[bugfix] fix Error 'ValueError: Duplicate layer name' (#5280)

### What this PR does / why we need it?
When matmul_and_reduce is enabled, the prefix attribute is required.
However, in some models, the prefix is not passed correctly, causing
errors when starting the service.
The issue of incorrect prefix passing will be fixed in vLLM in the
future.

- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: Wang Kunpeng <1289706727@qq.com>

vllm_ascend/ops/linear_op.py

@@ -484,6 +484,10 @@ class SequenceColumnParallelOp(CustomColumnParallelOp):
 
 class SequenceRowParallelOp(CustomRowParallelOp):
 
+    def __init__(self, layer):
+        super().__init__(layer)
+        self.unique_prefix = None
+
     def apply_impl(
         self, input_: torch.Tensor
     ) -> Union[torch.Tensor, tuple[torch.Tensor, Optional[Parameter]]]:
@@ -509,7 +513,7 @@ class SequenceRowParallelOp(CustomRowParallelOp):
                                              bias=bias_)
         else:
             output = torch.ops.vllm.matmul_and_reduce(input_parallel,
-                                                      self.prefix)
+                                                      self.unique_prefix)
 
         output_bias = self.bias if self.skip_bias_add else None
         return output, output_bias
@@ -602,6 +606,7 @@ class SequenceRowParallelOp(CustomRowParallelOp):
         super().update_attrs()
         self.input_is_parallel = self.layer.input_is_parallel
         self.reduce_results = self.layer.reduce_results
+        self.unique_prefix = self.layer.unique_prefix
 
 
 def _get_column_parallel_op(