graph-mode-internals
OfficialUnderstand graph mode internals end-to-end.
Software Engineering#model-inference#buffer-management#lmdeploy#backend-compatibility#graph-mode#graph-capture#dlinfer
AuthorDeepLink-org
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Understand the end-to-end graph mode workflow used by lmdeploy+dlinfer, including runner architecture, buffer management, capture/replay flows, and vendor differences.
Core Features & Use Cases
- Clarifies how graph mode captures and replays computations to reduce Python dispatch overhead.
- Details the buffer layout, KV cache handling, and per-step data flows across Ascend, Camb, MACA, and PPU backends.
- Provides practical guidance on common pitfalls and troubleshooting for graph-mode deployments.
Quick Start
Review the guide to understand how graph-mode capture and replay works and how to troubleshoot common issues.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: graph-mode-internals Download link: https://github.com/DeepLink-org/dlinfer/archive/main.zip#graph-mode-internals Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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