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[BugFix] Fix mlapo accuracy problem related with weight processing. (#3857)

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This PR fixes a mlapo accuracy problem related with weight processing.
Furthermore, modify mlapo related e2e test with quantized deepseek model
to make it effective.

Signed-off-by: whx-sjtu <2952154980@qq.com>
This commit is contained in:
whx
2025-10-30 00:35:50 +08:00
committed by GitHub
parent d9249c968e
commit 211d4b9da4
2 changed files with 2 additions and 18 deletions
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4
vllm_ascend/attention/mla_v1.py
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@@ -676,9 +676,9 @@ class AscendMLAImpl(MLAAttentionImpl):
..., self.q_lora_rank:].contiguous()
q_a_proj_wt = self.fused_qkv_a_proj.weight.data[
..., :self.q_lora_rank].contiguous()
kv_a_proj_wt = kv_a_proj_wt.contiguous()
kv_a_proj_wt = kv_a_proj_wt.t().contiguous()
kv_a_proj_wt = trans_rope_weight(kv_a_proj_wt, self.qk_rope_head_dim)
kv_a_proj_wt = kv_a_proj_wt.contiguous()
kv_a_proj_wt = kv_a_proj_wt.t().contiguous()
wd_qkv = torch.cat((kv_a_proj_wt, q_a_proj_wt), dim=-1)
wd_qkv = wd_qkv.t().contiguous()
wd_qkv = transdata(wd_qkv,