[Misc][Model][Refactor] Pass the prefix into Linear layers (#28259)

Signed-off-by: MengqingCao <cmq0113@163.com>

vllm/model_executor/models/baichuan.py

@@ -98,13 +98,22 @@ class BaiChuanMLP(nn.Module):
         intermediate_size: int,
         hidden_act: str,
         quant_config: QuantizationConfig | None = None,
+        prefix: str = "",
     ):
         super().__init__()
         self.gate_up_proj = MergedColumnParallelLinear(
-            hidden_size, [intermediate_size] * 2, bias=False, quant_config=quant_config
+            hidden_size,
+            [intermediate_size] * 2,
+            bias=False,
+            quant_config=quant_config,
+            prefix=f"{prefix}.gate_up_proj",
         )
         self.down_proj = RowParallelLinear(
-            intermediate_size, hidden_size, bias=False, quant_config=quant_config
+            intermediate_size,
+            hidden_size,
+            bias=False,
+            quant_config=quant_config,
+            prefix=f"{prefix}.down_proj",
         )
         if hidden_act != "silu":
             raise ValueError(
@@ -152,12 +161,14 @@ class BaiChuanAttention(nn.Module):
             self.total_num_heads,
             bias=False,
             quant_config=quant_config,
+            prefix=f"{prefix}.W_pack",
         )
         self.o_proj = RowParallelLinear(
             self.total_num_heads * self.head_dim,
             hidden_size,
             bias=False,
             quant_config=quant_config,
+            prefix=f"{prefix}.o_proj",
         )
         # Create the alibi slopes and slice them.
         if self.position_embedding == "ALIBI":
@@ -235,6 +246,7 @@ class BaiChuanDecoderLayer(nn.Module):
             intermediate_size=config.intermediate_size,
             hidden_act=config.hidden_act,
             quant_config=quant_config,
+            prefix=f"{prefix}.mlp",
         )
         self.input_layernorm = RMSNorm(config.hidden_size, eps=config.rms_norm_eps)
         self.post_attention_layernorm = RMSNorm(