Add INT8, INT16, and UINT8 type support for CUDA TopK operator

[elwhyjay]

Add type constraints and dispatch cases for int8_t, int16_t, and uint8_t in the CUDA TopK kernel (opset 1-9, 10, 11-23, 24), along with three new .cu template instantiation files. This is the CUDA counterpart to the CPU support added in #27860.

Fixes #27859

Description

Add CUDA kernel type dispatch and template specializations for int8_t, int16_t, and uint8_t types in the CUDA TopK operator

Changed files:

• onnxruntime/core/providers/cuda/math/topk.cc — type constraints + dispatch cases for int8/int16/uint8
• onnxruntime/core/providers/cuda/math/topk_impl_i8.cu — new template instantiation for int8_t
• onnxruntime/core/providers/cuda/math/topk_impl_u8.cu — new template instantiation for uint8_t
• onnxruntime/core/providers/cuda/math/topk_impl_i16.cu — new template instantiation for int16_t

Motivation and Context

This is the CUDA counterpart to #27860 (CPU TopK INT8/INT16/UINT8 support).

The ONNX specification (opset 11+) lists INT8, INT16, and UINT8 as valid input types for the TopK operator. After #27860 added CPU support, the CUDA execution provider still lacked kernels for these types, causing models to fall back to CPU or fail when using CUDAExecutionProvider.

The existing CUDA TopK implementation uses a split-compilation pattern (one .cu file per type) with ToCudaType<T> mapping. Since the default template maps integer types to themselves and NumericLimits<T> uses std::numeric_limits<T>, no algorithmic changes were needed — only:

1. Adding type constraints to kernel registrations (all opset versions)
2. Adding dispatch cases in ComputeInternal
3. Creating three new .cu files for template instantiation

All 64 TopK tests pass (including 8 tests for the new types, running on both CPU and CUDA providers).

Test Results

[==========] Running 64 tests from 1 test suite.
...
[ RUN      ] TopKOperator.TopK_Int8
[       OK ] TopKOperator.TopK_Int8 (21 ms)
[ RUN      ] TopKOperator.TopK_Int8_Negative
[       OK ] TopKOperator.TopK_Int8_Negative (21 ms)
[ RUN      ] TopKOperator.TopK_Int8_Smallest
[       OK ] TopKOperator.TopK_Int8_Smallest (21 ms)
[ RUN      ] TopKOperator.TopK_Int16
[       OK ] TopKOperator.TopK_Int16 (21 ms)
[ RUN      ] TopKOperator.TopK_Uint8
[       OK ] TopKOperator.TopK_Uint8 (21 ms)
[ RUN      ] TopKOperator.TopK_Int8_ExplicitAxis
[       OK ] TopKOperator.TopK_Int8_ExplicitAxis (21 ms)
[ RUN      ] TopKOperator.TopK_Int8_Opset24
[       OK ] TopKOperator.TopK_Int8_Opset24 (21 ms)
[ RUN      ] TopKOperator.TopK_Uint8_Opset24
[       OK ] TopKOperator.TopK_Uint8_Opset24 (21 ms)
...
[  PASSED  ] 64 tests.

[tianleiwu]

Please also update docs/OperatorKernels.md. You may download the updated file in artifact of Windows GPU Doc Gen CI Pipeline job.

[tianleiwu]

/azp run Windows GPU Doc Gen CI Pipeline

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).

[azure-pipelines]

Commenter does not have sufficient privileges for PR 27862 in repo microsoft/onnxruntime

[elwhyjay]

@tianleiwu Hi, I've addressed the review feedback in the latest commit (restricting int8/int16/uint8 TopK CUDA kernels to opset 11+). Could you please trigger the CI pipeline so I can download the updated OperatorKernels.md from the artifact? Thanks!

[tianleiwu]

/azp run Windows GPU Doc Gen CI Pipeline

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).

[elwhyjay]

@tianleiwu Done — updated docs/OperatorKernels.md with the artifact from the Windows GPU Doc Gen CI Pipeline. Thanks for the review!

[elwhyjay]

@tianleiwu Friendly ping — I've addressed all the feedback and updated OperatorKernels.md. The CPU counterpart (#27860) has already been merged. Is there anything else needed for this to move forward?

[tianleiwu]

/azp run Linux QNN CI Pipeline, Win_TRT_Minimal_CUDA_Test_CI, Windows ARM64 QNN CI Pipeline, Windows GPU Doc Gen CI Pipeline, Web CI Pipeline, ONNX Runtime WebGPU Builds

[azure-pipelines]

Azure Pipelines successfully started running 4 pipeline(s).

[elwhyjay]

@tianleiwu Hi, it looks like the CI failure was due to a self-hosted runner losing connection — not related to code changes. Could you re-trigger the pipeline when you get a chance? Thanks!

[tianleiwu]

Thanks for tightening the opset gating after the earlier review. One remaining blocker is test coverage: this PR enables new CUDA TopK runtime paths, but currently only the compile is covered. Please add CUDA-covered TopK cases for the newly registered int8/int16/uint8 types before merging.

[tianleiwu]

I saw some test cases in #2786.

[elwhyjay]

@tianleiwu Hi! Thanks for the review and approval!