liger-kernel-dev
Develops production-ready Triton kernels for Liger Kernel. Creates new kernels from PyTorch operations (local files, URLs, code snippets, or natural language) with ops, module wrappers, functional APIs, unit tests, benchmarks, and plots. Also modifies existing Liger kernels. Use when adding a new Triton kernel, converting a PyTorch operation to Triton, or updating an existing Liger kernel.
适合你，如果经常编写或优化高性能 Triton 内核。
npx oh-my-skill add linkedin/liger-kernel/liger-kernel-devcurl -fsSL https://oh-my-skill.com/install.sh | bash -s -- linkedin/liger-kernel/liger-kernel-devnpx oh-my-skill verify linkedin/liger-kernel/liger-kernel-dev怎么用
商店整理自技能原文 · 版本 e9bbef0 · 表述以原文为准Claude可以帮你为Liger Kernel开发高效的Triton内核。它能从你提供的PyTorch代码（文件、网址、代码片段或描述）自动生成完整的Triton内核，包括操作、模块封装、函数API、测试和基准测试。也可以修改已有的内核。需要NVIDIA GPU。
当你要求创建新的Triton内核（如说“生成内核”、“添加内核”）或修改现有Liger内核（如“更新内核”、“修复内核”）时触发。
技能原文 SKILL.md
Liger Kernel Dev
Develops Triton kernels for Liger Kernel through a 3-stage pipeline with human review between stages. Supports creating new kernels and modifying existing ones. NVIDIA GPUs only.
Mode Detection
- Create mode: User asks to create/add/generate/write/build a new kernel → full pipeline
- Modify mode: User asks to update/fix/change/extend an existing kernel → skip Analyze, modify files, then Validate
Pipeline (Create Mode)
Stage 1: Analyze
Follow the Analyzer workflow in [analyzer.md](analyzer.md). If the host runtime supports parallel subagents, this stage may be delegated to one; otherwise execute the workflow directly.
Accepts any input: local file, URL, code snippet, natural language description, or model component reference. Produces a standalone PyTorch reference implementation and a kernel profile.
Human checkpoint: Present PyTorch reference + kernel profile. Confirm before proceeding.
Stage 2: Generate
Follow the Generator workflow in [generator.md](generator.md).
Generates/modifies up to 8 files:
src/liger_kernel/ops/{kernel}.py— NEW Triton kernels + autograd Functionsrc/liger_kernel/transformers/{kernel}.py— NEW nn.Module wrappersrc/liger_kernel/transformers/functional.py— MODIFY add functional APIsrc/liger_kernel/ops/__init__.py— MODIFY export Function classsrc/liger_kernel/transformers/__init__.py— MODIFY export Module +__all__test/transformers/test_{kernel}.py— NEW unit testsbenchmark/scripts/benchmark_{kernel}.py— NEW benchmark scriptbenchmark/data/all_benchmark_data.csv— MODIFY (after benchmarks run)
Human checkpoint: Present changes for review.
Stage 3: Validate
Follow the Validator workflow in [validator.md](validator.md).
Runs checkstyle, unit tests (hard gate — stops on persistent failure), benchmarks, and generates plots. Optionally runs ncu profiling.
Human checkpoint: Report final results with benchmark numbers and plots.
Pipeline (Modify Mode)
- Read existing kernel files to understand current implementation
- Understand the requested modification
- Make targeted changes (Generator handles this)
- Run full Validate stage (same as create mode)
Reference Files
- [kernel-profile-format.md](kernel-profile-format.md) — Kernel profile schema and field descriptions
- [examples/swiglu-profile.md](examples/swiglu-profile.md) — Tier 1 (element-wise) reference
- [examples/rms-norm-profile.md](examples/rms-norm-profile.md) — Tier 2 (reduction) reference
- [examples/cross-entropy-profile.md](examples/cross-entropy-profile.md) — Tier 3 (fused/complex) reference
- Templates in [templates/](templates/) — Code generation patterns for each file type