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Copy file name to clipboardExpand all lines: .coderabbit.yaml
+16-3Lines changed: 16 additions & 3 deletions
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@@ -7,7 +7,7 @@ reviews:
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collapse_walkthrough: true
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sequence_diagrams: false
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poem: false
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request_changes_workflow: false
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request_changes_workflow: true
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review_status: false
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auto_review:
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enabled: true
@@ -22,6 +22,19 @@ reviews:
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gitleaks:
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enabled: true
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path_instructions:
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- path: "src/rapids_singlecell/**"
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instructions: |
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For every code change, check whether the PR includes adequate test coverage in tests/.
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If new functionality is added or existing behavior is changed and no tests are added or updated, flag this.
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However, if a change is a pure internal optimization (e.g., replacing CuPy operations with a fused kernel, rewriting a RawKernel as nanobind C++)
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and the existing tests already cover the affected behavior, new tests are not required — note this in the review.
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Codecov line-coverage numbers alone are not meaningful — check that tests verify the specific behavior being changed, not just that the code path is hit.
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Multi-GPU / cross-device: NEVER inline cross-device cp.asarray D2D copies with arithmetic
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(e.g., `sums += cp.asarray(data["sums"])`). This fuses allocation + copy + addition and can
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surface stale CUDA async errors through cudaMalloc (cudaErrorLaunchFailure), especially without
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RMM pool allocation. Always split into a separate assignment first:
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`dev0_sums = cp.asarray(data["sums"])` then `sums += dev0_sums`.
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Sync non-blocking streams explicitly, not the null stream.
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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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