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v0.15.0rc5 release prep (#622)
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.coderabbit.yaml

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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
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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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opt_out: false
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code_guidelines:
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filePatterns:
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- "python_agents.md"
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- "cuda_agents.md"
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- ".coderabbit/python_agents.md"
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- ".coderabbit/cuda_agents.md"
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- "docs/contributing.md"
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chat:
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auto_reply: true
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### 0.15.0 {small}`the-future`
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### 0.15.0rc5 {small}`2026-03-21`
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```{rubric} Features
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```

docs/release-notes/index.md

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## Version 0.15.0
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```{include} /release-notes/0.15.0.md
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```{include} /release-notes/0.15.0rc5.md
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```
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```{include} /release-notes/0.15.0rc4.md
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```

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