[Fix] DO NOT skip save_kv_cache for dllm

[DarkSharpness]

Motivation

Fix #19019

TL;DR: DLLM needs to attend to kvcache, so we cannot skip save_kv_cache.

Modifications

Accuracy Tests

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[gemini-code-assist]

Summary of Changes

Hello @DarkSharpness, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request resolves a bug that prevented the Key-Value (KV) cache from being properly utilized in Distributed Large Language Models (DLLMs) under specific attention configurations. By adjusting the logic that determines when KV cache saving is skipped, the change ensures that DLLMs can correctly leverage this optimization, which is essential for efficient inference.

Highlights

• KV Cache Management for DLLMs: Modified the condition for skipping KV cache saving to ensure it is not skipped for Distributed Large Language Models (DLLMs) when using encoder-only attention. This addresses an identified bug where save_kv_cache was unintentionally disabled for DLLMs.

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Changelog

• python/sglang/srt/layers/attention/flashinfer_backend.py
  • Updated the conditional logic for save_kv_cache to explicitly allow KV cache saving for DLLM models.

Activity

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[gemini-code-assist]

Code Review

This pull request addresses a bug where the KV cache was not being saved for diffusion language models (dllm) that use encoder-only attention. The change correctly modifies the condition to avoid disabling save_kv_cache for these models, ensuring their KV cache is properly stored. The fix is accurate and well-targeted.

[BBuf]

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