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Fix a build warning in SparseTensor code for 32-bit build configs (#1…
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…8766)

### 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 <[email protected]>
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@snnn @yuslepukhin
snnn and yuslepukhin authored Dec 13, 2023
1 parent 44054e7 commit 17eaf9b
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73 changes: 48 additions & 25 deletions onnxruntime/contrib_ops/cpu/math/sparse_dense_matmul.cc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,6 @@ struct ComputeCtx {
float alpha;
};

#if !defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
template <typename T>
inline void SparseDenseMatMulImpl(const ComputeCtx& ctx, const ConstSparseMatrixMap<T>& map_A,
const ConstEigenMatrixMapRowMajor<T>& map_B, EigenMatrixMapRowMajor<T>& output_map) {
Expand All @@ -64,7 +63,8 @@ inline void SparseDenseMatMulImpl(const ComputeCtx& ctx, const ConstSparseMatrix

template <>
inline void SparseDenseMatMulImpl<float>(const ComputeCtx& ctx, const ConstSparseMatrixMap<float>& map_A,
const ConstEigenMatrixMapRowMajor<float>& map_B, EigenMatrixMapRowMajor<float>& output_map) {
const ConstEigenMatrixMapRowMajor<float>& map_B,
EigenMatrixMapRowMajor<float>& output_map) {
if (ctx.trans_A && ctx.trans_B) {
output_map = map_A.transpose() * ctx.alpha * map_B.transpose();
} else if (ctx.trans_A && !ctx.trans_B) {
Expand All @@ -84,21 +84,47 @@ struct SparseToDenseCsr {
const auto& b_dims = B.Shape().GetDims();
const auto& out_dims = output.Shape().GetDims();
auto csr_view = A.AsCsr();

ConstSparseMatrixMap<T> map_A(a_dims[0], a_dims[1], A.NumValues(),
csr_view.Outer().Data<int64_t>(),
csr_view.Inner().Data<int64_t>(),
const Eigen::Index* inner_index_pointer = nullptr;
const Eigen::Index* outer_index_pointer = nullptr;
// For auto-release the above two pointers when they are not NULL.
std::unique_ptr<Eigen::Index[]> buffer_holder_inner, buffer_holder_outer;
if constexpr (std::is_integral<Eigen::Index>::value &&
std::is_signed<Eigen::Index>::value &&
(sizeof(Eigen::Index) == sizeof(int64_t))) {
// On macOS the following reinterpret_cast is necessary because Eigen::Index is an alias of `long` but int64_t is
// `long long`. Though they have the same size, compilers still do not allow an implicit casting between them.
inner_index_pointer = reinterpret_cast<const Eigen::Index*>(csr_view.Inner().Data<int64_t>());
outer_index_pointer = reinterpret_cast<const Eigen::Index*>(csr_view.Outer().Data<int64_t>());
} else {
// In a 32-bit build we need to cast the following two tensors to 32 bits
gsl::span<const int64_t> inner_data = csr_view.Inner().DataAsSpan<int64_t>();
gsl::span<const int64_t> outer_data = csr_view.Outer().DataAsSpan<int64_t>();
buffer_holder_inner.reset(new Eigen::Index[inner_data.size()]);
buffer_holder_outer.reset(new Eigen::Index[outer_data.size()]);
inner_index_pointer = buffer_holder_inner.get();
outer_index_pointer = buffer_holder_outer.get();

std::transform(inner_data.begin(), inner_data.end(),
buffer_holder_inner.get(), [](int64_t v) -> Eigen::Index {
return narrow<Eigen::Index>(v);
});
std::transform(outer_data.begin(), outer_data.end(),
buffer_holder_outer.get(), [](int64_t v) -> Eigen::Index {
return narrow<Eigen::Index>(v);
});
}
ConstSparseMatrixMap<T> map_A(narrow<Eigen::Index>(a_dims[0]), narrow<Eigen::Index>(a_dims[1]),
narrow<Eigen::Index>(A.NumValues()), outer_index_pointer, inner_index_pointer,
A.Values().Data<T>());
ConstEigenMatrixMapRowMajor<T> map_B(B.Data<T>(), b_dims[0], b_dims[1]);
EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), out_dims[0], out_dims[1]);
ConstEigenMatrixMapRowMajor<T> map_B(B.Data<T>(), narrow<Eigen::Index>(b_dims[0]), narrow<Eigen::Index>(b_dims[1]));
EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), narrow<Eigen::Index>(out_dims[0]),
narrow<Eigen::Index>(out_dims[1]));
// XXX: Consider re-writing it as a parallel loop as Eigen requires it to use OpenMP
// XXX: Consider vectorization
SparseDenseMatMulImpl(ctx, map_A, map_B, output_map);
}
};

#endif //! defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)

template <typename T>
inline T Mul(T a_value, float, T b_value) {
return a_value * b_value;
Expand All @@ -121,9 +147,11 @@ struct SparseToDenseCoo {
auto coo_view = A.AsCoo();
const auto& ind_dims = coo_view.Indices().Shape().GetDims();
ORT_RETURN_IF_NOT(ind_dims.size() == 2, "COO indices must be 2-D, got: ", ind_dims.size());
ConstEigenMatrixMapRowMajor<int64_t> a_indicies_map(coo_view.Indices().Data<int64_t>(), narrow<size_t>(ind_dims[0]), narrow<size_t>(ind_dims[1]));
ConstEigenMatrixMapRowMajor<int64_t> a_indicies_map(coo_view.Indices().Data<int64_t>(), narrow<size_t>(ind_dims[0]),
narrow<size_t>(ind_dims[1]));
ConstEigenMatrixMapRowMajor<T> map_b(B.Data<T>(), narrow<size_t>(b_dims[0]), narrow<size_t>(b_dims[1]));
EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), narrow<size_t>(out_dims[0]), narrow<size_t>(out_dims[1]));
EigenMatrixMapRowMajor<T> output_map(output.MutableData<T>(), narrow<size_t>(out_dims[0]),
narrow<size_t>(out_dims[1]));
output_map.setZero();

const auto rhs_right = (ctx.trans_B) ? b_dims[0] : b_dims[1];
Expand All @@ -140,7 +168,8 @@ struct SparseToDenseCoo {
ORT_RETURN_IF_NOT(m < out_left, "COO m index: ", m, " is out of bounds of out_left: ", out_left);
const T a_value = a_values[i];
for (int64_t n = 0; n < rhs_right; ++n) {
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));
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));
output_map(narrow<size_t>(m), narrow<size_t>(n)) += Mul(a_value, ctx.alpha, b_value);
}
}
Expand Down Expand Up @@ -170,8 +199,9 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
const auto inner_B = (trans_b_attr_) ? b_dims[1] : b_dims[0];
const auto outer_B = (trans_b_attr_) ? b_dims[0] : b_dims[1];

ORT_RETURN_IF_NOT(inner_A == inner_B, "Can not multiply A and B as inner dimension does not match. inner_A: ",
inner_A, " vs inner_B: ", inner_B);
ORT_RETURN_IF_NOT(inner_A == inner_B,
"Can not multiply A and B as inner dimension does not match. inner_A: ", inner_A,
" vs inner_B: ", inner_B);

TensorShape output_shape{outer_A, outer_B};
auto* output = ctx->Output(0, output_shape);
Expand All @@ -184,12 +214,10 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
auto coo_view = A->AsCoo();
const auto num_dims = coo_view.Indices().Shape().NumDimensions();
ORT_RETURN_IF_NOT(num_dims == 2, "Expecting COO 2-D indices shape");
ORT_RETURN_IF_NOT(A->Values().Shape().Size() * 2 == coo_view.Indices().Shape().Size(), "Expecting 2xValues == indices");
ORT_RETURN_IF_NOT(A->Values().Shape().Size() * 2 == coo_view.Indices().Shape().Size(),
"Expecting 2xValues == indices");
auto status = t_disp.InvokeRet<Status, SparseToDenseCoo>(compute_ctx, *A, *B, *output);
ORT_RETURN_IF_ERROR(status);
// Eigen has a bug in x86 where it calculates reallocation size as -1
// and throws bad_alloc
#if !defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
} else if (A->Format() == SparseFormat::kCsrc) {
auto csr_view = A->AsCsr();
ORT_RETURN_IF_NOT(A->Values().Shape().Size() == csr_view.Inner().Shape().Size(),
Expand All @@ -199,16 +227,11 @@ Status SparseToDenseMatMul::Compute(OpKernelContext* ctx) const {
} else {
return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "Currently support only COO and CSR(x64) formats");
}
#else
} else {
return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "WASM and 32-bit builds support only COO format");
}
#endif //! defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)

return Status::OK();
}

} // namespace contrib
} // namespace onnxruntime

#endif //! defined(DISABLE_SPARSE_TENSORS)
#endif //! defined(DISABLE_SPARSE_TENSORS)
2 changes: 1 addition & 1 deletion onnxruntime/core/util/math_cpuonly.h
View file
Original file line number Diff line number Diff line change
Expand Up @@ -93,7 +93,7 @@ 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, int64_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>>;
Expand Down
2 changes: 0 additions & 2 deletions onnxruntime/test/contrib_ops/math/matmul_sparse_test.cc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -140,7 +140,6 @@ void resize(Index size, double reserveSizeFactor = 0) {
}
*/
#if !defined(DISABLE_SPARSE_TENSORS)
#if !defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)
TEST(SparseToDenseMatMul, TestCsr) {
constexpr int64_t rows = 9;
constexpr int64_t cols = 9;
Expand Down Expand Up @@ -261,7 +260,6 @@ TEST(SparseToDenseMatMul, TestCsr) {
tester.Run(OpTester::ExpectResult::kExpectSuccess);
}
}
#endif // //!defined(__i386__) && !defined(_M_IX86) && !defined(__wasm__) && !defined(__ANDROID__)

TEST(SparseToDenseMatMul, TestCoo) {
constexpr int64_t rows = 9;
Expand Down
3 changes: 1 addition & 2 deletions tools/ci_build/github/azure-pipelines/linux-ci-pipeline.yml
View file
Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down

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