[Diffusion][HunyuanImage3] Add request paged prefix caching (#7719)

Signed-off-by: zwhzzz0821 <2831474076@qq.com>
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Yukim1 authored and GitHub committed 2026-09-23 15:34:56 +00:00
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@@ -164,3 +164,22 @@ batch may still pay compile or CUDA-graph capture cost.
For a Qwen-Image continuous-batching replay example, see
[`performance_dashboard/qwen_image_serving_performance.md`](./performance_dashboard/qwen_image_serving_performance.md).
## HunyuanImage3 reference-prefix reuse
The prefix-cache benchmark uses the unified `vllm bench serve --omni` runner,
not this legacy diffusion benchmark. It reuses the two-image IT2I input on a
single DiT stage, comparing dense, paged without caching, and paged with caching.
See [Shared-reference benchmark](../../docs/design/feature/prefix_caching.md#shared-reference-benchmark)
for the configuration, commands, and separate partial-hit accuracy coverage.
The accuracy regression compares paged-no-cache, partial-hit and exact-repeat
outputs against the checked-in official-repository reference-image goldens at
**50 steps, CFG=2.5, seeds 43/45** (both CFG branches remain on CFGP1).
It uses the AR-to-DiT image criteria: CLIP ≥ 90, SSIM ≥ 0.26, PSNR ≥ 12.5 dB.
`HUNYUAN_IMAGE3_INCLUDE_DENSE=1` adds dense as another comparison to the goldens.
It also requires actual reference-image hits and model-side query slicing,
and checks bitwise repeatability for repeated requests at the same hit boundary.
Images, logs, deployment YAMLs, hit traces and quality metrics are saved under
pytest's temporary output directory. `HUNYUAN_IMAGE3_MODEL` selects a local model;
DFX uses the repository's normal model/cache resolution.