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Copy file name to clipboardExpand all lines: .coderabbit.yaml
+10-34Lines changed: 10 additions & 34 deletions
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@@ -10,7 +10,7 @@ reviews:
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request_changes_workflow: false
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review_status: false
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auto_review:
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enabled: true
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enabled: false
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drafts: false
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base_branches:
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- "^main$"
@@ -23,45 +23,21 @@ reviews:
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enabled: true
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path_instructions:
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- path: "src/rapids_singlecell/_cuda/**"
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instructions: |
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These are nanobind CUDA C++ kernels. Pay close attention to:
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- Shared memory usage and device limits
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- Thread/block configuration
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- Memory access patterns and coalescing
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- Correct use of atomicAdd and synchronization
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- Template parameter correctness (float vs double)
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- MANDATORY: Every kernel launch (<<<grid, block, shared, stream>>>) MUST be followed by cudaGetLastError() to catch launch failures. Flag any kernel launch missing this check.
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- MANDATORY: No magic numbers. All block sizes, tile sizes, grid calculations, and thresholds must use named constants (constexpr int BLOCK_SIZE = 256). Flag any raw numeric literal in dim3, grid, or shared memory calculations.
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- path: "src/rapids_singlecell/**/_kernels/**"
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instructions: |
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These are CuPy RawKernel definitions. Review for:
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- Correct CUDA kernel launch configurations
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- Shared memory bounds
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- Type safety (float32 vs float64 mismatches)
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- No magic numbers in kernel launch configurations or kernel code. Block sizes, tile sizes, and thresholds must use named constants.
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- After RawKernel calls, check for cp.cuda.runtime.getLastError() to catch silent launch failures.
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instructions: "Nanobind CUDA C++ kernels. See knowledge base for detailed review guidelines."
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- path: "src/rapids_singlecell/**"
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instructions: "GPU-accelerated Python. See knowledge base for detailed review guidelines."
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- path: "tests/**"
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instructions: |
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Do not suggest changing test tolerances without strong justification.
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Tests run on GPU; some numerical differences vs CPU are expected.
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instructions: "GPU tests — do not suggest tolerance changes without strong justification."
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- path: "docs/**"
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instructions: |
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For documentation changes, focus on:
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- Accuracy of code examples
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- Completeness of API documentation
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- Consistency with current code
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instructions: "Check accuracy of code examples and consistency with current code."
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- path: ".github/**"
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instructions: |
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For CI/workflow changes:
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- Check for proper error handling
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- Verify GPU availability checks before tests
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- Watch for semicolon issues in CMAKE_CUDA_ARCHITECTURES
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instructions: "CI workflows — watch for semicolon issues in CMAKE_CUDA_ARCHITECTURES."
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