[Diffusion][HunyuanImage3] Add request paged prefix caching (#7719)
Signed-off-by: zwhzzz0821 <2831474076@qq.com>
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@@ -164,3 +164,22 @@ batch may still pay compile or CUDA-graph capture cost.
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For a Qwen-Image continuous-batching replay example, see
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[`performance_dashboard/qwen_image_serving_performance.md`](./performance_dashboard/qwen_image_serving_performance.md).
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## HunyuanImage3 reference-prefix reuse
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The prefix-cache benchmark uses the unified `vllm bench serve --omni` runner,
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not this legacy diffusion benchmark. It reuses the two-image IT2I input on a
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single DiT stage, comparing dense, paged without caching, and paged with caching.
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See [Shared-reference benchmark](../../docs/design/feature/prefix_caching.md#shared-reference-benchmark)
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for the configuration, commands, and separate partial-hit accuracy coverage.
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The accuracy regression compares paged-no-cache, partial-hit and exact-repeat
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outputs against the checked-in official-repository reference-image goldens at
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**50 steps, CFG=2.5, seeds 43/45** (both CFG branches remain on CFGP1).
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It uses the AR-to-DiT image criteria: CLIP ≥ 90, SSIM ≥ 0.26, PSNR ≥ 12.5 dB.
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`HUNYUAN_IMAGE3_INCLUDE_DENSE=1` adds dense as another comparison to the goldens.
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It also requires actual reference-image hits and model-side query slicing,
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and checks bitwise repeatability for repeated requests at the same hit boundary.
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Images, logs, deployment YAMLs, hit traces and quality metrics are saved under
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pytest's temporary output directory. `HUNYUAN_IMAGE3_MODEL` selects a local model;
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DFX uses the repository's normal model/cache resolution.
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