[BugFix] Fix mlapo accuracy problem related with weight processing. (#3850)

This PR fixes a mlapo accuracy problem related with weight processing.
Furthermore, add back mlapo related e2e test with quantized deepseek
model.


- vLLM version: v0.11.0rc3
- vLLM main:
vllm-project/vllm@83f478b

Signed-off-by: whx-sjtu <[email protected]>

Author: whx-sjtu

vllm_ascend/attention/mla_v1.py

@@ -826,9 +826,9 @@ def _process_weights_for_fused_mlapo(self, act_dtype: torch.dtype):
             ..., 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,