Fill CUDA opset gap for ReduceMax and ReduceMin (18 → 20)#27755
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Fill CUDA opset gap for ReduceMax and ReduceMin (18 → 20)#27755
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… 18 to opset 20 Co-authored-by: tianleiwu <30328909+tianleiwu@users.noreply.github.com>
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March 19, 2026 00:05
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| #define REGISTER_KERNEL_VERSIONED_RANGE_AXES_INPUT_TYPED(name, T, begin, end) \ | ||
| ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_EX( \ | ||
| name, \ | ||
| kOnnxDomain, \ | ||
| begin, end, \ | ||
| T, \ | ||
| kCudaExecutionProvider, \ | ||
| (*KernelDefBuilder::Create()).TypeConstraint("T", DataTypeImpl::GetTensorType<T>()).InputMemoryType(OrtMemTypeCPUInput, 1), \ |
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| #define REGISTER_KERNEL_VERSIONED_RANGE_AXES_INPUT_TYPED(name, T, begin, end) \ | |
| ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_EX( \ | |
| name, \ | |
| kOnnxDomain, \ | |
| begin, end, \ | |
| T, \ | |
| kCudaExecutionProvider, \ | |
| (*KernelDefBuilder::Create()).TypeConstraint("T", DataTypeImpl::GetTensorType<T>()).InputMemoryType(OrtMemTypeCPUInput, 1), \ | |
| #define REGISTER_KERNEL_VERSIONED_RANGE_AXES_INPUT_TYPED(name, T, begin, end) \ | |
| ONNX_OPERATOR_VERSIONED_TYPED_KERNEL_EX( \ | |
| name, \ | |
| kOnnxDomain, \ | |
| begin, end, \ | |
| T, \ | |
| kCudaExecutionProvider, \ | |
| (*KernelDefBuilder::Create()).TypeConstraint("T", DataTypeImpl::GetTensorType<T>()).InputMemoryType(OrtMemTypeCPUInput, 1), \ |
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Description
Extends CUDA ReduceMax and ReduceMin kernel registrations from opset 18 to opset 20.
reduction_ops.cc: AddedREGISTER_KERNEL_VERSIONED_RANGE_AXES_INPUT_TYPEDmacro for versioned ranges requiringInputMemoryType(OrtMemTypeCPUInput, 1). Split both operators from 2-way (1–17, 18+) to 3-way (1–17, 18–19, 20+).cuda_execution_provider.cc: Capped opset 18 forward declarations andBuildKernelCreateInfoentries to versioned 18–19. Added opset 20 non-versioned entries for both operators.Type coverage maintained as-is: ReduceMax (float, double, MLFloat16, int32_t, int64_t), ReduceMin adds int8_t, uint8_t.
Motivation and Context
ReduceMax and ReduceMin CUDA registrations stopped at opset 18; ONNX latest is opset 20. Models exported with opset 19–20 could fail to find a matching CUDA kernel for these ops.
Follows the same pattern used in #27735 (TopK) and other opset gap PRs tracked in #27729.