2a7ca101d7
Sparse-checkout from NVIDIA/cccl main branch to complete cccl_upstream: Added: - python/cuda_cccl/ (226 files) — Python bindings for device-level algorithms Critical for muh toolchain: cuda.compute.reduce_into, scan, radix_sort, etc. Includes 204 .py files with full test coverage for all 27 algorithms - ci/ (163 files) — Build/test infrastructure build_cub.sh, test_cub.sh, build_and_test_targets.sh, matrix.yaml Directly maps to our [INFRA-CI] and [INFRA-BUILD] items - .agent/skills/ (7 files) — NVIDIA's own agent skills for CCCL cccl-style/SKILL.md, cccl-test/SKILL.md, sass-diff/SKILL.md - docs/ (491 files) — Official CCCL documentation CI references, CMake guides, Python compute docs, libcudacxx PTX docs - test/ (12 files) — Top-level integration tests (cuda_smoke, stdpar) - Root configs: .clang-format, .clang-tidy, CONTRIBUTING.md, pyproject.toml - CLAUDE.md symlink → AGENTS.md (NVIDIA's standard) cccl_upstream now mirrors full NVIDIA/cccl structure: Before: 42M (cub + thrust + libcudacxx + cudax + c + examples + benchmarks) After: 53M (+python +ci +docs +.agent +test +configs) This completes the CCCL base needed for: - [muh-bench] items: ci/util/build_and_test_targets.sh for targeted builds - [CCCL-verify] items: python/cuda_cccl/tests/ as reference implementations - [CCCL-test] items: ci/test_cub.sh, ci/test_thrust.sh - Agent workflow: .agent/skills/ for consistent style and test patterns
67 lines
2.6 KiB
ReStructuredText
67 lines
2.6 KiB
ReStructuredText
CodeRabbit
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==========
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This page explains how to configure and use CodeRabbit for CCCL pull request
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review. For the complete product documentation, see the
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`CodeRabbit documentation <https://docs.coderabbit.ai/>`__.
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Configuration
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-------------
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CCCL configures CodeRabbit through ``.coderabbit.yaml`` in the repository root.
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The configuration in the pull request branch is used for that review.
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When setting up or updating CodeRabbit:
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#. Keep repository-specific settings in ``.coderabbit.yaml``.
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#. Use ``@coderabbitai configuration`` on a pull request to inspect the
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resolved configuration. This is useful when checking whether CodeRabbit is
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using the expected repository settings for that pull request.
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#. Use ``@coderabbitai generate configuration`` to export the resolved
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configuration if a new baseline is needed. This is useful when moving
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settings into a reviewable repository configuration file.
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#. Keep configuration changes small and reviewable.
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#. Use ``reviews.path_instructions`` for path-specific review guidance.
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#. Use ``knowledge_base.code_guidelines.filePatterns`` for CCCL guidance files
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that CodeRabbit should read as review context.
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The CCCL configuration should keep comments focused on correctness, API
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stability, performance, security, and other high-impact issues. Avoid enabling
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features that add noisy generated comments or code by default.
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Pull Request Reviews
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--------------------
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Automatic reviews may be disabled or restricted by the repository
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configuration. Maintainers can always request review explicitly from a pull
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request comment:
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.. code-block:: text
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@coderabbitai review
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Use a full review when the pull request should be reviewed again from scratch:
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.. code-block:: text
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@coderabbitai full review
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Other useful commands:
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- ``@coderabbitai help`` shows the current command reference.
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- ``@coderabbitai configuration`` shows the active configuration.
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- ``@coderabbitai summary`` can be placed in the pull request description as a
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placeholder for the generated summary.
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- ``@coderabbitai pause`` and ``@coderabbitai resume`` pause or resume
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automatic review behavior. This is useful when a pull request is still being
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updated frequently and should not be reviewed again until it is ready.
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- ``@coderabbitai ignore`` can be placed in the pull request description to
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disable automatic reviews.
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Review Guidance
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---------------
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Treat CodeRabbit feedback as review assistance, not as a merge requirement by
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itself. Maintainers remain responsible for deciding whether comments are
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actionable and whether a pull request has adequate tests and CI coverage.
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