mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-07-29 20:14:01 +00:00
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>
This commit is contained in:
Changming Sun
GitHub
parent
44054e7508
commit
17eaf9b053
4 changed files with 49 additions and 29 deletions
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@ -47,7 +47,6 @@ struct ComputeCtx {
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float alpha;
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};
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#if !defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
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template <typename T>
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inline void SparseDenseMatMulImpl(const ComputeCtx& ctx, const ConstSparseMatrixMap<T>& map_A,
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const ConstEigenMatrixMapRowMajor<T>& map_B, EigenMatrixMapRowMajor<T>& output_map) {
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@ -64,7 +63,8 @@ inline void SparseDenseMatMulImpl(const ComputeCtx& ctx, const ConstSparseMatrix
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template <>
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inline void SparseDenseMatMulImpl<float>(const ComputeCtx& ctx, const ConstSparseMatrixMap<float>& map_A,
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const ConstEigenMatrixMapRowMajor<float>& map_B, EigenMatrixMapRowMajor<float>& output_map) {
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const ConstEigenMatrixMapRowMajor<float>& map_B,
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EigenMatrixMapRowMajor<float>& output_map) {
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if (ctx.trans_A && ctx.trans_B) {
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output_map = map_A.transpose() * ctx.alpha * map_B.transpose();
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} else if (ctx.trans_A && !ctx.trans_B) {
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@ -84,21 +84,47 @@ struct SparseToDenseCsr {
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const auto& b_dims = B.Shape().GetDims();
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const auto& out_dims = output.Shape().GetDims();
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auto csr_view = A.AsCsr();
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const Eigen::Index* inner_index_pointer = nullptr;
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const Eigen::Index* outer_index_pointer = nullptr;
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// For auto-release the above two pointers when they are not NULL.
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std::unique_ptr<Eigen::Index[]> buffer_holder_inner, buffer_holder_outer;
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if constexpr (std::is_integral<Eigen::Index>::value &&
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std::is_signed<Eigen::Index>::value &&
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(sizeof(Eigen::Index) == sizeof(int64_t))) {
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// On macOS the following reinterpret_cast is necessary because Eigen::Index is an alias of `long` but int64_t is
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// `long long`. Though they have the same size, compilers still do not allow an implicit casting between them.
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inner_index_pointer = reinterpret_cast<const Eigen::Index*>(csr_view.Inner().Data<int64_t>());
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outer_index_pointer = reinterpret_cast<const Eigen::Index*>(csr_view.Outer().Data<int64_t>());
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} else {
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// In a 32-bit build we need to cast the following two tensors to 32 bits
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gsl::span<const int64_t> inner_data = csr_view.Inner().DataAsSpan<int64_t>();
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gsl::span<const int64_t> outer_data = csr_view.Outer().DataAsSpan<int64_t>();
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buffer_holder_inner.reset(new Eigen::Index[inner_data.size()]);
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buffer_holder_outer.reset(new Eigen::Index[outer_data.size()]);
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inner_index_pointer = buffer_holder_inner.get();
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outer_index_pointer = buffer_holder_outer.get();
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ConstSparseMatrixMap<T> map_A(a_dims[0], a_dims[1], A.NumValues(),
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csr_view.Outer().Data<int64_t>(),
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csr_view.Inner().Data<int64_t>(),
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std::transform(inner_data.begin(), inner_data.end(),
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buffer_holder_inner.get(), [](int64_t v) -> Eigen::Index {
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return narrow<Eigen::Index>(v);
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});
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std::transform(outer_data.begin(), outer_data.end(),
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buffer_holder_outer.get(), [](int64_t v) -> Eigen::Index {
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return narrow<Eigen::Index>(v);
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});
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}
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ConstSparseMatrixMap<T> map_A(narrow<Eigen::Index>(a_dims[0]), narrow<Eigen::Index>(a_dims[1]),
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narrow<Eigen::Index>(A.NumValues()), outer_index_pointer, inner_index_pointer,
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A.Values().Data<T>());
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ConstEigenMatrixMapRowMajor<T> map_B(B.Data<T>(), b_dims[0], b_dims[1]);
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EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), out_dims[0], out_dims[1]);
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ConstEigenMatrixMapRowMajor<T> map_B(B.Data<T>(), narrow<Eigen::Index>(b_dims[0]), narrow<Eigen::Index>(b_dims[1]));
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EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), narrow<Eigen::Index>(out_dims[0]),
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narrow<Eigen::Index>(out_dims[1]));
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// XXX: Consider re-writing it as a parallel loop as Eigen requires it to use OpenMP
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// XXX: Consider vectorization
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SparseDenseMatMulImpl(ctx, map_A, map_B, output_map);
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}
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};
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#endif //! defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
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template <typename T>
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inline T Mul(T a_value, float, T b_value) {
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return a_value * b_value;
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@ -121,9 +147,11 @@ struct SparseToDenseCoo {
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auto coo_view = A.AsCoo();
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const auto& ind_dims = coo_view.Indices().Shape().GetDims();
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ORT_RETURN_IF_NOT(ind_dims.size() == 2, "COO indices must be 2-D, got: ", ind_dims.size());
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ConstEigenMatrixMapRowMajor<int64_t> a_indicies_map(coo_view.Indices().Data<int64_t>(), narrow<size_t>(ind_dims[0]), narrow<size_t>(ind_dims[1]));
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ConstEigenMatrixMapRowMajor<int64_t> a_indicies_map(coo_view.Indices().Data<int64_t>(), narrow<size_t>(ind_dims[0]),
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narrow<size_t>(ind_dims[1]));
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ConstEigenMatrixMapRowMajor<T> map_b(B.Data<T>(), narrow<size_t>(b_dims[0]), narrow<size_t>(b_dims[1]));
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EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), narrow<size_t>(out_dims[0]), narrow<size_t>(out_dims[1]));
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EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), narrow<size_t>(out_dims[0]),
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narrow<size_t>(out_dims[1]));
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output_map.setZero();
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const auto rhs_right = (ctx.trans_B) ? b_dims[0] : b_dims[1];
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@ -140,7 +168,8 @@ struct SparseToDenseCoo {
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ORT_RETURN_IF_NOT(m < out_left, "COO m index: ", m, " is out of bounds of out_left: ", out_left);
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const T a_value = a_values[i];
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for (int64_t n = 0; n < rhs_right; ++n) {
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const T b_value = (ctx.trans_B) ? map_b(narrow<size_t>(n), narrow<size_t>(k)) : map_b(narrow<size_t>(k), narrow<size_t>(n));
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const T b_value =
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(ctx.trans_B) ? map_b(narrow<size_t>(n), narrow<size_t>(k)) : map_b(narrow<size_t>(k), narrow<size_t>(n));
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output_map(narrow<size_t>(m), narrow<size_t>(n)) += Mul(a_value, ctx.alpha, b_value);
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}
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}
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@ -170,8 +199,9 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
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const auto inner_B = (trans_b_attr_) ? b_dims[1] : b_dims[0];
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const auto outer_B = (trans_b_attr_) ? b_dims[0] : b_dims[1];
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ORT_RETURN_IF_NOT(inner_A == inner_B, "Can not multiply A and B as inner dimension does not match. inner_A: ",
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inner_A, " vs inner_B: ", inner_B);
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ORT_RETURN_IF_NOT(inner_A == inner_B,
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"Can not multiply A and B as inner dimension does not match. inner_A: ", inner_A,
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" vs inner_B: ", inner_B);
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TensorShape output_shape{outer_A, outer_B};
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auto* output = ctx->Output(0, output_shape);
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@ -184,12 +214,10 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
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auto coo_view = A->AsCoo();
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const auto num_dims = coo_view.Indices().Shape().NumDimensions();
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ORT_RETURN_IF_NOT(num_dims == 2, "Expecting COO 2-D indices shape");
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ORT_RETURN_IF_NOT(A->Values().Shape().Size() * 2 == coo_view.Indices().Shape().Size(), "Expecting 2xValues == indices");
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ORT_RETURN_IF_NOT(A->Values().Shape().Size() * 2 == coo_view.Indices().Shape().Size(),
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"Expecting 2xValues == indices");
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auto status = t_disp.InvokeRet<Status, SparseToDenseCoo>(compute_ctx, *A, *B, *output);
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ORT_RETURN_IF_ERROR(status);
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// Eigen has a bug in x86 where it calculates reallocation size as -1
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// and throws bad_alloc
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#if !defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
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} else if (A->Format() == SparseFormat::kCsrc) {
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auto csr_view = A->AsCsr();
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ORT_RETURN_IF_NOT(A->Values().Shape().Size() == csr_view.Inner().Shape().Size(),
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@ -199,11 +227,6 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
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} else {
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return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "Currently support only COO and CSR(x64) formats");
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}
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#else
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} else {
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return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "WASM and 32-bit builds support only COO format");
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}
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#endif //! defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
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return Status::OK();
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}
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@ -211,4 +234,4 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
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} // namespace contrib
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} // namespace onnxruntime
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#endif //! defined(DISABLE_SPARSE_TENSORS)
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#endif //! defined(DISABLE_SPARSE_TENSORS)
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@ -93,7 +93,7 @@ template <typename T>
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using ConstEigenMatrixMap = Eigen::Map<const Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>;
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template <class T>
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using ConstSparseMatrixMap = Eigen::Map<const Eigen::SparseMatrix<T, Eigen::RowMajor, int64_t>>;
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using ConstSparseMatrixMap = Eigen::Map<const Eigen::SparseMatrix<T, Eigen::RowMajor, Eigen::Index>>;
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template <typename T>
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using ConstEigenArrayMap = Eigen::Map<const Eigen::Array<T, Eigen::Dynamic, Eigen::Dynamic>>;
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@ -140,7 +140,6 @@ void resize(Index size, double reserveSizeFactor = 0) {
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}
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*/
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#if !defined(DISABLE_SPARSE_TENSORS)
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#if !defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
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TEST(SparseToDenseMatMul, TestCsr) {
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constexpr int64_t rows = 9;
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constexpr int64_t cols = 9;
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@ -261,7 +260,6 @@ TEST(SparseToDenseMatMul, TestCsr) {
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tester.Run(OpTester::ExpectResult::kExpectSuccess);
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}
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}
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#endif // //!defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
|
||||
|
||||
TEST(SparseToDenseMatMul, TestCoo) {
|
||||
constexpr int64_t rows = 9;
|
||||
|
|
|
|||
|
|
@ -106,8 +106,7 @@ stages:
|
|||
ls $(Build.BinariesDirectory)/gccbin/bin
|
||||
mkdir $(Build.BinariesDirectory)/arm32build
|
||||
cd $(Build.BinariesDirectory)/arm32build
|
||||
# TODO: fix the warnings and remove the --compile-no-warning-as-error arg
|
||||
cmake --compile-no-warning-as-error $(Build.SourcesDirectory)/cmake -Donnxruntime_ENABLE_CPUINFO=OFF -DPython_EXECUTABLE=/usr/bin/python3 -DPYTHON_EXECUTABLE=/usr/bin/python3 -DCMAKE_BUILD_TYPE=Debug -DCMAKE_TOOLCHAIN_FILE=$(Build.SourcesDirectory)/cmake/linux_arm32_crosscompile_toolchain.cmake -G Ninja
|
||||
cmake $(Build.SourcesDirectory)/cmake -Donnxruntime_ENABLE_CPUINFO=OFF -DPython_EXECUTABLE=/usr/bin/python3 -DPYTHON_EXECUTABLE=/usr/bin/python3 -DCMAKE_BUILD_TYPE=Debug -DCMAKE_TOOLCHAIN_FILE=$(Build.SourcesDirectory)/cmake/linux_arm32_crosscompile_toolchain.cmake -G Ninja
|
||||
ninja
|
||||
rm -rf $(Build.BinariesDirectory)/arm32build $(Build.BinariesDirectory)/gccbin
|
||||
displayName: Cross-compile for Linux ARM32 and ARM64
|
||||
|
|
|
|||
Loading…
Reference in a new issue