[ModelRunner][Refactor] Refactor kv cache tensor initialization logic #3106
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yiz-liu
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…ype (#3760) ### What this PR does / why we need it? Part of #3106 Fix Hybrid kvcache sharing bug in same attention type Change the `shared_by` logic so that the same attention spec could share the same buffer instead of allocating more hbm. After this pr, kvcache memory saved 50% in qwen3-next compared with before (`self_attn:linear_attn=1:3` in an `attn_group`), and `gpu_memory_utilization` could increase to `0.8` on Qwen3-Next when running on A2 64G/card with tp4 <img width="2833" height="1540" alt="image" src="https://github.com/user-attachments/assets/2a91fa99-fb0f-447c-9e8b-acd587890fbe" /> ### Does this PR introduce _any_ user-facing change? ### How was this patch tested? Test pass with the latest e2e test case on qwen3-next - vLLM version: v0.11.0rc3 - vLLM main: vllm-project/vllm@c9461e0 --------- Signed-off-by: MengqingCao <[email protected]>
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* Unify the kvcache tensor initialization logic of deepseek and normal models * spilt initialize_kv_cache_tensors into _allocate_kv_cache_tensors and _reshape_kv_cache_tensors, following gpu modelrunner in vllm * Fix the shared_by logic so that the same attention spec could share the same buffer instead of allocating more hbm. Signed-off-by: MengqingCao <[email protected]>
Signed-off-by: MengqingCao <[email protected]>
Signed-off-by: MengqingCao <[email protected]>
Signed-off-by: MengqingCao <[email protected]>
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What this PR does / why we need it?
Refactor kv cache tensor initialization logic.
initialize_kv_cache_tensorsinto_allocate_kv_cache_tensorsand_reshape_kv_cache_tensors, following gpu modelrunner in vllmDoes this PR introduce any user-facing change?
N/A
How was this patch tested?
CI passed with existing test.