| [feat] parameterize hardcoded MLA dimensions to support GLM5-W8A8 (#6902)
Derive MLA dimension constants (q_lora_rank, qk_nope_head_dim, etc.)
from tensor shapes at runtime instead of hardcoding DeepSeek V3 values.
This enables the mla_preprocess fused op to work with both DeepSeek V3
and GLM5 models without Python API changes.
- Add 9 dimension fields to MlaTilingData with DeepSeek V3 defaults
- Add OpParam fields and dynamize all host-side tiling functions
- Derive dimensions from wuk, gamma1, kv_cache_rope tensor shapes
- Replace 310+ hardcoded constants across 4 kernel .hpp files
- Remove unused MMSIZE1/MMSIZE2 constants
### What this PR does / why we need it?
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
https://github.com/vllm-project/vllm/commit/15d76f74e2fdb12a95ea00f0ca283acf6219a2b7
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Signed-off-by: liuchenbing <chenliumail@163.com>
Co-authored-by: liuchenbing <chenliumail@163.com> | 2 个月前 |