::Packet4i* {aka Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>*}
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/src/Core/util/ConfigureVectorization.h:345,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Core:22,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Dense:1,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:3:
[build] C:/msys64/mingw64/lib/gcc/x86_64-w64-mingw32/10.2.0/include/emmintrin.h:725:30: note: initializing argument 1 of 'void _mm_storeu_si128(__m128i_u*, __m128i)'
[build] 725 | _mm_storeu_si128 (__m128i_u *__P, __m128i __B)
[build] | ~~~~~~~~~~~^~~
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:15,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h: In function 'decltype (Eigen::internal::reinterpret_to_double(declval<Packet>())) Eigen::internal::pgather(const double*, const Packet&, bool) [with Packet = Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>; decltype (Eigen::internal::reinterpret_to_double(declval<Packet>())) = __vector(2) double]':
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:896:21: error: cannot convert 'Eigen::internal::Packet4i*' {aka 'Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>*'} to '__m128i_u*'
[build] 896 | _mm_storeu_si128((Packet4i*)u, index);
[build] | ^~~~~~~~~~~~
[build] | |
[build] | Eigen::internal::Packet4i* {aka Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>*}
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/src/Core/util/ConfigureVectorization.h:345,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Core:22,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Dense:1,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:3:
[build] C:/msys64/mingw64/lib/gcc/x86_64-w64-mingw32/10.2.0/include/emmintrin.h:725:30: note: initializing argument 1 of 'void _mm_storeu_si128(__m128i_u*, __m128i)'
[build] 725 | _mm_storeu_si128 (__m128i_u *__P, __m128i __B)
[build] | ~~~~~~~~~~~^~~
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:15,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h: In function 'Packet Eigen::internal::pcmpeq64(const Packet&, const Packet&) [with Packet = Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>]':
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:961:64: error: no matching function for call to 'pand(Eigen::internal::Packet4i&, __m128i)'
[build] 961 | return pand(c, _mm_shuffle_epi32(c, _MM_SHUFFLE(2, 3, 0, 1)));
[build] | ^
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Core:165,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/Dense:1,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:3:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/src/Core/GenericPacketMath.h:272:1: note: candidate: 'template<class Packet> Packet Eigen::internal::pand(const Packet&, const Packet&)'
[build] 272 | pand(const Packet& a, const Packet& b) {
[build] | ^~~~
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/eigen/Eigen/src/Core/GenericPacketMath.h:272:1: note: template argument deduction/substitution failed:
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:15,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/MorePacketMath.h:961:64: note: deduced conflicting types for parameter 'const Packet' ('Eigen::internal::eigen_packet_wrapper<__vector(2) long long int, 0>' and '__m128i')
[build] 961 | return pand(c, _mm_shuffle_epi32(c, _MM_SHUFFLE(2, 3, 0, 1)));
[build] | ^
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/PacketFilter.h: At global scope:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/PacketFilter.h:178:37: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
[build] 178 | std::array<internal::Packet4f, 4> selector;
[build] | ^
[build] In file included from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/Core.h:16,
[build] from C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/EigenRand:17,
[build] from C:\Users\the_s\Documents\coding\my-first-nn\src\Network.cpp:4:
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:347:40: warning: ignoring attributes on template argument 'Eigen::internal::Packet4f' {aka '__m128'} [-Wignored-attributes]
[build] 347 | struct UniformRealUtils<Packet4f, Rng> : public RawbitsMaker<Packet4i, Rng>
[build] | ^
[build] C:/Users/the_s/Documents/coding/my-first-nn/deps/EigenRand/EigenRand/RandUtils.h:362:40: warning: ignoring attributes on template argument 'Eigen::internal::Packet2d' {aka '__m128d'} [-Wignored-attributes]
[build] 362 | struct UniformRealUtils<Packet2d, Rng> : public RawbitsMaker<Packet4i, Rng>
[build] | ^
[build] mingw32-make[2]: *** [src\CMakeFiles\my_first_nn.dir\build.make:110: src/CMakeFiles/my_first_nn.dir/Network.cpp.obj] Error 1
[build] mingw32-make[1]: *** [CMakeFiles\Makefile2:112: src/CMakeFiles/my_first_nn.dir/all] Error 2
[build] mingw32-make: *** [Makefile:102: all] Error 2
Is it thread safe?
Hi! Thanks for the great library. I haven't seen this being mentioned in the docs or issues, so I just wanna ask to see if this library is thread safe, and more importantly, would the random number generator seeded uniquely across different threads?
Say if I have spawned multiple threads, and each of them constructed their own instances of Eigen::Rand::Vmt19937_64{}(i.e. Without fixed random seed). Would different thread guarantees to produce different random numbers?
I know some libraries (e.g. Eigen's own Rand) doesn't work across threads as they are not re-entrant
note that all functions generating random matrices are not re-entrant nor thread-safe. Those include DenseBase::Random(), and DenseBase::setRandom() despite a call to Eigen::initParallel(). This is because these functions are based on std::rand which is not re-entrant.
https://eigen.tuxfamily.org/dox/TopicMultiThreading.html
A different scenario would be a master thread constructs a Eigen::Rand::Vmt19937_64{}and each slave threads holds a reference to the same instance. I would assume it will not be thread safe in this case?
Rand::normal does not finish
Hello
I just tried the following line of codes:
#include <Eigen/Dense>
#include <EigenRand/EigenRand>
Eigen::Rand::Vmt19937_64 gen{ 42 };
Eigen::MatrixXd test = Eigen::Rand::normal<Eigen::MatrixXd>(3,3,gen,0,1);
std::cout << test << std::endl;`
I have no compilation issue (just warnings but I think it is normal according to another discussion issue on gitlab). However, I can wait 10 mins and I have absolutely no results.
I compile with g++ (C++ 17 or 11) and I have the Eigen version 3.7.7.
Thanks in advance
Compilation errors at MinGW64 + Eigen3.4.0 + AVX512
E:\AddInclude/EigenRand/Dists/NormalExp.h:79:12: error: no matching function for call to 'psincos(__vector(16) float&, __vector(16) float&, __vector(16) float&)'
79 | psincos(theta, sintheta, costheta);
| ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~
In file included from E:\AddInclude/EigenRand/RandUtils.h:15,
from E:\AddInclude/EigenRand/Core.h:16,
from E:\AddInclude/EigenRand/EigenRand:20,
from E:\CppRepo\EigenRand\tuto.cpp:3:
E:\AddInclude/EigenRand/MorePacketMath.h:273:11: note: candidate: 'template<class Packet> typename std::enable_if<Eigen::internal::IsFloatPacket<Ty>::value>::type Eigen::internal::psincos(Packet, Packet&, Packet&)'
273 | >::type psincos(Packet x, Packet& s, Packet& c)
| ^~~~~~~
E:\AddInclude/EigenRand/MorePacketMath.h:273:11: note: template argument deduction/substitution failed:
E:\AddInclude/EigenRand/MorePacketMath.h: In substitution of 'template<class Packet> typename std::enable_if<Eigen::internal::IsFloatPacket<Ty>::value>::type Eigen::internal::psincos(Packet, Packet&, Packet&) [with Packet = __vector(16) float]':
E:\AddInclude/EigenRand/Dists/NormalExp.h:79:12: required from 'const Packet Eigen::Rand::StdNormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(16) float; Rng = Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&; _Scalar = float]'
E:\AddInclude/EigenRand/RandUtils.h:130:45: required from 'const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, true>::packetOp() const [with Packet = __vector(16) float; Gen = Eigen::Rand::StdNormalGen<float>; _Scalar = float; Rng = Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&]'
E:\AddInclude/Eigen/src/Core/CoreEvaluators.h:402:180: required from 'T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(16) float; IndexType = int; Scalar = float; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>]'
E:\AddInclude/Eigen/src/Core/CoreEvaluators.h:547:68: required from 'PacketType Eigen::internal::evaluator<Eigen::CwiseNullaryOp<NullaryOp, PlainObjectType> >::packet(IndexType) const [with int LoadMode = 64; PacketType = __vector(16) float; IndexType = int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>; PlainObjectType = const Eigen::Array<float, -1, -1>]'
E:\AddInclude/Eigen/src/Core/AssignEvaluator.h:681:5: required from 'void Eigen::internal::generic_dense_assignment_kernel<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor, Version>::assignPacket(Eigen::Index) [with int StoreMode = 64; int LoadMode = 64; PacketType = __vector(16) float; DstEvaluatorTypeT = Eigen::internal::evaluator<Eigen::Array<float, -1, -1> >; SrcEvaluatorTypeT = Eigen::internal::evaluator<Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>, const Eigen::Array<float, -1, -1> > >; Functor = Eigen::internal::assign_op<float, float>; int Version = 0; Eigen::Index = int]'
E:\AddInclude/Eigen/src/Core/AssignEvaluator.h:437:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
E:\AddInclude/Eigen/src/Core/AssignEvaluator.h:944:31: required from 'static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<float, -1, -1>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>, const Eigen::Array<float, -1, -1> >; Functor = Eigen::internal::assign_op<float, float>; Weak = void]'
E:\AddInclude/Eigen/src/Core/AssignEvaluator.h:880:49: required from 'void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<float, -1, -1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>, const Eigen::Array<float, -1, -1> >; Func = Eigen::internal::assign_op<float, float>]'
E:\AddInclude/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>, const Eigen::Array<float, -1, -1> >; Derived = Eigen::Array<float, -1, -1>]'
E:\AddInclude/Eigen/src/Core/PlainObjectBase.h:594:7: required from 'Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>, const Eigen::Array<float, -1, -1> >; Derived = Eigen::Array<float, -1, -1>]'
E:\AddInclude/Eigen/src/Core/Array.h:288:29: required from 'Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Array(const Eigen::EigenBase<OtherDerived>&, typename Eigen::internal::enable_if<std::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::StdNormalGen<float>, float, Eigen::Rand::ParallelRandomEngineAdaptor<long long unsigned int, Eigen::Rand::MersenneTwister<__vector(4) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>, 8>&, true>, const Eigen::Array<float, -1, -1> >; _Scalar = float; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1; typename Eigen::internal::enable_if<std::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type = Eigen::Array<float, -1, -1>::PrivateType]'
Adding multivariate distribution
It is more useful to provide RNGs for multivariate distributions such as
- multivariate normal distribution
- Wishart / inverse-Wishart distribution
- other distributions listed on scipy.stats
Support Eigen 3.4.0
Since a new Eigen 3.4.0 has many internal changes, it isn't compatible to the current EigenRand. Thus it is need to support Eigen 3.4.0.
Large (scale) samples with MvNormalGen
Hi, apologies in advance as this may look long winded but to reproduce the issue simply just copy-paste the following piece of code
#include <Eigen/Dense>
#include <EigenRand/EigenRand>
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor> TMatrix;
typedef Eigen::VectorXd TVector;
using Eigen::Rand::Vmt19937_64;
Vmt19937_64 gen_eigen;
void cdist(const TMatrix& X1, const TMatrix& X2, TMatrix& D, bool squared = false) {
// |X1(i) - X2(j)^T|^2 = |X1(i)|^2 + |X2(j)|^2 - (2 * X1(i)^T X2(j))
D = ((-2.0 * (X1 * X2.transpose())).colwise()
+ X1.rowwise().squaredNorm()).rowwise()
+ X2.rowwise().squaredNorm().transpose();
if (!squared) { D = (D.array().sqrt()).matrix(); }
}
const TMatrix Matern52(const TMatrix& X1, const TMatrix& X2, TVector& length_scale) {
TMatrix R(X1.rows(), X2.rows());
const TMatrix X1sc = X1.array().rowwise() / length_scale.transpose().array();
const TMatrix X2sc = X2.array().rowwise() / length_scale.transpose().array();
cdist(X1sc, X2sc, R, false);
R *= sqrt(5);
return ((1 + R.array() + square(R.array()) / 3) * (exp(-R.array()))).matrix();
}
void xiong1d(const Eigen::Ref<const TMatrix>& X, Eigen::Ref<TMatrix> Y) {
Y = -0.5 * (sin((40 * pow((X.array() - 0.85), 4)).array()) * cos((2.5 * (X.array() - 0.95)).array()) + 0.5 * (X.array() - 0.9) + 1);
}
TMatrix sample_mvn(const TVector& mean, const TMatrix& K) {
MvNormalGen sampler = makeMvNormalGen(mean, K);
return sampler.generate(gen_eigen);
}
void test_mvn_sample() {
TVector x_range = TVector::LinSpaced(10, 0, 1);
TMatrix X = Eigen::Map<TVector>(x_range.data(), 10);
TMatrix Y(X.rows(), 1);
xiong1d(X, Y);
TVector length_scale = TVector::Ones(1);
TMatrix K = Matern52(X, X, length_scale);
std::cout << "K =\n" << K << std::endl;
TVector mean = TVector::Zero(X.rows());
TMatrix mvn_samples = sample_mvn(mean, K);
std::cout << "MVN_SAMPLE =\n" << mvn_samples << std::endl;
}
int main() {
test_mvn_sample();
return 0;
}
This should give out
K =
1 0.989851 0.960808 0.916168 0.859902 0.795934 0.727763 0.658294 0.589808 0.523994
0.989851 1 0.989851 0.960808 0.916168 0.859902 0.795934 0.727763 0.658294 0.589808
0.960808 0.989851 1 0.989851 0.960808 0.916168 0.859902 0.795934 0.727763 0.658294
0.916168 0.960808 0.989851 1 0.989851 0.960808 0.916168 0.859902 0.795934 0.727763
0.859902 0.916168 0.960808 0.989851 1 0.989851 0.960808 0.916168 0.859902 0.795934
0.795934 0.859902 0.916168 0.960808 0.989851 1 0.989851 0.960808 0.916168 0.859902
0.727763 0.795934 0.859902 0.916168 0.960808 0.989851 1 0.989851 0.960808 0.916168
0.658294 0.727763 0.795934 0.859902 0.916168 0.960808 0.989851 1 0.989851 0.960808
0.589808 0.658294 0.727763 0.795934 0.859902 0.916168 0.960808 0.989851 1 0.989851
0.523994 0.589808 0.658294 0.727763 0.795934 0.859902 0.916168 0.960808 0.989851 1
MVN_SAMPLE =
-8.07388
-7.99194
-7.75746
-7.41463
-6.69153
-5.8611
-5.10573
-4.42873
-3.50118
-2.69687
As you can see the MVN samples look out of range, reproducing this issue (same mean and K value) in python with numpy.random.default_rng().multivariate_normal(mean=mean, cov=K, check_valid='ignore') would (consistently) give me a max MVN range of around (-2, 2)
"fatal error: 'Eigen/Dense' file not found" when using Eigen in header-only mode
hello Bab2min, I am a novice at C++ and Eigen. I found your EigenRand library yesterday and I think it is awesome. However, I came across 2 issues.
- I use eigen with header-only mode, and I put the Eigen library under
./libs. Since EigenRand is also header only, I put EigenRand under./libs, too. The file structure is shown in the picture.
Then I use the code below to test EigenRand, and compile the eigen_demo.cpp with
clang++ eigen_demo.cpp -I libs/Eigen/ -I libs/EigenRand/ -o ./output/eigen_demo -lmkl_intel_lp64 -lmkl_gnu_thread -lmkl_core -lgomp -lpthread -lm -ldl -I /usr/include/mkl
However, it raised an error. I am not sure how to solve it. Is there something wrong in the compile command?
"In file included from eigen_demo.cpp:10:
./libs/EigenRand/EigenRand:15:10: fatal error: 'Eigen/Dense' file not found
#include <Eigen/Dense>
^~~~~~~~~~~~~
1 error generated."
#define EIGEN_USE_BLAS
#define EIGEN_USE_LAPACK
#define EIGEN_USE_MKL_ALL
#include <iostream>
#include <chrono>
#include <ctime>
#include <random>
#include "libs/Eigen/Dense"
#include "libs/EigenRand/EigenRand"
void RunTest(int size=100, size_t loops=10)
{
for (size_t i = 0; i <= loops; ++i)
{
std::srand((unsigned)time(NULL));
int urng = std::rand();
Eigen::Rand::NormalGen<double> norm_gen{ 0.0, 1.0 };
Eigen::MatrixXd A = norm_gen.template generate<Eigen::MatrixXd>(size, size, urng);
Eigen::MatrixXd B = A * A;
std::cout << urng << std::endl;
}
}
int main(){
RunTest();
return 0;
}- The other issue is that if I want to change the random seed in every loop, what is the proper way to achieve the goal. I use the
srandfunction, but I did't try because the code can't be compiled.😂
Because I am quite new to C++, I have to ask you for solutions. Hope I claimed the questions clearly and thank you for your great work.
Vectorisation over distribution parameters
Hi, fantastic work - it's making our code a lot faster! Having said that we got a bit stuck of generating an array/matrix of numbers from binomial distribution for different trials and probabilities. For example, in numpy you can run np.random.binomial(n, p) where n and p can either be a scalar (like in EigenRand) or arrays of the same dimensions. How difficult would it be to implement to implement a similar interface? Do you think it's possible to SIMD operations like this? Many thanks!
Performance comparison with a written eigenmvn
Thanks for this useful random module.
If I want to sample from Multivariate Normal Distribution, Could you please tell me the performance difference between EigenRand and this Github module, eigenmvn? Which one is faster or does it have the same sampling speed?
In EigenRand, I can do
Rand::P8_mt19937_64 urng{ 42 };
Rand::MvNormalGen<double, 4> gen_init{ mu, cov };
Matrix<double, 4, -1> samples = gen_init.generate(urng, 10);
In eigenmvn, I can do
EigenMultivariateNormal<double> norm_init(mu, cov);
norm_init.samples(10);
Automatic detection of CPU capabilities.
Is there a way the CPU capabilites can automatically being detected?
Since today EigenRand is used in all of the optmization algorithms of fcmaes
currently by hardcoding SSE2 support. Would be better if AVX support would be automatically detected
since fcmaes is used from Python and I cannot predict on which CPUs it is deployed.
But I already see a significant speedup, specially with machine learning tasks ( EvoJax uses some of my algos) which require up to a million random variable generations each iteration (lasting a few seconds).
Thks for this great project!
merge this project to Eigen?
I find Eigen's built-in RNG super slow and thank you for this great project. Have you contacted Eigen's developers to get it merged into Eigen?
Compilation Error when using Eigen double
System: Ubuntu 20.04
Compiler: g++ 9.3.0
When trying to use double type (double, ArrayXXd or MatrixXd), the compiler throws the following error:
/usr/local/include/Eigen/src/Core/GenericPacketMath.h: In instantiation of ‘Packet Eigen::internal::plog(const Packet&) [with Packet = __vector(2) double]’:
/usr/local/include/EigenRand/Dists/NormalExp.h:74:53: required from ‘const Packet Eigen::Rand::StdNormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/Dists/NormalExp.h:124:21: required from ‘const Packet Eigen::Rand::NormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/RandUtils.h:417:45: required from ‘const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, _mutable>::packetOp() const [with Packet = __vector(2) double; Gen = Eigen::Rand::NormalGen<double>&; _Scalar = double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; bool _mutable = false]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:360:180: required from ‘T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(2) double; IndexType = long int; Scalar = double; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:505:68: required from ‘PacketType Eigen::internal::evaluator<Eigen::CwiseNullaryOp<NullaryOp, PlainObjectType> >::packet(IndexType) const [with int LoadMode = 16; PacketType = __vector(2) double; IndexType = long int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>; PlainObjectType = const Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:658:5: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:879:31: required from ‘static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, -1, -1>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:836:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, -1, -1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Func = Eigen::internal::assign_op<double, double>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:732:41: required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:537:7: required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/Array.h:242:29: required from ‘Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Array(const Eigen::EigenBase<OtherDerived>&, typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1; typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type = Eigen::Array<double, -1, -1>::PrivateType]’
test_randeigen.cpp:19:59: required from here
/usr/local/include/Eigen/src/Core/GenericPacketMath.h:406:58: error: no matching function for call to ‘log(const __vector(2) double&)’
406 | Packet plog(const Packet& a) { using std::log; return log(a); }
| ~~~^~~
In file included from /usr/local/include/Eigen/Core:96,
from /usr/local/include/Eigen/Dense:1,
from test_randeigen.cpp:4:
/usr/include/c++/9/complex:817:5: note: candidate: ‘template<class _Tp> std::complex<_Tp> std::log(const std::complex<_Tp>&)’
817 | log(const complex<_Tp>& __z) { return __complex_log(__z.__rep()); }
| ^~~
/usr/include/c++/9/complex:817:5: note: template argument deduction/substitution failed:
In file included from /usr/local/include/Eigen/Core:372,
from /usr/local/include/Eigen/Dense:1,
from test_randeigen.cpp:4:
/usr/local/include/Eigen/src/Core/GenericPacketMath.h:406:58: note: mismatched types ‘const std::complex<_Tp>’ and ‘const __vector(2) double’
406 | Packet plog(const Packet& a) { using std::log; return log(a); }
| ~~~^~~
In file included from /usr/include/c++/9/complex:44,
from /usr/local/include/Eigen/Core:96,
from /usr/local/include/Eigen/Dense:1,
from test_randeigen.cpp:4:
/usr/include/c++/9/cmath:350:5: note: candidate: ‘template<class _Tp> constexpr typename __gnu_cxx::__enable_if<std::__is_integer<_Tp>::__value, double>::__type std::log(_Tp)’
350 | log(_Tp __x)
| ^~~
/usr/include/c++/9/cmath:350:5: note: template argument deduction/substitution failed:
/usr/include/c++/9/cmath: In substitution of ‘template<class _Tp> constexpr typename __gnu_cxx::__enable_if<std::__is_integer<_Tp>::__value, double>::__type std::log(_Tp) [with _Tp = __vector(2) double]’:
/usr/local/include/Eigen/src/Core/GenericPacketMath.h:406:58: required from ‘Packet Eigen::internal::plog(const Packet&) [with Packet = __vector(2) double]’
/usr/local/include/EigenRand/Dists/NormalExp.h:74:53: required from ‘const Packet Eigen::Rand::StdNormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/Dists/NormalExp.h:124:21: required from ‘const Packet Eigen::Rand::NormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/RandUtils.h:417:45: required from ‘const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, _mutable>::packetOp() const [with Packet = __vector(2) double; Gen = Eigen::Rand::NormalGen<double>&; _Scalar = double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; bool _mutable = false]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:360:180: required from ‘T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(2) double; IndexType = long int; Scalar = double; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:505:68: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:879:31: required from ‘static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, -1, -1>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:836:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, -1, -1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Func = Eigen::internal::assign_op<double, double>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:732:41: required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:537:7: required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/Array.h:242:29: required from ‘Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Array(const Eigen::EigenBase<OtherDerived>&, typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1; typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type = Eigen::Array<double, -1, -1>::PrivateType]’
test_randeigen.cpp:19:59: required from here
/usr/include/c++/9/cmath:350:5: error: no type named ‘__type’ in ‘struct __gnu_cxx::__enable_if<false, double>’
/usr/local/include/Eigen/src/Core/GenericPacketMath.h: In instantiation of ‘Packet Eigen::internal::plog(const Packet&) [with Packet = __vector(2) double]’:
/usr/local/include/EigenRand/Dists/NormalExp.h:74:53: required from ‘const Packet Eigen::Rand::StdNormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/Dists/NormalExp.h:124:21: required from ‘const Packet Eigen::Rand::NormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/RandUtils.h:417:45: required from ‘const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, _mutable>::packetOp() const [with Packet = __vector(2) double; Gen = Eigen::Rand::NormalGen<double>&; _Scalar = double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; bool _mutable = false]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:360:180: required from ‘T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(2) double; IndexType = long int; Scalar = double; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:505:68: required from ‘PacketType Eigen::internal::evaluator<Eigen::CwiseNullaryOp<NullaryOp, PlainObjectType> >::packet(IndexType) const [with int LoadMode = 16; PacketType = __vector(2) double; IndexType = long int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>; PlainObjectType = const Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:658:5: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:879:31: required from ‘static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, -1, -1>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:836:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, -1, -1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Func = Eigen::internal::assign_op<double, double>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:732:41: required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:537:7: required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/Array.h:242:29: required from ‘Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Array(const Eigen::EigenBase<OtherDerived>&, typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1; typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type = Eigen::Array<double, -1, -1>::PrivateType]’
test_randeigen.cpp:19:59: required from here
/usr/include/c++/9/cmath:342:3: note: candidate: ‘constexpr long double std::log(long double)’
342 | log(long double __x)
| ^~~
/usr/include/c++/9/cmath:342:19: note: no known conversion for argument 1 from ‘const __vector(2) double’ to ‘long double’
342 | log(long double __x)
| ~~~~~~~~~~~~^~~
/usr/include/c++/9/cmath:338:3: note: candidate: ‘constexpr float std::log(float)’
338 | log(float __x)
| ^~~
/usr/include/c++/9/cmath:338:13: note: no known conversion for argument 1 from ‘const __vector(2) double’ to ‘float’
338 | log(float __x)
| ~~~~~~^~~
In file included from /usr/include/features.h:461,
from /usr/include/x86_64-linux-gnu/c++/9/bits/os_defines.h:39,
from /usr/include/x86_64-linux-gnu/c++/9/bits/c++config.h:524,
from /usr/include/c++/9/iostream:38,
from test_randeigen.cpp:1:
/usr/include/x86_64-linux-gnu/bits/mathcalls.h:104:1: note: candidate: ‘double log(double)’
104 | __MATHCALL_VEC (log,, (_Mdouble_ __x));
| ^~~~~~~~~~~~~~
In file included from /usr/include/c++/9/cmath:45,
from /usr/include/c++/9/complex:44,
from /usr/local/include/Eigen/Core:96,
from /usr/local/include/Eigen/Dense:1,
from test_randeigen.cpp:4:
/usr/include/x86_64-linux-gnu/bits/mathcalls.h:104:1: note: no known conversion for argument 1 from ‘const __vector(2) double’ to ‘double’
104 | __MATHCALL_VEC (log,, (_Mdouble_ __x));
| ^
In file included from /usr/local/include/EigenRand/RandUtils.h:15,
from /usr/local/include/EigenRand/Core.h:16,
from /usr/local/include/EigenRand/EigenRand:17,
from test_randeigen.cpp:5:
/usr/local/include/EigenRand/MorePacketMath.h: In instantiation of ‘void Eigen::internal::psincos(Packet, Packet&, Packet&) [with Packet = __vector(2) double]’:
/usr/local/include/EigenRand/Dists/NormalExp.h:78:12: required from ‘const Packet Eigen::Rand::StdNormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/Dists/NormalExp.h:124:21: required from ‘const Packet Eigen::Rand::NormalGen<_Scalar>::packetOp(Rng&&) [with Packet = __vector(2) double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; _Scalar = double]’
/usr/local/include/EigenRand/RandUtils.h:417:45: required from ‘const Packet Eigen::internal::scalar_rng_adaptor<Gen, _Scalar, Rng, _mutable>::packetOp() const [with Packet = __vector(2) double; Gen = Eigen::Rand::NormalGen<double>&; _Scalar = double; Rng = Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&; bool _mutable = false]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:360:180: required from ‘T Eigen::internal::nullary_wrapper<Scalar, NullaryOp, true, false, false>::packetOp(const NullaryOp&, IndexType, IndexType) const [with T = __vector(2) double; IndexType = long int; Scalar = double; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>]’
/usr/local/include/Eigen/src/Core/CoreEvaluators.h:505:68: required from ‘PacketType Eigen::internal::evaluator<Eigen::CwiseNullaryOp<NullaryOp, PlainObjectType> >::packet(IndexType) const [with int LoadMode = 16; PacketType = __vector(2) double; IndexType = long int; NullaryOp = Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>; PlainObjectType = const Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:658:5: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ]
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:879:31: required from ‘static void Eigen::internal::Assignment<DstXprType, SrcXprType, Functor, Eigen::internal::Dense2Dense, Weak>::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array<double, -1, -1>; SrcXprType = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Functor = Eigen::internal::assign_op<double, double>; Weak = void]’
/usr/local/include/Eigen/src/Core/AssignEvaluator.h:836:49: required from ‘void Eigen::internal::call_assignment_no_alias(Dst&, const Src&, const Func&) [with Dst = Eigen::Array<double, -1, -1>; Src = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Func = Eigen::internal::assign_op<double, double>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:732:41: required from ‘Derived& Eigen::PlainObjectBase<Derived>::_set_noalias(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/PlainObjectBase.h:537:7: required from ‘Eigen::PlainObjectBase<Derived>::PlainObjectBase(const Eigen::DenseBase<OtherDerived>&) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; Derived = Eigen::Array<double, -1, -1>]’
/usr/local/include/Eigen/src/Core/Array.h:242:29: required from ‘Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Array(const Eigen::EigenBase<OtherDerived>&, typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type) [with OtherDerived = Eigen::CwiseNullaryOp<Eigen::internal::scalar_rng_adaptor<Eigen::Rand::NormalGen<double>&, double, Eigen::Rand::MersenneTwister<__vector(2) long long int, 312, 156, 31, 13043109905998158313, 29, 6148914691236517205, 17, 8202884508482404352, 37, 18444473444759240704, 43, 6364136223846793005>&, false>, const Eigen::Array<double, -1, -1> >; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1; typename Eigen::internal::enable_if<Eigen::internal::is_convertible<typename OtherDerived::Scalar, typename Eigen::internal::traits<Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >::Scalar>::value, Eigen::Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::PrivateType>::type = Eigen::Array<double, -1, -1>::PrivateType]’
test_randeigen.cpp:19:59: required from here
/usr/local/include/EigenRand/MorePacketMath.h:91:39: error: cannot convert ‘__vector(4) float’ to ‘__vector(2) double’ in assignment
91 | sign_bit_sin = reinterpret_to_float(
| ~~~~~~~~~~~~~~~~~~~~^
| |
| __vector(4) float
92 | pand(reinterpret_to_int(sign_bit_sin), pset1<IntPacket>(0x80000000))
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
93 | );
| ~
/usr/local/include/EigenRand/MorePacketMath.h:111:51: error: cannot convert ‘__vector(4) float’ to ‘__vector(2) double’ in initialization
111 | Packet swap_sign_bit_sin = reinterpret_to_float(emm0);
| ~~~~~~~~~~~~~~~~~~~~^~~~~~
| |
| __vector(4) float
/usr/local/include/EigenRand/MorePacketMath.h:117:43: error: cannot convert ‘__vector(4) float’ to ‘__vector(2) double’ in initialization
117 | Packet poly_mask = reinterpret_to_float(emm2);
| ~~~~~~~~~~~~~~~~~~~~^~~~~~
| |
| __vector(4) float
/usr/local/include/EigenRand/MorePacketMath.h:134:46: error: cannot convert ‘__vector(4) float’ to ‘__vector(2) double’ in initialization
134 | Packet sign_bit_cos = reinterpret_to_float(emm4);
| ~~~~~~~~~~~~~~~~~~~~^~~~~~
| |
| __vector(4) float
Here the snippet of code:
#include <iostream>
#include <string>
#include <fstream>
#include <Eigen/Dense>
#include <EigenRand/EigenRand>
using namespace Eigen;
int main()
{
std::ofstream outputFile;
outputFile.open("distribution.csv");
int n = 100000;
// Initialize random number generator with seed=42 for following codes.
// Or you can use C++11 RNG such as std::mt19937 or std::ranlux48.
Rand::Vmt19937_64 urng{ 1234 };
Rand::NormalGen<double> normal_dist{1.0,0.5};
ArrayXXd arr = normal_dist.generate<ArrayXXd>(n,1,urng);
std::cout << arr << std::endl;
for(int i;i<n;i++)
{
outputFile << i << "," << arr(i,0) <<std::endl;
}
outputFile.close();
return 0;
}
It compiles normally if everything is typed as float
thank you
About the compilation warnings
Thanks for your efforts again! I get compilation warnings every time I build the packages, it there any plan to fix them? Or is it safe to ignore them?
In file included from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:15,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/Core.h:16,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/EigenRand:17,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/include/semantic_bki/bkioctomap.h:9,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/src/semantickitti_node.cpp:5:
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:52:30: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
52 | struct IsIntPacket<Packet4i> : std::true_type {};
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:55:32: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__vector(4) float’} [-Wignored-attributes]
55 | struct IsFloatPacket<Packet4f> : std::true_type {};
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:58:33: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__vector(2) double’} [-Wignored-attributes]
58 | struct IsDoublePacket<Packet2d> : std::true_type {};
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:61:29: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
61 | struct HalfPacket<Packet4i>
| ^
In file included from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:15,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/Core.h:16,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/EigenRand:17,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/include/semantic_bki/bkioctomap.h:9,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/src/semantickitti_node.cpp:5:
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:1129:32: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
1129 | struct reinterpreter<Packet4i>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:1148:32: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__vector(4) float’} [-Wignored-attributes]
1148 | struct reinterpreter<Packet4f>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/MorePacketMath.h:1167:32: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__vector(2) double’} [-Wignored-attributes]
1167 | struct reinterpreter<Packet2d>
| ^
In file included from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:16,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/Core.h:16,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/EigenRand:17,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/include/semantic_bki/bkioctomap.h:9,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/src/semantickitti_node.cpp:5:
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/PacketFilter.h:178:37: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__vector(4) float’} [-Wignored-attributes]
178 | std::array<internal::Packet4f, 4> selector;
| ^
In file included from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:17,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/Core.h:16,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/EigenRand:17,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/include/semantic_bki/bkioctomap.h:9,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/src/semantickitti_node.cpp:5:
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/PacketRandomEngine.h:573:53: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
573 | using Vmt19937_64 = Pmt19937_64<internal::Packet4i>;
| ^
In file included from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/Core.h:16,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/EigenRand:17,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/include/semantic_bki/bkioctomap.h:9,
from /home/jacobz/Mapping/ws/src/BKISemanticMapping/src/semantickitti_node.cpp:5:
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:279:79: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
279 | struct RawbitsMaker<Packet4i, Rng, RngResult, Rand::RandomEngineType::scalar>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:328:78: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
328 | struct RawbitsMaker<Packet4i, Rng, Packet4i, Rand::RandomEngineType::packet>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:328:78: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:347:40: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4f’ {aka ‘__vector(4) float’} [-Wignored-attributes]
347 | struct UniformRealUtils<Packet4f, Rng> : public RawbitsMaker<Packet4i, Rng>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:347:77: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
347 | struct UniformRealUtils<Packet4f, Rng> : public RawbitsMaker<Packet4i, Rng>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:362:40: warning: ignoring attributes on template argument ‘Eigen::internal::Packet2d’ {aka ‘__vector(2) double’} [-Wignored-attributes]
362 | struct UniformRealUtils<Packet2d, Rng> : public RawbitsMaker<Packet4i, Rng>
| ^
/home/jacobz/Mapping/ws/src/BKISemanticMapping/thirdparty/EigenRand/EigenRand/RandUtils.h:362:77: warning: ignoring attributes on template argument ‘Eigen::internal::Packet4i’ {aka ‘__vector(2) long long int’} [-Wignored-attributes]
362 | struct UniformRealUtils<Packet2d, Rng> : public RawbitsMaker<Packet4i, Rng>
| ^
modernize cmake
The cmake configuration can be improved in various ways:
- add install statements
- simplify executable generation and maintenance
- add packaging configuration
- remove include_directory and replace with target_link_libraries that allows to pass the necessary flags automatically
see eg here https://cliutils.gitlab.io/modern-cmake/
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