onnxruntime/onnxruntime/core/util/math_cpuonly.h
Changming Sun 17eaf9b053
Fix a build warning in SparseTensor code for 32-bit build configs (#18766)
### Description
The warning is:

```

                C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(88,54): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.1812949Z                  with
2023-12-08T20:58:48.2144272Z                  [
2023-12-08T20:58:48.2145285Z                      Derived=Eigen::Map<const Eigen::SparseMatrix<uint64_t,1,int64_t>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.2801935Z                  ]
2023-12-08T20:58:48.2804047Z        C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(82,8): message : while compiling class template member function 'void onnxruntime::contrib::`anonymous-namespace'::SparseToDenseCsr<uint64_t>::operator ()(const onnxruntime::contrib::`anonymous-namespace'::ComputeCtx &,const onnxruntime::SparseTensor &,const onnxruntime::Tensor &,onnxruntime::Tensor &) const' [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.2806197Z        C:\a\_work\1\s\include\onnxruntime\core/framework/data_types_internal.h(302,27): message : see the first reference to 'onnxruntime::contrib::`anonymous-namespace'::SparseToDenseCsr<uint64_t>::operator ()' in 'onnxruntime::utils::mltype_dispatcher_internal::CallableDispatchableHelper::Invoke' (compiling source file C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc) [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.2871783Z        C:\a\_work\1\s\include\onnxruntime\core/framework/data_types_internal.h(438,100): message : see reference to class template instantiation 'onnxruntime::contrib::`anonymous-namespace'::SparseToDenseCsr<uint64_t>' being compiled (compiling source file C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc) [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.2893010Z        C:\a\_work\1\s\include\onnxruntime\core/framework/data_types_internal.h(414,5): message : see reference to function template instantiation 'void onnxruntime::utils::MLTypeCallDispatcher<float,double,int32_t,uint32_t,int64_t,uint64_t>::InvokeWithLeadingTemplateArgs<Fn,onnxruntime::TypeList<>,onnxruntime::contrib::`anonymous-namespace'::ComputeCtx&,const T&,const onnxruntime::Tensor&,onnxruntime::Tensor&>(onnxruntime::contrib::`anonymous-namespace'::ComputeCtx &,const T &,const onnxruntime::Tensor &,onnxruntime::Tensor &) const' being compiled [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.2894476Z                  with
2023-12-08T20:58:48.2911521Z                  [
2023-12-08T20:58:48.2912457Z                      Fn=onnxruntime::contrib::`anonymous-namespace'::SparseToDenseCsr,
2023-12-08T20:58:48.3067840Z                      T=onnxruntime::SparseTensor
2023-12-08T20:58:48.3068863Z                  ] (compiling source file C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc)
2023-12-08T20:58:48.3195854Z        C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(198,11): message : see reference to function template instantiation 'void onnxruntime::utils::MLTypeCallDispatcher<float,double,int32_t,uint32_t,int64_t,uint64_t>::Invoke<onnxruntime::contrib::`anonymous-namespace'::SparseToDenseCsr,onnxruntime::contrib::`anonymous-namespace'::ComputeCtx&,const T&,const onnxruntime::Tensor&,onnxruntime::Tensor&>(onnxruntime::contrib::`anonymous-namespace'::ComputeCtx &,const T &,const onnxruntime::Tensor &,onnxruntime::Tensor &) const' being compiled [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.3197946Z                  with
2023-12-08T20:58:48.3198565Z                  [
2023-12-08T20:58:48.3199093Z                      T=onnxruntime::SparseTensor
2023-12-08T20:58:48.3905678Z                  ]
2023-12-08T20:58:48.3907275Z        C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(198,36): message : see the first reference to 'onnxruntime::utils::MLTypeCallDispatcher<float,double,int32_t,uint32_t,int64_t,uint64_t>::Invoke' in 'onnxruntime::contrib::SparseToDenseMatMul::Compute' [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.3910999Z ##[warning]onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(88,43): Warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data
2023-12-08T20:58:48.3912734Z    182>C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(88,43): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.3913414Z                  with
2023-12-08T20:58:48.3913660Z                  [
2023-12-08T20:58:48.3914001Z                      Derived=Eigen::Map<const Eigen::SparseMatrix<uint64_t,1,int64_t>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.3914499Z                  ]
2023-12-08T20:58:48.3914743Z          qlinear_concat.cc
2023-12-08T20:58:48.3917082Z ##[warning]onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(92,74): Warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data
2023-12-08T20:58:48.3918624Z    182>C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(92,74): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.5534583Z                  with
2023-12-08T20:58:48.5541266Z                  [
2023-12-08T20:58:48.5542401Z                      Derived=Eigen::Map<const Eigen::Matrix<uint64_t,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.5544914Z                  ]
2023-12-08T20:58:48.5548670Z ##[warning]onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(92,63): Warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data
2023-12-08T20:58:48.5552099Z    182>C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(92,63): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.5553712Z                  with
2023-12-08T20:58:48.5555569Z                  [
2023-12-08T20:58:48.5556779Z                      Derived=Eigen::Map<const Eigen::Matrix<uint64_t,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.5558707Z                  ]
2023-12-08T20:58:48.5561428Z ##[warning]onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(93,90): Warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data
2023-12-08T20:58:48.5565624Z    182>C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(93,90): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.5566354Z                  with
2023-12-08T20:58:48.5568185Z                  [
2023-12-08T20:58:48.5569305Z                      Derived=Eigen::Map<Eigen::Matrix<uint64_t,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.5571339Z                  ]
2023-12-08T20:58:48.5574864Z ##[warning]onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(93,77): Warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data
2023-12-08T20:58:48.5577866Z    182>C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(93,77): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.5578562Z                  with
2023-12-08T20:58:48.5580399Z                  [
2023-12-08T20:58:48.5581503Z                      Derived=Eigen::Map<Eigen::Matrix<uint64_t,-1,-1,1,-1,-1>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.5583465Z                  ]
2023-12-08T20:58:48.5587661Z ##[warning]onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(88,54): Warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data
2023-12-08T20:58:48.5590705Z    182>C:\a\_work\1\s\onnxruntime\contrib_ops\cpu\math\sparse_dense_matmul.cc(88,54): warning C4244: 'argument': conversion from 'const __int64' to 'Eigen::EigenBase<Derived>::Index', possible loss of data [C:\a\_work\1\b\RelWithDebInfo\onnxruntime_providers.vcxproj]
2023-12-08T20:58:48.5591396Z                  with
2023-12-08T20:58:48.5593220Z                  [
2023-12-08T20:58:48.5593693Z                      Derived=Eigen::Map<const Eigen::SparseMatrix<int64_t,1,int64_t>,0,Eigen::Stride<0,0>>
2023-12-08T20:58:48.5595955Z                  ]

```
And the warning in #18195



### Motivation and Context
AB#22894

---------

Co-authored-by: Dmitri Smirnov <yuslepukhin@users.noreply.github.com>
2023-12-13 11:11:13 -08:00

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/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// Modifications Copyright (c) Microsoft.
#pragma once
#include "onnxruntime_config.h"
// external/eigen/Eigen/src/Core/AssignEvaluator.h:86:63:
// error: enum constant in boolean context [-Werror=int-in-bool-context]
#if defined(__GNUC__)
#pragma GCC diagnostic push
#if __GNUC__ >= 6
#pragma GCC diagnostic ignored "-Wignored-attributes"
#endif
#pragma GCC diagnostic ignored "-Wunused-parameter"
#pragma GCC diagnostic ignored "-Wunused-result"
#if __GNUC__ >= 7
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wint-in-bool-context"
#ifdef HAS_DEPRECATED_COPY
#pragma GCC diagnostic ignored "-Wdeprecated-copy"
#endif
#endif
// cmake/external/eigen/Eigen/src/Core/arch/NEON/PacketMath.h:1633:9:
// error: void* memcpy(void*, const void*, size_t) copying an object of non-trivial type Eigen::internal::Packet4c
// {aka struct Eigen::internal::eigen_packet_wrapper<int, 2>} from an array of const int8_t
// {aka const signed char} [-Werror=class-memaccess]
#ifdef HAS_CLASS_MEMACCESS
#pragma GCC diagnostic ignored "-Wclass-memaccess"
#endif
// cmake/external/eigen\Eigen/src/SparseCore/TriangularSolver.h:273:13:
// error: variable 'count' set but not used [-Werror,-Wunused-but-set-variable]
// Index count = 0;
#ifdef HAS_UNUSED_BUT_SET_VARIABLE
#pragma GCC diagnostic ignored "-Wunused-but-set-variable"
#endif
#ifdef HAS_DEPRECATED_DECLARATIONS
#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
#elif defined(_MSC_VER)
// build\windows\debug\external\eigen3\unsupported\eigen\cxx11\src/Tensor/Tensor.h(76):
// warning C4554: '&': check operator precedence for possible error; use parentheses to clarify precedence
// unsupported\eigen\cxx11\src\Tensor\TensorUInt128.h(150,0): Warning C4245: 'initializing': conversion from '__int64'
// to 'uint64_t', signed/unsigned mismatch
#pragma warning(push)
#pragma warning(disable : 4554)
#pragma warning(disable : 4245)
#pragma warning(disable : 4127)
#endif
#include "Eigen/Core"
#include "Eigen/Dense"
#include "Eigen/Sparse"
#if defined(__GNUC__)
#pragma GCC diagnostic pop
#else
#pragma warning(pop)
#endif
namespace onnxruntime {
// common Eigen types that we will often use
template <typename T>
using EigenMatrixMap = Eigen::Map<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>;
template <typename T>
using EigenArrayMap = Eigen::Map<Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
template <typename T>
using EigenVectorMap = Eigen::Map<Eigen::Matrix<T, Eigen::Dynamic, 1>>;
template <typename T>
using EigenVectorArrayMap = Eigen::Map<Eigen::Array<T, Eigen::Dynamic, 1>>;
template <typename T>
using ConstEigenMatrixMap = Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>;
template <class T>
using ConstSparseMatrixMap = Eigen::Map<const Eigen::SparseMatrix<T, Eigen::RowMajor, Eigen::Index>>;
template <typename T>
using ConstEigenArrayMap = Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
template <typename T>
using ConstEigenVectorMap = Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, 1>>;
template <typename T>
using ConstEigenVectorArrayMap = Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, 1>>;
template <typename T>
using EigenMatrixMapRowMajor = Eigen::Map<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>;
template <typename T>
using ConstEigenMatrixMapRowMajor = Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>>;
template <typename T>
using EigenMatrixMapRowMajorOuterStride =
Eigen::Map<Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>, 0, Eigen::OuterStride<>>;
template <typename T>
using ConstEigenMatrixMapRowMajorOuterStride =
Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>, 0, Eigen::OuterStride<>>;
class CPUMathUtil {
public:
/*CPUMathUtil contains some help method like generate a
random seed. We only need a single instance for it.*/
static CPUMathUtil& Instance() {
static CPUMathUtil p;
return p;
}
// todo: the random generate interface.
private:
CPUMathUtil() = default;
};
// cast TA and TB to TC, and do matrix multiply in Eigen
// note that inputs/outputs is row-major, while Eigen is col-major
// so (M, K) x (K, N) -> (M, N) becomes (N, K) x (K, M) -> (N, M) in Eigen
template <typename TA, typename TB, typename TY>
void EigenCastGEMM(const TA* A_data, const TB* B_data, TY* Y_data, int M, int N, int K) {
auto A = ConstEigenMatrixMap<TA>(A_data, K, M);
auto B = ConstEigenMatrixMap<TB>(B_data, N, K);
EigenMatrixMap<TY>(Y_data, N, M) = B.template cast<TY>() * A.template cast<TY>();
}
} // namespace onnxruntime