Contributing to SGLang Diffusion - SGLang Documentation

This guide outlines the requirements for contributing to the SGLang Diffusion module (sglang.multimodal_gen).

Contributor Guides

Support New Models: implementation guide for adding new diffusion pipelines
Helper ownership: where to put shared and model-specific utilities
CI Performance: update and regenerate perf baselines
SGLang Plugin System: package a hardware platform outside the SGLang repository

On AI-Assisted (“Vibe Coding”) PRs

Vibe-coded PRs are welcome — we judge code quality, not how it was produced. The bar is the same for all PRs:

No over-commenting. If the name says it all, skip the docstring.
No over-catching. Don’t guard against errors that virtually never happen in practice.
Test before submitting. AI-generated code can be subtly wrong — verify correctness end-to-end.

Pull request titles

Follow the repository-wide PR title convention. Use diffusion as the scope, or diffusion/<submodule-or-model> when a more specific scope helps.

[Perf] diffusion/scheduler: Reduce scheduling overhead
[Fix] diffusion/cli: Fix argument parsing
[Feat] diffusion/wan: Add model support
[Doc] diffusion: Update the contribution guide
[Perf] [NVIDIA] diffusion/attention: Optimize attention kernels

Put the change type in the first bracketed tag. diffusion belongs in the scope, not in a hardware tag or a separate [Diffusion] prefix. Omit the hardware tag unless the change is hardware-specific.

Performance Reporting

For PRs that impact latency, throughput, or memory usage, you should provide a performance comparison report.

How to Generate a Report

Baseline: run the benchmark (for a single generation task)

$ sglang generate --model-path <model> --prompt "A benchmark prompt" --perf-dump-path baseline.json

New: run the same benchmark, without modifying any server_args or sampling_params

$ sglang generate --model-path <model> --prompt "A benchmark prompt" --perf-dump-path new.json

Compare: run the compare script, which will print a Markdown table to the console

$ python python/sglang/multimodal_gen/benchmarks/compare_perf.py baseline.json new.json [new2.json ...]
### Performance Comparison Report
...

Paste: paste the table into the PR description

CI-Based Change Protection

Consider adding tests to the pr-test or nightly-test suites to safeguard your changes, especially for PRs that:

support a new model
- add a testcase for this new model to testcase_configs.py
support or fix important features
significantly improve performance

Please run the according testcase, then update/add the baseline to perf_baselines.json by following the instruction in console if applicable. See test for examples

Out-of-tree platform changes

Use the sglang.multimodal_gen.platforms entry-point group when a hardware integration can live in a separately installed package. The plugin guide describes the activation callback, diffusion platform contract, and selection behavior. When you change the platform interface or discovery implementation in SGLang:

Add focused CPU-only tests with a fake OOT platform.
Run the relevant SRT plugin tests when changing shared hook-registry behavior.
Document workload-specific kernels or optimized paths that still require vendor integration.

​Contributor Guides

​On AI-Assisted (“Vibe Coding”) PRs

​Pull request titles

​Performance Reporting

​How to Generate a Report

​CI-Based Change Protection

​Out-of-tree platform changes