vllm-omni/.claude/skills/add-diffusion-model/references/native-model-integration-checklist.md

Native Diffusion Model Integration Checklist

Use this checklist for native non-Diffusers models, hybrid pipelines, and model-specific optimization work.

1. Freeze the contract before coding

Record:

• Reference repository and immutable revision.
• Official checkpoint ID, local layout, license, and required auxiliary files.
• Pipeline stages: prompt/image encoding, denoising, video/image/audio decoding, and muxing.
• Token packing, RoPE coordinates, attention sinks/LSE behavior, MoE layout, scheduler equations, CFG formulation, dtypes, and checkpoint transforms.
• Output geometry, frame count/FPS, audio rate/channels, supported tasks, and default generation steps.
• Available local hardware versus the official qualification hardware.
• Intended default deployment and optional optimization paths.

State whether the deliverable is a native implementation or an external adapter. For native support, use the reference as an oracle only.

2. Use phase gates

Phase	Required exit evidence
Architecture	Component/weight inventory; unsupported reference dependencies identified; ownership decisions documented
Native correctness	Strict checkpoint load; tiny forward or one-step golden vs pinned reference; output contract validated
Framework integration	Registry/discovery, shared request types, existing category example, serving route, docs, and recipe work without model-name branching in shared scripts
Lossless distribution	One-rank oracle vs each supported TP/SP/CFG/HSDP/VAE layout; released-checkpoint smoke for the recommended layout
Memory optimization	Ordinary/layerwise/DLO behavior, peak HBM, full-tree host PSS, and stage timeline; shared backend unchanged unless a general contract is proven
Lossy optimization	Cache hit demonstrated; quality delta measured; speed claim made only when warmup permits hits
Full qualification	Default-resolution E2E at official step count for every supported task; media metadata and hashes recorded
Review readiness	Focused tests, Ruff/format, strict docs, DCO, current-main rebase, issue/RFC for large changes, concise PR evidence and limitations

Do not start performance tuning before native one-step parity. Do not claim a feature from topology validation alone when released weights can exercise it.

3. Keep ownership narrow

Default placement:

Concern	Owner
Architecture, checkpoint remap, packed attention math, nested block alias, auxiliary lifecycle	Model package
Kernel/version dispatch already useful to multiple models	Shared attention utility
Request-dependent example defaults	Typed model-extra entry consumed through a registry
Exact-ID/local-file detection for repositories without standard metadata	Generic native-checkpoint signature table
General offload/cache/HSDP bug	Shared layer plus one focused shared regression

Before changing shared code, answer:

1. Is this a framework contract or only this checkpoint's layout?
2. Can the model expose an existing declarative hook instead?
3. Is there a second consumer or a framework-level failing test?
4. Can the shared change avoid importing or naming the model?

If the answers do not justify a shared change, keep it model-local.

4. Reuse examples without leaking model logic

• Reuse the existing x_to_y.py category script.
• Resolve the pipeline class through standard metadata or native signature discovery, not path substrings.
• Put dynamic model defaults and validation in model_extras; let shared examples consume only the generic typed API.
• Do not create image/speech/default abstractions without a real consumer.
• Add a dedicated example only when the shared request/output protocol cannot express the model.

5. Build a bounded evidence matrix

Start with the recommended resident layout. Add only supported, useful points:

• Single request: TP, SP, or hybrid TP/SP.
• Throughput: DLO/DP layouts when concurrent requests are valid.
• CFG: compare CFG-parallel output with the packed-CFG oracle only if the model actually uses CFG.
• HSDP: record loading and materialization peaks; it can use more HBM than a resident SP layout.
• VAE patch parallelism: compare decoded tensors or media exactly where the algorithm should be lossless.
• Cache: separate cache integration from acceleration evidence.

With four devices, qualify four-device layouts such as DP4, DP2SP2, SP4, or CFG2xSP2. Do not present CFG2xSP4 or an official eight-device runtime as locally validated.

For each measured layout record:

• Cold E2E and warm user latency.
• Steady-state wave time and throughput per device.
• Prompt, denoise, video decode, audio decode, and mux times.
• Peak allocated/reserved HBM and full-process-tree host PSS.
• Step count, seed, output geometry, frame/FPS/audio metadata, and parity metric.

Plot latency versus throughput/device. Keep one-step, four-step, and full-step results separate because they are not quality-equivalent.

6. Keep tests proportional

Prefer a small set with distinct failure ownership:

1. Strict weight-key/dtype/load contract.
2. Tiny native golden or one-step reference parity.
3. One parametrized distributed-parity test covering supported layouts.
4. Pipeline/request/output geometry and serving smoke.
5. Shared-example/default test when the category script changes.
6. One shared regression only for a genuine shared-layer fix.

Avoid duplicating the same shape or configuration assertion across model-specific files. Keep expensive released-checkpoint evidence in the PR or recipe unless the repository's CI tier explicitly requires it.

7. Write evidence, not marketing

In the PR description include:

• A compact architecture/data-flow explanation.
• Default deployment and why it is recommended.
• Code-change counts by component.
• Accuracy and distributed-parity evidence tied to commands/scripts.
• Separate Pareto figures for different step counts.
• Supported versus validated versus planned optimizations.
• Hardware gaps and untested official-runtime claims.

Call a result a bounded local qualification unless it includes repeated timing and variance. State whether latency includes text/image encoding and all decoders. Preserve the reference revision and exact commands needed to reproduce the evidence.