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Switch to a static local variable to avoid global constexpr warning (#14638)

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### Description
Switch to a static local variable to fix the warning

Comments in the code so it's clear that it's intentional.

### Motivation and Context
Prefast warning: [prefast:Warning]: C26426 (in
'onnxruntime::cuda::`dynamic initializer for 'castOpTypeConstraints''')
Global initializer calls a non-constexpr function
'onnxruntime::DataTypeImpl::GetTensorType<onnxruntime::MLFloat16>'
(i.22).
This commit is contained in:
Ryan Hill 2023-02-09 14:25:02 -08:00 committed by GitHub
parent 23f0e44265
commit 02bba3e268
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GPG key ID: 4AEE18F83AFDEB23
1 changed files with 12 additions and 7 deletions
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19
onnxruntime/core/providers/cuda/tensor/cast_op.cc
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@ -9,8 +9,12 @@ using namespace onnxruntime::common;
namespace onnxruntime {
namespace cuda {
const std::vector<MLDataType> castOpTypeConstraints{
DataTypeImpl::GetTensorType<MLFloat16>(),
const std::vector<MLDataType>& CastOpTypeConstraints() {
// Must be done as a local static for a shared provider, to avoid the prefast warning:
// Global initializer calls a non-constexpr function 'onnxruntime::DataTypeImpl::GetTensorType<onnxruntime::MLFloat16>'
// In a shared provider, GetTensorType is a function call into Onnxruntime and isn't constexpr
static std::vector<MLDataType> types{
DataTypeImpl::GetTensorType<MLFloat16>(),
DataTypeImpl::GetTensorType<BFloat16>(),
DataTypeImpl::GetTensorType<float>(),
DataTypeImpl::GetTensorType<double>(),
@ -22,8 +26,9 @@ const std::vector<MLDataType> castOpTypeConstraints{
DataTypeImpl::GetTensorType<uint16_t>(),
DataTypeImpl::GetTensorType<uint32_t>(),
DataTypeImpl::GetTensorType<uint64_t>(),
DataTypeImpl::GetTensorType<bool>()
};
DataTypeImpl::GetTensorType<bool>()};
return types;
}
#define REGISTER_KERNEL_TYPED(T) \
ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_EX( \
@ -34,7 +39,7 @@ const std::vector<MLDataType> castOpTypeConstraints{
kCudaExecutionProvider, \
(*KernelDefBuilder::Create()) \
.TypeConstraint("T1", DataTypeImpl::GetTensorType<T>()) \
.TypeConstraint("T2", castOpTypeConstraints), \
.TypeConstraint("T2", CastOpTypeConstraints()), \
Cast<T>); \
ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_EX( \
Cast, \
@ -44,7 +49,7 @@ const std::vector<MLDataType> castOpTypeConstraints{
kCudaExecutionProvider, \
(*KernelDefBuilder::Create()) \
.TypeConstraint("T1", DataTypeImpl::GetTensorType<T>()) \
.TypeConstraint("T2", castOpTypeConstraints), \
.TypeConstraint("T2", CastOpTypeConstraints()), \
Cast<T>); \
ONNX_OPERATOR_TYPED_KERNEL_EX( \
Cast, \
@ -54,7 +59,7 @@ const std::vector<MLDataType> castOpTypeConstraints{
kCudaExecutionProvider, \
(*KernelDefBuilder::Create()) \
.TypeConstraint("T1", DataTypeImpl::GetTensorType<T>()) \
.TypeConstraint("T2", castOpTypeConstraints), \
.TypeConstraint("T2", CastOpTypeConstraints()), \
Cast<T>);
template <typename SrcT>