[BugFix] Fix muls_add fusion not working for GLM5 models (#6928)

### What this PR does / why we need it?
fix: support model-specific routed_scaling_factor in muls_add fusion
Previously, MulsAddFusionPass used a hardcoded scale=1.0, which failed
to match the x * routed_scaling_factor + y pattern in models like GLM5
that use routed_scaling_factor=2.5. This caused the muls_add fusion to
be skipped, leaving unoptimized mul+add operations.

This fix reads routed_scaling_factor from model config (defaulting to
1.0
for backward compatibility) and uses it as the pattern scale, enabling
correct fusion for GLM5 and other models with custom scaling factors.

Fixes: Unoptimized mul+add in GLM5 attention blocks
Tested: GLM5-W8A8 with routed_scaling_factor=2.5
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.16.0
- vLLM main:
15d76f74e2

Signed-off-by: liuchenbing <chenliumail@163.com>
Co-authored-by: liuchenbing <chenliumail@163.com>

vllm_ascend/compilation/passes/muls_add_pass.py

@@ -95,10 +95,8 @@ class MulsAddFusionPass(VllmInductorPass):
             logger.debug("MulsAdd fusion not enabled: unsupported dtype %s", dtype)
             return
 
-        # Currently we only register a single pattern instance with a fixed
+        routed_scaling_factor = getattr(vllm_config.model_config.hf_text_config, "routed_scaling_factor", 1.0)
-        # scalar scale value. If needed, multiple instances with different
+        MulsAddPattern(vllm_config, scale=routed_scaling_factor).register(self.pattern_match_passes)
-        # scales can be added here in the future.
-        MulsAddPattern(vllm_config, scale=1.0).register(self.pattern_match_passes)
 
     def __call__(self, graph: torch.fx.Graph) -> None:  # type: ignore[override]
         self.begin()