Fix AWQ with enable MLA (#2364)

python/sglang/srt/models/deepseek_v2.py

@@ -21,6 +21,7 @@
 import torch
 from torch import nn
 from transformers import PretrainedConfig
+from vllm import _custom_ops as ops
 from vllm.distributed import (
     get_tensor_model_parallel_rank,
     get_tensor_model_parallel_world_size,
@@ -894,7 +895,19 @@ def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
         if not global_server_args_dict["disable_mla"]:
             for layer_id in range(self.config.num_hidden_layers):
                 self_attn = self.model.layers[layer_id].self_attn
-                w_kc, w_vc = self_attn.kv_b_proj.weight.unflatten(
+                if hasattr(self_attn.kv_b_proj, "qweight"):
+                    # AWQ compatible
+                    w = ops.awq_dequantize(
+                        self_attn.kv_b_proj.qweight,
+                        self_attn.kv_b_proj.scales,
+                        self_attn.kv_b_proj.qzeros,
+                        0,
+                        0,
+                        0,
+                    ).T
+                else:
+                    w = self_attn.kv_b_proj.weight
+                w_kc, w_vc = w.unflatten(
                     0, (-1, self_attn.qk_nope_head_dim + self_attn.v_head_dim)
                 ).split([self_attn.qk_nope_head_dim, self_attn.v_head_dim], dim=1)
                 self_attn.w_kc = w_kc.transpose(1, 2).contiguous().transpose(1, 2)